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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
2 23-47 Disease denotes coronavirus disease 2019 MESH:C000657245
3 49-57 Disease denotes COVID-19 MESH:C000657245
10 347-355 Species denotes patients Tax:9606
11 187-211 Disease denotes coronavirus disease 2019 MESH:C000657245
12 213-221 Disease denotes COVID-19 MESH:C000657245
13 337-346 Disease denotes pneumonia MESH:D011014
14 373-381 Disease denotes COVID-19 MESH:C000657245
15 434-442 Disease denotes COVID-19 MESH:C000657245
20 578-586 Species denotes patients Tax:9606
21 642-650 Species denotes Patients Tax:9606
22 539-547 Disease denotes COVID-19 MESH:C000657245
23 559-577 Disease denotes COVID-19 pneumonia MESH:C000657245
25 1442-1450 Disease denotes COVID-19 MESH:C000657245
30 1830-1838 Species denotes patients Tax:9606
31 1820-1829 Disease denotes pneumonia MESH:D011014
32 1856-1864 Disease denotes COVID-19 MESH:C000657245
33 2001-2009 Disease denotes COVID-19 MESH:C000657245
37 2094-2102 Species denotes patients Tax:9606
38 2084-2093 Disease denotes pneumonia MESH:D011014
39 2120-2128 Disease denotes COVID-19 MESH:C000657245
41 2176-2184 Disease denotes COVID-19 MESH:C000657245
51 2678-2725 Species denotes severe acute respiratory syndrome coronavirus 2 Tax:2697049
52 2727-2737 Species denotes SARS-CoV-2 Tax:2697049
53 3088-3135 Species denotes severe acute respiratory syndrome coronavirus 2 Tax:2697049
54 3137-3147 Species denotes SARS-CoV-2 Tax:2697049
55 3168-3186 Species denotes beta coronaviruses Tax:694002
56 3229-3274 Species denotes severe acute respiratory syndrome coronavirus Tax:694009
57 3276-3284 Species denotes SARS-Cov Tax:694009
58 3290-3345 Species denotes Middle East respiratory syndrome coronavirus (MERS-CoV) Tax:1335626
59 2821-2829 Disease denotes infected MESH:D007239
74 3351-3359 Species denotes Patients Tax:9606
75 3926-3934 Species denotes patients Tax:9606
76 4186-4194 Species denotes patients Tax:9606
77 3365-3373 Disease denotes COVID-19 MESH:C000657245
78 3382-3391 Disease denotes pneumonia MESH:D011014
79 3420-3425 Disease denotes fever MESH:D005334
80 3433-3438 Disease denotes cough MESH:D003371
81 3450-3457 Disease denotes myalgia MESH:D063806
82 3461-3468 Disease denotes fatigue MESH:D005221
83 3662-3670 Disease denotes COVID-19 MESH:C000657245
84 3985-3993 Disease denotes COVID-19 MESH:C000657245
85 4054-4063 Disease denotes pneumonia MESH:D011014
86 4176-4185 Disease denotes pneumonia MESH:D011014
87 4212-4220 Disease denotes COVID-19 MESH:C000657245
93 4621-4631 Species denotes SARS-CoV-2 Tax:2697049
94 4851-4859 Species denotes patients Tax:9606
95 4259-4267 Disease denotes COVID-19 MESH:C000657245
96 4836-4850 Disease denotes critically ill MESH:D016638
97 4897-4906 Disease denotes pneumonia MESH:D011014
101 5186-5194 Species denotes patients Tax:9606
102 5212-5220 Disease denotes COVID-19 MESH:C000657245
103 5263-5271 Disease denotes COVID-19 MESH:C000657245
105 5337-5345 Species denotes Patients Tax:9606
120 5576-5584 Species denotes patients Tax:9606
121 5734-5737 Species denotes men Tax:9606
122 5788-5793 Species denotes women Tax:9606
123 5842-5850 Species denotes patients Tax:9606
124 5953-5961 Species denotes patients Tax:9606
125 6110-6118 Species denotes patients Tax:9606
126 6149-6155 Species denotes People Tax:9606
127 6252-6255 Species denotes men Tax:9606
128 6307-6312 Species denotes women Tax:9606
129 6479-6486 Species denotes patient Tax:9606
130 5590-5598 Disease denotes COVID-19 MESH:C000657245
131 5871-5891 Disease denotes SARS-CoV-2 infection MESH:C000657245
132 6100-6109 Disease denotes pneumonia MESH:D011014
133 6127-6135 Disease denotes COVID-19 MESH:C000657245
143 6747-6755 Species denotes patients Tax:9606
144 6861-6869 Species denotes patients Tax:9606
145 6892-6900 Species denotes patients Tax:9606
146 6914-6920 Species denotes People Tax:9606
147 6939-6947 Species denotes patients Tax:9606
148 7136-7144 Species denotes patients Tax:9606
149 7207-7215 Species denotes patients Tax:9606
150 6852-6860 Disease denotes COVID-19 MESH:C000657245
151 7198-7206 Disease denotes COVID-19 MESH:C000657245
153 7680-7682 Disease denotes HD MESH:D006816
157 8412-8430 Gene denotes C-reactive protein Gene:1401
158 8438-8441 Gene denotes CRP Gene:1401
159 8072-8080 Species denotes patients Tax:9606
161 9731-9736 Disease denotes fever MESH:D005334
167 9086-9094 Disease denotes COVID-19 MESH:C000657245
168 9208-9217 Disease denotes infection MESH:D007239
169 9226-9235 Disease denotes infection MESH:D007239
170 9244-9253 Disease denotes infection MESH:D007239
171 9273-9282 Disease denotes infection MESH:D007239
175 10442-10450 Disease denotes COVID-19 MESH:C000657245
176 10459-10467 Disease denotes COVID-19 MESH:C000657245
177 10641-10649 Disease denotes COVID-19 MESH:C000657245
182 13223-13231 Species denotes patients Tax:9606
183 13197-13205 Disease denotes COVID-19 MESH:C000657245
184 13214-13222 Disease denotes COVID-19 MESH:C000657245
185 13350-13358 Disease denotes COVID-19 MESH:C000657245
188 12230-12239 Disease denotes infection MESH:D007239
189 12243-12251 Disease denotes COVID-19 MESH:C000657245
191 14251-14254 Chemical denotes dca MESH:D003999
194 15045-15053 Disease denotes COVID-19 MESH:C000657245
195 15063-15071 Disease denotes COVID-19 MESH:C000657245
199 14995-15003 Species denotes patients Tax:9606
200 15007-15015 Disease denotes COVID-19 MESH:C000657245
201 15024-15032 Disease denotes COVID-19 MESH:C000657245
203 16510-16513 Chemical denotes GGO
209 18124-18142 Gene denotes C-reactive protein Gene:1401
210 16839-16847 Disease denotes COVID-19 MESH:C000657245
211 16857-16865 Disease denotes COVID-19 MESH:C000657245
212 17340-17349 Disease denotes Dry cough MESH:D003371
213 17385-17392 Disease denotes Fatigue MESH:D005221
217 16789-16797 Species denotes patients Tax:9606
218 16801-16809 Disease denotes COVID-19 MESH:C000657245
219 16818-16826 Disease denotes COVID-19 MESH:C000657245
225 14353-14361 Species denotes patients Tax:9606
226 14379-14387 Disease denotes COVID-19 MESH:C000657245
227 14710-14717 Disease denotes fatigue MESH:D005221
228 14901-14909 Disease denotes COVID-19 MESH:C000657245
229 14937-14945 Disease denotes COVID-19 MESH:C000657245
245 18444-18452 Species denotes patients Tax:9606
246 18514-18522 Species denotes patients Tax:9606
247 18589-18597 Species denotes patients Tax:9606
248 18842-18850 Species denotes patients Tax:9606
249 18980-18988 Species denotes patients Tax:9606
250 19134-19142 Species denotes patients Tax:9606
251 18460-18468 Disease denotes COVID-19 MESH:C000657245
252 18505-18513 Disease denotes COVID-19 MESH:C000657245
253 18580-18588 Disease denotes COVID-19 MESH:C000657245
254 18833-18841 Disease denotes COVID-19 MESH:C000657245
255 18971-18979 Disease denotes COVID-19 MESH:C000657245
256 19125-19133 Disease denotes COVID-19 MESH:C000657245
257 19378-19395 Disease denotes pleural effusions MESH:D010996
258 19565-19573 Disease denotes COVID-19 MESH:C000657245
259 19582-19590 Disease denotes COVID-19 MESH:C000657245
278 20462-20465 Gene denotes CRP Gene:1401
279 20442-20460 Gene denotes C-creative protein Gene:1401
280 19657-19665 Species denotes patients Tax:9606
281 20147-20155 Species denotes patients Tax:9606
282 20343-20351 Species denotes patients Tax:9606
283 20608-20616 Species denotes patients Tax:9606
284 19683-19691 Disease denotes COVID-19 MESH:C000657245
285 19869-19874 Disease denotes fever MESH:D005334
286 19888-19897 Disease denotes dry cough MESH:D003371
287 19915-19922 Disease denotes fatigue MESH:D005221
288 20065-20083 Disease denotes COVID-19 pneumonia MESH:C000657245
289 20138-20146 Disease denotes COVID-19 MESH:C000657245
290 20260-20268 Disease denotes COVID-19 MESH:C000657245
291 20277-20285 Disease denotes COVID-19 MESH:C000657245
292 20303-20314 Disease denotes lymphopenia MESH:D008231
293 20334-20342 Disease denotes COVID-19 MESH:C000657245
294 20426-20434 Disease denotes COVID-19 MESH:C000657245
295 20599-20607 Disease denotes COVID-19 MESH:C000657245
300 21510-21515 Disease denotes Cough MESH:D003371
301 21526-21533 Disease denotes Fatigue MESH:D005221
302 21837-21842 Disease denotes Cough MESH:D003371
303 21853-21860 Disease denotes Fatigue MESH:D005221
305 23999-24007 Disease denotes COVID-19 MESH:C000657245
307 24974-24982 Disease denotes COVID-19 MESH:C000657245
310 25968-25976 Disease denotes COVID-19 MESH:C000657245
311 25982-25990 Disease denotes COVID-19 MESH:C000657245
316 25357-25362 Disease denotes cough MESH:D003371
317 25364-25371 Disease denotes fatigue MESH:D005221
318 25618-25626 Disease denotes COVID-19 MESH:C000657245
319 25627-25636 Disease denotes infection MESH:D007239
326 26133-26141 Species denotes patients Tax:9606
327 26123-26132 Disease denotes pneumonia MESH:D011014
328 26159-26167 Disease denotes COVID-19 MESH:C000657245
329 26339-26347 Disease denotes COVID-19 MESH:C000657245
330 26683-26691 Disease denotes COVID-19 MESH:C000657245
331 26692-26701 Disease denotes infection MESH:D007239
344 26956-26964 Species denotes patients Tax:9606
345 27475-27483 Species denotes patients Tax:9606
346 27981-27989 Species denotes patients Tax:9606
347 26970-26978 Disease denotes COVID-19 MESH:C000657245
348 26979-26988 Disease denotes infection MESH:D007239
349 27364-27372 Disease denotes COVID-19 MESH:C000657245
350 27489-27497 Disease denotes COVID-19 MESH:C000657245
351 27498-27507 Disease denotes infection MESH:D007239
352 27792-27803 Disease denotes lymphopenia MESH:D008231
353 27931-27942 Disease denotes lymphopenia MESH:D008231
354 27955-27963 Disease denotes COVID-19 MESH:C000657245
355 27972-27980 Disease denotes COVID-19 MESH:C000657245
361 28433-28435 Chemical denotes CR
362 28113-28121 Disease denotes COVID-19 MESH:C000657245
363 28368-28373 Disease denotes cough MESH:D003371
364 28378-28385 Disease denotes fatigue MESH:D005221
365 28562-28575 Disease denotes breast cancer MESH:D001943
369 29375-29382 Species denotes patient Tax:9606
370 29960-29968 Species denotes patients Tax:9606
371 29974-29982 Disease denotes COVID-19 MESH:C000657245
376 30196-30204 Species denotes patients Tax:9606
377 30186-30195 Disease denotes pneumonia MESH:D011014
378 30222-30230 Disease denotes COVID-19 MESH:C000657245
379 30457-30465 Disease denotes COVID-19 MESH:C000657245
381 31019-31027 Disease denotes COVID-19 MESH:C000657245

LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T1 1360-1364 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T2 1464-1468 Body_part denotes Lung http://purl.org/sig/ont/fma/fma7195
T3 3028-3034 Body_part denotes genome http://purl.org/sig/ont/fma/fma84116
T4 7525-7530 Body_part denotes chest http://purl.org/sig/ont/fma/fma9576
T5 8149-8153 Body_part denotes body http://purl.org/sig/ont/fma/fma256135
T6 8167-8172 Body_part denotes blood http://purl.org/sig/ont/fma/fma9670
T7 8183-8188 Body_part denotes heart http://purl.org/sig/ont/fma/fma7088
T8 8281-8297 Body_part denotes white blood cell http://purl.org/sig/ont/fma/fma62852
T9 8293-8297 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646
T10 8312-8322 Body_part denotes lymphocyte http://purl.org/sig/ont/fma/fma62863
T11 8340-8350 Body_part denotes lymphocyte http://purl.org/sig/ont/fma/fma62863
T12 8352-8362 Body_part denotes neutrophil http://purl.org/sig/ont/fma/fma62860
T13 8379-8389 Body_part denotes neutrophil http://purl.org/sig/ont/fma/fma62860
T14 8423-8430 Body_part denotes protein http://purl.org/sig/ont/fma/fma67257
T15 8448-8459 Body_part denotes erythrocyte http://purl.org/sig/ont/fma/fma62845
T16 8956-8960 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T17 9032-9036 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T18 9115-9119 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T19 9847-9863 Body_part denotes right upper lobe http://purl.org/sig/ont/fma/fma7333
T20 9947-9963 Body_part denotes right upper lobe http://purl.org/sig/ont/fma/fma7333
T21 9999-10014 Body_part denotes lung parenchyma http://purl.org/sig/ont/fma/fma27360
T22 13008-13012 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T23 14722-14738 Body_part denotes white blood cell http://purl.org/sig/ont/fma/fma62852
T24 14734-14738 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646
T25 17032-17037 Body_part denotes blood http://purl.org/sig/ont/fma/fma9670
T26 17103-17108 Body_part denotes blood http://purl.org/sig/ont/fma/fma9670
T27 17223-17228 Body_part denotes Heart http://purl.org/sig/ont/fma/fma7088
T28 17432-17438 Body_part denotes throat http://purl.org/sig/ont/fma/fma228738
T29 17513-17517 Body_part denotes nose http://purl.org/sig/ont/fma/fma46472
T30 17546-17562 Body_part denotes White blood cell http://purl.org/sig/ont/fma/fma62852
T31 17558-17562 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646
T32 17614-17630 Body_part denotes White blood cell http://purl.org/sig/ont/fma/fma62852
T33 17626-17630 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646
T34 17747-17757 Body_part denotes Lymphocyte http://purl.org/sig/ont/fma/fma62863
T35 17805-17815 Body_part denotes Lymphocyte http://purl.org/sig/ont/fma/fma62863
T36 17935-17945 Body_part denotes Neutrophil http://purl.org/sig/ont/fma/fma62860
T37 17996-18006 Body_part denotes Neutrophil http://purl.org/sig/ont/fma/fma62860
T38 18135-18142 Body_part denotes protein http://purl.org/sig/ont/fma/fma67257
T39 18489-18494 Body_part denotes chest http://purl.org/sig/ont/fma/fma9576
T40 19097-19101 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T41 19244-19258 Body_part denotes bronchial wall http://purl.org/sig/ont/fma/fma13121|http://purl.org/sig/ont/fma/fma67480
T43 19507-19511 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T44 19961-19966 Body_part denotes heart http://purl.org/sig/ont/fma/fma7088
T45 20182-20192 Body_part denotes lymphocyte http://purl.org/sig/ont/fma/fma62863
T46 20206-20216 Body_part denotes neutrophil http://purl.org/sig/ont/fma/fma62860
T47 20453-20460 Body_part denotes protein http://purl.org/sig/ont/fma/fma67257
T48 21434-21439 Body_part denotes Heart http://purl.org/sig/ont/fma/fma7088
T49 21477-21493 Body_part denotes White blood cell http://purl.org/sig/ont/fma/fma62852
T50 21489-21493 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646
T51 21542-21552 Body_part denotes Lymphocyte http://purl.org/sig/ont/fma/fma62863
T52 21760-21765 Body_part denotes Heart http://purl.org/sig/ont/fma/fma7088
T53 21804-21820 Body_part denotes White blood cell http://purl.org/sig/ont/fma/fma62852
T54 21816-21820 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646
T55 21871-21881 Body_part denotes Lymphocyte http://purl.org/sig/ont/fma/fma62863
T56 24520-24524 Body_part denotes axis http://purl.org/sig/ont/fma/fma12520
T57 25307-25312 Body_part denotes heart http://purl.org/sig/ont/fma/fma7088
T58 25333-25349 Body_part denotes white blood cell http://purl.org/sig/ont/fma/fma62852
T59 25345-25349 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646
T60 25376-25386 Body_part denotes lymphocyte http://purl.org/sig/ont/fma/fma62863
T61 26895-26899 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T62 27209-27214 Body_part denotes lungs http://purl.org/sig/ont/fma/fma68877
T63 27290-27294 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T64 27344-27348 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T65 27624-27628 Body_part denotes lung http://purl.org/sig/ont/fma/fma7195
T66 28342-28347 Body_part denotes heart http://purl.org/sig/ont/fma/fma7088
T67 28402-28412 Body_part denotes lymphocyte http://purl.org/sig/ont/fma/fma62863
T68 28562-28568 Body_part denotes breast http://purl.org/sig/ont/fma/fma9601

LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T1 1360-1364 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T2 1464-1468 Body_part denotes Lung http://purl.obolibrary.org/obo/UBERON_0002048
T3 7525-7530 Body_part denotes chest http://purl.obolibrary.org/obo/UBERON_0001443
T4 8167-8172 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T5 8183-8188 Body_part denotes heart http://purl.obolibrary.org/obo/UBERON_0000948
T6 8287-8292 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T7 8956-8960 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T8 9032-9036 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T9 9115-9119 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T10 9120-9124 Body_part denotes lobe http://purl.obolibrary.org/obo/UBERON_3010752
T11 9155-9159 Body_part denotes lobe http://purl.obolibrary.org/obo/UBERON_3010752
T12 9859-9863 Body_part denotes lobe http://purl.obolibrary.org/obo/UBERON_3010752
T13 9959-9963 Body_part denotes lobe http://purl.obolibrary.org/obo/UBERON_3010752
T14 9999-10014 Body_part denotes lung parenchyma http://purl.obolibrary.org/obo/UBERON_0008946
T15 9999-10003 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T16 10004-10014 Body_part denotes parenchyma http://purl.obolibrary.org/obo/UBERON_0000353
T17 12579-12584 Body_part denotes scale http://purl.obolibrary.org/obo/UBERON_0002542
T18 13008-13012 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T19 14728-14733 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T20 16399-16405 Body_part denotes vessel http://purl.obolibrary.org/obo/UBERON_0000055
T21 17032-17037 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T22 17103-17108 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T23 17223-17228 Body_part denotes Heart http://purl.obolibrary.org/obo/UBERON_0000948
T24 17432-17438 Body_part denotes throat http://purl.obolibrary.org/obo/UBERON_0000341
T25 17513-17517 Body_part denotes nose http://purl.obolibrary.org/obo/UBERON_0000004
T26 17552-17557 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T27 17620-17625 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T28 18489-18494 Body_part denotes chest http://purl.obolibrary.org/obo/UBERON_0001443
T29 19097-19101 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T30 19378-19395 Body_part denotes pleural effusions http://purl.obolibrary.org/obo/UBERON_0000175
T31 19459-19465 Body_part denotes vessel http://purl.obolibrary.org/obo/UBERON_0000055
T32 19507-19511 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T33 19961-19966 Body_part denotes heart http://purl.obolibrary.org/obo/UBERON_0000948
T34 21339-21345 Body_part denotes vessel http://purl.obolibrary.org/obo/UBERON_0000055
T35 21434-21439 Body_part denotes Heart http://purl.obolibrary.org/obo/UBERON_0000948
T36 21483-21488 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T37 21699-21705 Body_part denotes vessel http://purl.obolibrary.org/obo/UBERON_0000055
T38 21760-21765 Body_part denotes Heart http://purl.obolibrary.org/obo/UBERON_0000948
T39 21810-21815 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T40 25254-25260 Body_part denotes vessel http://purl.obolibrary.org/obo/UBERON_0000055
T41 25307-25312 Body_part denotes heart http://purl.obolibrary.org/obo/UBERON_0000948
T42 25339-25344 Body_part denotes blood http://purl.obolibrary.org/obo/UBERON_0000178
T43 25498-25503 Body_part denotes scale http://purl.obolibrary.org/obo/UBERON_0002542
T44 25553-25558 Body_part denotes scale http://purl.obolibrary.org/obo/UBERON_0002542
T45 25581-25586 Body_part denotes scale http://purl.obolibrary.org/obo/UBERON_0002542
T46 25817-25823 Body_part denotes vessel http://purl.obolibrary.org/obo/UBERON_0000055
T47 25953-25958 Body_part denotes scale http://purl.obolibrary.org/obo/UBERON_0002542
T48 26895-26899 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T49 27290-27294 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T50 27344-27348 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T51 27624-27628 Body_part denotes lung http://purl.obolibrary.org/obo/UBERON_0002048
T52 28297-28303 Body_part denotes vessel http://purl.obolibrary.org/obo/UBERON_0000055
T53 28342-28347 Body_part denotes heart http://purl.obolibrary.org/obo/UBERON_0000948
T54 28562-28568 Body_part denotes breast http://purl.obolibrary.org/obo/UBERON_0000310

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T1 23-47 Disease denotes coronavirus disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T2 49-57 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T3 187-211 Disease denotes coronavirus disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T4 213-221 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T5 337-346 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T6 373-381 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T7 434-442 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T8 539-547 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T9 559-567 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T10 568-577 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T11 1442-1450 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T12 1820-1829 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T13 1856-1864 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T14 2001-2009 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T15 2084-2093 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T16 2120-2128 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T17 2176-2184 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T18 2678-2725 Disease denotes severe acute respiratory syndrome coronavirus 2 http://purl.obolibrary.org/obo/MONDO_0100096
T19 2678-2711 Disease denotes severe acute respiratory syndrome http://purl.obolibrary.org/obo/MONDO_0005091
T20 2727-2735 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T21 3088-3135 Disease denotes severe acute respiratory syndrome coronavirus 2 http://purl.obolibrary.org/obo/MONDO_0100096
T22 3088-3121 Disease denotes severe acute respiratory syndrome http://purl.obolibrary.org/obo/MONDO_0005091
T23 3137-3145 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T24 3229-3262 Disease denotes severe acute respiratory syndrome http://purl.obolibrary.org/obo/MONDO_0005091
T25 3276-3280 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T26 3365-3373 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T27 3382-3391 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T28 3662-3670 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T29 3985-3993 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T30 4054-4063 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T31 4176-4185 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T32 4212-4220 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T33 4259-4267 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T34 4621-4629 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T35 4897-4906 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T36 5212-5220 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T37 5263-5271 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T38 5590-5598 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T39 5871-5879 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T40 5882-5891 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T41 6100-6109 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T42 6127-6135 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T43 6852-6860 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T44 7198-7206 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T45 7680-7682 Disease denotes HD http://purl.obolibrary.org/obo/MONDO_0007739
T46 8406-8409 Disease denotes PCT http://purl.obolibrary.org/obo/MONDO_0008296|http://purl.obolibrary.org/obo/MONDO_0015104
T48 9086-9094 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T49 9208-9217 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T50 9226-9235 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T51 9244-9253 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T52 9273-9282 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T53 10442-10450 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T54 10459-10467 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T55 10641-10649 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T56 12230-12239 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T57 12243-12251 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T58 13197-13205 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T59 13214-13222 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T60 13350-13358 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T61 14379-14387 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T62 14901-14909 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T63 14937-14945 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T64 15007-15015 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T65 15024-15032 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T66 15045-15053 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T67 15063-15071 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T68 16801-16809 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T69 16818-16826 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T70 16839-16847 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T71 16857-16865 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T72 17427-17438 Disease denotes Sore throat http://purl.obolibrary.org/obo/MONDO_0002258
T73 17507-17517 Disease denotes Runny nose http://purl.obolibrary.org/obo/MONDO_0003014
T74 18460-18468 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T75 18505-18513 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T76 18580-18588 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T77 18833-18841 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T78 18971-18979 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T79 19125-19133 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T80 19565-19573 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T81 19582-19590 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T82 19683-19691 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T83 20065-20073 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T84 20074-20083 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T85 20138-20146 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T86 20260-20268 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T87 20277-20285 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T88 20303-20314 Disease denotes lymphopenia http://purl.obolibrary.org/obo/MONDO_0003783
T89 20334-20342 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T90 20426-20434 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T91 20599-20607 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T92 23999-24007 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T93 24974-24982 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T94 25618-25626 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T95 25627-25636 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T96 25968-25976 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T97 25982-25990 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T98 26123-26132 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T99 26159-26167 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T100 26339-26347 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T101 26632-26635 Disease denotes PCT http://purl.obolibrary.org/obo/MONDO_0008296|http://purl.obolibrary.org/obo/MONDO_0015104
T103 26683-26691 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T104 26692-26701 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T105 26970-26978 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T106 26979-26988 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T107 27364-27372 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T108 27489-27497 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T109 27498-27507 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T110 27792-27803 Disease denotes lymphopenia http://purl.obolibrary.org/obo/MONDO_0003783
T111 27931-27942 Disease denotes lymphopenia http://purl.obolibrary.org/obo/MONDO_0003783
T112 27955-27963 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T113 27972-27980 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T114 28113-28121 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T115 28562-28575 Disease denotes breast cancer http://purl.obolibrary.org/obo/MONDO_0007254
T116 28569-28575 Disease denotes cancer http://purl.obolibrary.org/obo/MONDO_0004992
T117 29974-29982 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T118 30186-30195 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T119 30222-30230 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T120 30457-30465 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T121 31019-31027 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T1 0-1 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T2 113-114 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T3 144-154 http://purl.obolibrary.org/obo/BFO_0000030 denotes Objectives
T4 259-262 http://purl.obolibrary.org/obo/PR_000001343 denotes aim
T5 411-412 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T6 512-513 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T7 734-738 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T8 752-756 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T9 779-783 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T10 1360-1364 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T11 1360-1364 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T12 1464-1468 http://purl.obolibrary.org/obo/UBERON_0002048 denotes Lung
T13 1464-1468 http://www.ebi.ac.uk/efo/EFO_0000934 denotes Lung
T14 1680-1681 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T15 1887-1888 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T16 1951-1954 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T17 2153-2154 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T18 2642-2654 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T19 2661-2664 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T20 2751-2752 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T21 2817-2820 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T22 3199-3203 http://purl.obolibrary.org/obo/NCBITaxon_9397 denotes bats
T23 3497-3498 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T24 3936-3938 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T25 4294-4295 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T26 4309-4313 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T27 4539-4542 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T28 4583-4585 http://purl.obolibrary.org/obo/CLO_0050510 denotes 18
T29 4609-4616 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing
T30 4641-4642 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T31 4967-4968 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T32 5090-5094 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T33 5251-5252 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T34 5731-5733 http://purl.obolibrary.org/obo/CLO_0053794 denotes 41
T35 6436-6438 http://purl.obolibrary.org/obo/CLO_0002857 denotes E1
T36 6732-6733 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T37 6838-6839 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T38 7525-7530 http://www.ebi.ac.uk/efo/EFO_0000965 denotes chest
T39 7874-7875 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T40 7982-7984 http://purl.obolibrary.org/obo/CLO_0002857 denotes E1
T41 8167-8172 http://purl.obolibrary.org/obo/UBERON_0000178 denotes blood
T42 8167-8172 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T43 8183-8188 http://purl.obolibrary.org/obo/UBERON_0000948 denotes heart
T44 8183-8188 http://purl.obolibrary.org/obo/UBERON_0007100 denotes heart
T45 8183-8188 http://purl.obolibrary.org/obo/UBERON_0015228 denotes heart
T46 8183-8188 http://www.ebi.ac.uk/efo/EFO_0000815 denotes heart
T47 8287-8292 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T48 8293-8297 http://purl.obolibrary.org/obo/GO_0005623 denotes cell
T49 8448-8459 http://purl.obolibrary.org/obo/CL_0000232 denotes erythrocyte
T50 8764-8765 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T51 8956-8960 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T52 8956-8960 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T53 9032-9036 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T54 9032-9036 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T55 9062-9064 http://purl.obolibrary.org/obo/CLO_0050507 denotes 22
T56 9115-9119 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T57 9115-9119 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T58 9353-9354 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T59 9389-9390 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T60 9400-9402 http://purl.obolibrary.org/obo/CLO_0053794 denotes 41
T61 9594-9596 http://purl.obolibrary.org/obo/CLO_0002860 denotes E2
T62 9663-9664 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T63 9677-9683 http://purl.obolibrary.org/obo/UBERON_0003100 denotes female
T64 9689-9690 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T65 9771-9772 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T66 9999-10003 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T67 9999-10003 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T68 10317-10321 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T69 10344-10348 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T70 10356-10360 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T71 11193-11195 http://purl.obolibrary.org/obo/CLO_0002860 denotes E2
T72 11769-11770 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T73 12147-12148 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T74 12169-12170 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T75 12495-12496 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T76 12829-12831 http://purl.obolibrary.org/obo/CLO_0002861 denotes E3
T77 13008-13012 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T78 13008-13012 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T79 13744-13745 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T80 14409-14411 http://purl.obolibrary.org/obo/CLO_0053794 denotes 41
T81 14523-14525 http://purl.obolibrary.org/obo/CLO_0002861 denotes E3
T82 14728-14733 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T83 14734-14738 http://purl.obolibrary.org/obo/GO_0005623 denotes cell
T84 14841-14842 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T85 16073-16075 http://purl.obolibrary.org/obo/CLO_0050507 denotes 22
T86 16342-16344 http://purl.obolibrary.org/obo/CLO_0001313 denotes 36
T87 16377-16379 http://purl.obolibrary.org/obo/CLO_0001302 denotes 34
T88 16399-16405 http://purl.obolibrary.org/obo/UBERON_0000055 denotes vessel
T89 16486-16488 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T90 16733-16737 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T91 16755-16759 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T92 16889-16893 http://purl.obolibrary.org/obo/UBERON_0003101 denotes Male
T93 16889-16893 http://www.ebi.ac.uk/efo/EFO_0000970 denotes Male
T94 16907-16909 http://purl.obolibrary.org/obo/CLO_0053794 denotes 41
T95 16928-16934 http://purl.obolibrary.org/obo/UBERON_0003100 denotes Female
T96 17032-17037 http://purl.obolibrary.org/obo/UBERON_0000178 denotes blood
T97 17032-17037 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T98 17103-17108 http://purl.obolibrary.org/obo/UBERON_0000178 denotes blood
T99 17103-17108 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T100 17223-17228 http://purl.obolibrary.org/obo/UBERON_0000948 denotes Heart
T101 17223-17228 http://purl.obolibrary.org/obo/UBERON_0007100 denotes Heart
T102 17223-17228 http://purl.obolibrary.org/obo/UBERON_0015228 denotes Heart
T103 17223-17228 http://www.ebi.ac.uk/efo/EFO_0000815 denotes Heart
T104 17363-17365 http://purl.obolibrary.org/obo/CLO_0001382 denotes 48
T105 17405-17407 http://purl.obolibrary.org/obo/CLO_0050507 denotes 22
T106 17513-17517 http://www.ebi.ac.uk/efo/EFO_0000828 denotes nose
T107 17552-17557 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T108 17558-17562 http://purl.obolibrary.org/obo/GO_0005623 denotes cell
T109 17620-17625 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T110 17626-17630 http://purl.obolibrary.org/obo/GO_0005623 denotes cell
T111 17693-17695 http://purl.obolibrary.org/obo/CLO_0050509 denotes 27
T112 17882-17884 http://purl.obolibrary.org/obo/CLO_0001000 denotes 35
T113 18294-18298 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T114 18316-18320 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T115 18343-18347 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T116 18489-18494 http://www.ebi.ac.uk/efo/EFO_0000965 denotes chest
T117 18528-18529 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T118 19097-19101 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T119 19097-19101 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T120 19378-19395 http://purl.obolibrary.org/obo/UBERON_0000175 denotes pleural effusions
T121 19459-19465 http://purl.obolibrary.org/obo/UBERON_0000055 denotes vessel
T122 19507-19511 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T123 19507-19511 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T124 19961-19966 http://purl.obolibrary.org/obo/UBERON_0000948 denotes heart
T125 19961-19966 http://purl.obolibrary.org/obo/UBERON_0007100 denotes heart
T126 19961-19966 http://purl.obolibrary.org/obo/UBERON_0015228 denotes heart
T127 19961-19966 http://www.ebi.ac.uk/efo/EFO_0000815 denotes heart
T128 20227-20228 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T129 20724-20726 http://purl.obolibrary.org/obo/CLO_0050510 denotes 18
T130 21024-21026 http://purl.obolibrary.org/obo/CLO_0053794 denotes 41
T131 21339-21345 http://purl.obolibrary.org/obo/UBERON_0000055 denotes vessel
T132 21434-21439 http://purl.obolibrary.org/obo/UBERON_0000948 denotes Heart
T133 21434-21439 http://purl.obolibrary.org/obo/UBERON_0007100 denotes Heart
T134 21434-21439 http://purl.obolibrary.org/obo/UBERON_0015228 denotes Heart
T135 21434-21439 http://www.ebi.ac.uk/efo/EFO_0000815 denotes Heart
T136 21483-21488 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T137 21489-21493 http://purl.obolibrary.org/obo/GO_0005623 denotes cell
T138 21699-21705 http://purl.obolibrary.org/obo/UBERON_0000055 denotes vessel
T139 21760-21765 http://purl.obolibrary.org/obo/UBERON_0000948 denotes Heart
T140 21760-21765 http://purl.obolibrary.org/obo/UBERON_0007100 denotes Heart
T141 21760-21765 http://purl.obolibrary.org/obo/UBERON_0015228 denotes Heart
T142 21760-21765 http://www.ebi.ac.uk/efo/EFO_0000815 denotes Heart
T143 21810-21815 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T144 21816-21820 http://purl.obolibrary.org/obo/GO_0005623 denotes cell
T145 22628-22629 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T146 24024-24025 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T147 24043-24044 http://purl.obolibrary.org/obo/CLO_0001021 denotes b
T148 24389-24390 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T149 24697-24698 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T150 25254-25260 http://purl.obolibrary.org/obo/UBERON_0000055 denotes vessel
T151 25307-25312 http://purl.obolibrary.org/obo/UBERON_0000948 denotes heart
T152 25307-25312 http://purl.obolibrary.org/obo/UBERON_0007100 denotes heart
T153 25307-25312 http://purl.obolibrary.org/obo/UBERON_0015228 denotes heart
T154 25307-25312 http://www.ebi.ac.uk/efo/EFO_0000815 denotes heart
T155 25339-25344 http://www.ebi.ac.uk/efo/EFO_0000296 denotes blood
T156 25345-25349 http://purl.obolibrary.org/obo/GO_0005623 denotes cell
T157 25817-25823 http://purl.obolibrary.org/obo/UBERON_0000055 denotes vessel
T158 25855-25856 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T159 25884-25885 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T160 26670-26674 http://purl.obolibrary.org/obo/UBERON_0000473 denotes test
T161 26703-26704 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T162 26895-26899 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T163 26895-26899 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T164 26990-26996 http://purl.obolibrary.org/obo/CLO_0053003 denotes 11, 25
T165 27209-27214 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lungs
T166 27290-27294 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T167 27290-27294 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T168 27344-27348 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T169 27344-27348 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T170 27390-27391 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T171 27624-27628 http://purl.obolibrary.org/obo/UBERON_0002048 denotes lung
T172 27624-27628 http://www.ebi.ac.uk/efo/EFO_0000934 denotes lung
T173 27684-27686 http://purl.obolibrary.org/obo/CLO_0050507 denotes 22
T174 27869-27871 http://purl.obolibrary.org/obo/CLO_0050509 denotes 27
T175 28074-28077 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T176 28297-28303 http://purl.obolibrary.org/obo/UBERON_0000055 denotes vessel
T177 28342-28347 http://purl.obolibrary.org/obo/UBERON_0000948 denotes heart
T178 28342-28347 http://purl.obolibrary.org/obo/UBERON_0007100 denotes heart
T179 28342-28347 http://purl.obolibrary.org/obo/UBERON_0015228 denotes heart
T180 28342-28347 http://www.ebi.ac.uk/efo/EFO_0000815 denotes heart
T181 28562-28568 http://purl.obolibrary.org/obo/UBERON_0000310 denotes breast
T182 28674-28675 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T183 28895-28896 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T184 29102-29103 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T185 29194-29195 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T186 29222-29223 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T187 29355-29356 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T188 30006-30011 http://purl.obolibrary.org/obo/CLO_0009985 denotes focus
T189 30306-30307 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T190 30529-30531 http://purl.obolibrary.org/obo/CLO_0007074 denotes kb
T191 30529-30531 http://purl.obolibrary.org/obo/CLO_0051988 denotes kb
T192 30766-30769 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T193 31539-31542 http://purl.obolibrary.org/obo/CLO_0051582 denotes has

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 3168-3172 Chemical denotes beta http://purl.obolibrary.org/obo/CHEBI_10545
T2 4296-4308 Chemical denotes nucleic acid http://purl.obolibrary.org/obo/CHEBI_33696
T3 4304-4308 Chemical denotes acid http://purl.obolibrary.org/obo/CHEBI_37527
T4 5077-5089 Chemical denotes nucleic acid http://purl.obolibrary.org/obo/CHEBI_33696
T5 5085-5089 Chemical denotes acid http://purl.obolibrary.org/obo/CHEBI_37527
T6 6523-6528 Chemical denotes group http://purl.obolibrary.org/obo/CHEBI_24433
T7 7660-7662 Chemical denotes GE http://purl.obolibrary.org/obo/CHEBI_73801
T8 7680-7682 Chemical denotes HD http://purl.obolibrary.org/obo/CHEBI_73925
T9 8423-8430 Chemical denotes protein http://purl.obolibrary.org/obo/CHEBI_36080
T10 14910-14915 Chemical denotes group http://purl.obolibrary.org/obo/CHEBI_24433
T11 14946-14951 Chemical denotes group http://purl.obolibrary.org/obo/CHEBI_24433
T12 18135-18142 Chemical denotes protein http://purl.obolibrary.org/obo/CHEBI_36080
T13 18469-18474 Chemical denotes group http://purl.obolibrary.org/obo/CHEBI_24433
T14 20435-20440 Chemical denotes group http://purl.obolibrary.org/obo/CHEBI_24433
T15 20453-20460 Chemical denotes protein http://purl.obolibrary.org/obo/CHEBI_36080
T16 24885-24896 Chemical denotes application http://purl.obolibrary.org/obo/CHEBI_33232
T17 31316-31318 Chemical denotes GE http://purl.obolibrary.org/obo/CHEBI_73801

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T1 4327-4348 http://purl.obolibrary.org/obo/GO_0001171 denotes reverse transcription
T2 4335-4348 http://purl.obolibrary.org/obo/GO_0006351 denotes transcription
T3 17162-17173 http://purl.obolibrary.org/obo/GO_0045333 denotes Respiration
T4 17162-17173 http://purl.obolibrary.org/obo/GO_0007585 denotes Respiration
T5 19940-19951 http://purl.obolibrary.org/obo/GO_0045333 denotes respiration
T6 19940-19951 http://purl.obolibrary.org/obo/GO_0007585 denotes respiration
T7 21412-21423 http://purl.obolibrary.org/obo/GO_0045333 denotes Respiration
T8 21412-21423 http://purl.obolibrary.org/obo/GO_0007585 denotes Respiration
T9 21738-21749 http://purl.obolibrary.org/obo/GO_0045333 denotes Respiration
T10 21738-21749 http://purl.obolibrary.org/obo/GO_0007585 denotes Respiration
T11 25294-25305 http://purl.obolibrary.org/obo/GO_0045333 denotes respiration
T12 25294-25305 http://purl.obolibrary.org/obo/GO_0007585 denotes respiration
T13 25824-25836 http://purl.obolibrary.org/obo/GO_0035282 denotes segmentation
T14 28355-28366 http://purl.obolibrary.org/obo/GO_0045333 denotes respiration
T15 28355-28366 http://purl.obolibrary.org/obo/GO_0007585 denotes respiration
T16 29887-29895 http://purl.obolibrary.org/obo/GO_0007612 denotes learning

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T1 337-346 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T2 568-577 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T3 1820-1829 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T4 2084-2093 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T5 3382-3391 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T6 3420-3425 Phenotype denotes fever http://purl.obolibrary.org/obo/HP_0001945
T7 3433-3438 Phenotype denotes cough http://purl.obolibrary.org/obo/HP_0012735
T8 3450-3457 Phenotype denotes myalgia http://purl.obolibrary.org/obo/HP_0003326
T9 3461-3468 Phenotype denotes fatigue http://purl.obolibrary.org/obo/HP_0012378
T10 4054-4063 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T11 4176-4185 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T12 4897-4906 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T13 6100-6109 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T14 9731-9736 Phenotype denotes fever http://purl.obolibrary.org/obo/HP_0001945
T15 14710-14717 Phenotype denotes fatigue http://purl.obolibrary.org/obo/HP_0012378
T16 16292-16310 Phenotype denotes Pleural thickening http://purl.obolibrary.org/obo/HP_0031944
T17 17340-17349 Phenotype denotes Dry cough http://purl.obolibrary.org/obo/HP_0031246
T18 17385-17392 Phenotype denotes Fatigue http://purl.obolibrary.org/obo/HP_0012378
T19 17427-17438 Phenotype denotes Sore throat http://purl.obolibrary.org/obo/HP_0033050
T20 17507-17517 Phenotype denotes Runny nose http://purl.obolibrary.org/obo/HP_0031417
T21 19378-19395 Phenotype denotes pleural effusions http://purl.obolibrary.org/obo/HP_0002202
T22 19409-19427 Phenotype denotes pleural thickening http://purl.obolibrary.org/obo/HP_0031944
T23 19869-19874 Phenotype denotes fever http://purl.obolibrary.org/obo/HP_0001945
T24 19888-19897 Phenotype denotes dry cough http://purl.obolibrary.org/obo/HP_0031246
T25 19915-19922 Phenotype denotes fatigue http://purl.obolibrary.org/obo/HP_0012378
T26 20074-20083 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T27 20303-20314 Phenotype denotes lymphopenia http://purl.obolibrary.org/obo/HP_0001888
T28 21302-21320 Phenotype denotes Pleural thickening http://purl.obolibrary.org/obo/HP_0031944
T29 21510-21515 Phenotype denotes Cough http://purl.obolibrary.org/obo/HP_0012735
T30 21526-21533 Phenotype denotes Fatigue http://purl.obolibrary.org/obo/HP_0012378
T31 21837-21842 Phenotype denotes Cough http://purl.obolibrary.org/obo/HP_0012735
T32 21853-21860 Phenotype denotes Fatigue http://purl.obolibrary.org/obo/HP_0012378
T33 25357-25362 Phenotype denotes cough http://purl.obolibrary.org/obo/HP_0012735
T34 25364-25371 Phenotype denotes fatigue http://purl.obolibrary.org/obo/HP_0012378
T35 26123-26132 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T36 27758-27782 Phenotype denotes laboratory abnormalities http://purl.obolibrary.org/obo/HP_0001939
T37 27792-27803 Phenotype denotes lymphopenia http://purl.obolibrary.org/obo/HP_0001888
T38 27847-27864 Phenotype denotes immune deficiency http://purl.obolibrary.org/obo/HP_0002721
T39 27931-27942 Phenotype denotes lymphopenia http://purl.obolibrary.org/obo/HP_0001888
T40 28368-28373 Phenotype denotes cough http://purl.obolibrary.org/obo/HP_0012735
T41 28378-28385 Phenotype denotes fatigue http://purl.obolibrary.org/obo/HP_0012378
T42 28562-28575 Phenotype denotes breast cancer http://purl.obolibrary.org/obo/HP_0003002
T43 30186-30195 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090

0_colil

Id Subject Object Predicate Lexical cue
32300971-26037317-67437 10819-10821 26037317 denotes 23
32300971-30842125-67438 11966-11968 30842125 denotes 24
32300971-30842125-67439 28696-28698 30842125 denotes 24
32300971-31115618-67440 28913-28915 31115618 denotes 28
32300971-16505391-67441 29394-29396 16505391 denotes 29
32300971-29948074-67436 6610-6612 29948074 denotes 19
32300971-30093881-67436 6610-6612 30093881 denotes 19
32300971-30546304-67436 6610-6612 30546304 denotes 19

TEST0

Id Subject Object Predicate Lexical cue
32300971-31-37-67436 6610-6612 ["29948074", "30093881", "30546304"] denotes 19
32300971-68-74-67437 10819-10821 ["26037317"] denotes 23
32300971-197-203-67438 11966-11968 ["30842125"] denotes 24
32300971-195-201-67439 28696-28698 ["30842125"] denotes 24
32300971-18-24-67440 28913-28915 ["31115618"] denotes 28
32300971-100-106-67441 29394-29396 ["16505391"] denotes 29

2_test

Id Subject Object Predicate Lexical cue
32300971-29948074-29373584 6610-6612 29948074 denotes 19
32300971-30093881-29373584 6610-6612 30093881 denotes 19
32300971-30546304-29373584 6610-6612 30546304 denotes 19
32300971-26037317-29373585 10819-10821 26037317 denotes 23
32300971-30842125-29373586 11966-11968 30842125 denotes 24
32300971-30842125-29373587 28696-28698 30842125 denotes 24
32300971-31115618-29373588 28913-28915 31115618 denotes 28
32300971-16505391-29373589 29394-29396 16505391 denotes 29

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T1 0-133 Sentence denotes A diagnostic model for coronavirus disease 2019 (COVID-19) based on radiological semantic and clinical features: a multi-center study
T2 135-143 Sentence denotes Abstract
T3 144-154 Sentence denotes Objectives
T4 155-255 Sentence denotes Rapid and accurate diagnosis of coronavirus disease 2019 (COVID-19) is critical during the epidemic.
T5 256-502 Sentence denotes We aim to identify differences in CT imaging and clinical manifestations between pneumonia patients with and without COVID-19, and to develop and validate a diagnostic model for COVID-19 based on radiological semantic and clinical features alone.
T6 504-511 Sentence denotes Methods
T7 512-641 Sentence denotes A consecutive cohort of 70 COVID-19 and 66 non-COVID-19 pneumonia patients were retrospectively recruited from five institutions.
T8 642-718 Sentence denotes Patients were divided into primary (n = 98) and validation (n = 38) cohorts.
T9 719-857 Sentence denotes The chi-square test, Student’s t test, and Kruskal-Wallis H test were performed, comparing 1745 lesions and 67 features in the two groups.
T10 858-979 Sentence denotes Three models were constructed using radiological semantic and clinical features through multivariate logistic regression.
T11 980-1081 Sentence denotes Diagnostic efficacies of developed models were quantified by receiver operating characteristic curve.
T12 1082-1151 Sentence denotes Clinical usage was evaluated by decision curve analysis and nomogram.
T13 1153-1160 Sentence denotes Results
T14 1161-1279 Sentence denotes Eighteen radiological semantic features and seventeen clinical features were identified to be significantly different.
T15 1280-1463 Sentence denotes Besides ground-glass opacities (p = 0.032) and consolidation (p = 0.001) in the lung periphery, the lesion size (1–3 cm) is also significant for the diagnosis of COVID-19 (p = 0.027).
T16 1464-1522 Sentence denotes Lung score presents no significant difference (p = 0.417).
T17 1523-1624 Sentence denotes Three diagnostic models achieved an area under the curve value as high as 0.986 (95% CI 0.966~1.000).
T18 1625-1747 Sentence denotes The clinical and radiological semantic models provided a better diagnostic performance and more considerable net benefits.
T19 1749-1760 Sentence denotes Conclusions
T20 1761-1886 Sentence denotes Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished.
T21 1887-2010 Sentence denotes A model composed of radiological semantic and clinical features has an excellent performance for the diagnosis of COVID-19.
T22 2012-2022 Sentence denotes Key Points
T23 2023-2150 Sentence denotes • Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished.
T24 2151-2417 Sentence denotes • A diagnostic model for COVID-19 was developed and validated using radiological semantic and clinical features, which had an area under the curve value of 0.986 (95% CI 0.966~1.000) and 0.936 (95% CI 0.866~1.000) in the primary and validation cohorts, respectively.
T25 2419-2452 Sentence denotes Electronic supplementary material
T26 2453-2589 Sentence denotes The online version of this article (10.1007/s00330-020-06829-2) contains supplementary material, which is available to authorized users.
T27 2591-2603 Sentence denotes Introduction
T28 2604-2802 Sentence denotes On January 30, 2020, the World Health Organization (WHO) has declared the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak as a global health emergency of international concern.
T29 2803-2897 Sentence denotes This outbreak has infected all provinces of China and rapidly spread to the rest of the world.
T30 2898-3021 Sentence denotes At the time of writing this article (March 16, 2020), there have been more than 158 countries and territories affected [1].
T31 3022-3350 Sentence denotes Whole-genome sequencing and phylogenetic analysis reveal that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is similar to some beta coronaviruses detected in bats, but it is distinct from severe acute respiratory syndrome coronavirus (SARS-Cov) and Middle East respiratory syndrome coronavirus (MERS-CoV) [2].
T32 3351-3479 Sentence denotes Patients with COVID-19 develop pneumonia with associated symptoms of fever (98%), cough (76%), and myalgia or fatigue (44%) [3].
T33 3480-3578 Sentence denotes CT imaging plays a critical role in the diagnosis and the monitoring of disease progression [4–6].
T34 3579-3806 Sentence denotes The latest research studies described the characteristic imaging manifestations of COVID-19, including ground-glass opacities (GGO) (57 to 88%), bilateral involvement (76 to 88%), and peripheral distribution (33 to 85%) [7–10].
T35 3807-3943 Sentence denotes Other imaging features such as consolidation, cavitation, and interlobular septal thickening are also reported in some patients [11–13].
T36 3944-4064 Sentence denotes However, these imaging manifestations of COVID-19 are nonspecific and are difficult to distinguish from other pneumonia.
T37 4065-4221 Sentence denotes To our knowledge, there have been no studies explicitly comparing imaging and clinical characteristics between pneumonia patients with and without COVID-19.
T38 4222-4419 Sentence denotes The current diagnostic criterion for COVID-19 is the positive result of a nucleic acid test by real-time reverse transcription polymerase chain reaction (RT-PCR) or next-generation sequencing [14].
T39 4420-4587 Sentence denotes However, false-negative results caused by unstable specimen processing are relatively high in clinical practice, which has worsened the spread of the outbreak [15–18].
T40 4588-4702 Sentence denotes Moreover, laboratory testing for SARS-CoV-2 requires a rigorous platform, which is not assembled in all hospitals.
T41 4703-4777 Sentence denotes Thus, this requires specimen transfer, which may delay diagnosis for days.
T42 4778-4921 Sentence denotes Early and accurate diagnosis is crucial, particularly for critically ill patients who need emergency surgery, and with pneumonia complications.
T43 4922-5095 Sentence denotes To solve these problems, we hypothesize that a diagnostic model can be developed based on CT imaging and clinical manifestations alone, independent of the nucleic acid test.
T44 5096-5221 Sentence denotes In this study, we identify the differences in imaging and clinical manifestations between patients with and without COVID-19.
T45 5222-5335 Sentence denotes We also develop and validate a model for COVID-19 diagnosis based on radiological semantic and clinical features.
T46 5337-5357 Sentence denotes Patients and methods
T47 5359-5367 Sentence denotes Patients
T48 5368-5519 Sentence denotes Ethical approvals by the institutional review boards were obtained for this retrospective analysis, and the need to obtain informed consent was waived.
T49 5520-5837 Sentence denotes From January 1 to February 8, 2020, seventy consecutive patients with COVID-19 admitted in 5 independent hospitals from 4 cities were enrolled in this study (mean age, 42.9 years; range, 16–69 years), including 41 men (mean age, 41.8 years; range, 16–69 years) and 29 women (mean age, 44.5 years; range, 16–66 years).
T50 5838-5943 Sentence denotes All patients were confirmed with SARS-CoV-2 infection by real-time RT-PCR and next-generation sequencing.
T51 5944-6068 Sentence denotes Of these patients, 24 were from Huizhou City, 25 from Shantou City, 15 from Yongzhou City, and the rest 6 from Meizhou City.
T52 6069-6355 Sentence denotes At the same period, another 66 pneumonia patients without COVID-19 from Meizhou People’s Hospital were recruited as controls (mean age, 46.7 years; range, 0.3–93 years), including 43 men (mean age, 46.0 years; range, 0.3–93 years) and 23 women (mean age, 48.0 years; range, 1–86 years).
T53 6356-6428 Sentence denotes All the controls were confirmed with consecutive negative RT-PCR assays.
T54 6429-6578 Sentence denotes Figure E1 in the Supplementary Material shows the patient recruitment pathway for the control group, along with the inclusion and exclusion criteria.
T55 6579-6716 Sentence denotes According to previous studies [19–21], whose sample size is comparable with ours, the ratio between primary and validation cohort is 7:3.
T56 6717-6837 Sentence denotes In this study, a total of 136 patients were divided into primary (n = 98) and validation (n = 38) cohorts, close to 7:3.
T57 6838-7119 Sentence denotes A total of 19 COVID-19 patients from two hospitals (6 patients from Meizhou People’s Hospital and 13 patients from the First Affiliated Hospital of Shantou University Medical College) and 19 randomly selected controls from Meizhou City were incorporated into the validation cohort.
T58 7120-7293 Sentence denotes The rest of the patients are incorporated in the primary cohort, including 51 COVID-19 patients from Huizhou, Yongzhou, and Shantou cities and 47 controls from Meizhou City.
T59 7294-7484 Sentence denotes The primary cohort was utilized to select the most valuable features and build the predictive model, and the validation cohort was used to evaluate and validate the performance of the model.
T60 7486-7520 Sentence denotes Image and clinical data collection
T61 7521-7821 Sentence denotes The chest CT imaging data without contrast material enhancement were obtained from multiple hospitals with different CT systems, including GE CT Discovery 750 HD (General Electric Company), SCENARIA 64 CT (Hitachi Medical), Philips Ingenuity CT (PHILIPS), and Siemens SOMATOM Definition AS (Siemens).
T62 7822-7896 Sentence denotes All images were reconstructed into 1-mm slices with a slice gap of 0.8 mm.
T63 7897-7986 Sentence denotes Detailed acquisition parameters were summarized in the Supplementary Material (Table E1).
T64 7987-8081 Sentence denotes The clinical history, nursing records, and laboratory findings were reviewed for all patients.
T65 8082-8274 Sentence denotes Clinical characteristics, including demographic information, daily body temperature, blood pressure, heart rate, clinical symptoms, and history of exposure to epidemic centers, were collected.
T66 8275-8499 Sentence denotes Total white blood cell (WBC) counts, lymphocyte counts, ratio of lymphocyte, neutrophil count, ratio of neutrophil, procalcitonin (PCT), C-reactive protein level (CRP), and erythrocyte sedimentation rate (ESR) were measured.
T67 8500-8615 Sentence denotes All threshold values chosen for laboratory metrics were based on the normal ranges set by each individual hospital.
T68 8617-8631 Sentence denotes Image analysis
T69 8632-8821 Sentence denotes For extraction of radiological semantic features, two senior radiologists (D.L. and X.C., more than 15 years of experience) reached a consensus, blinded to clinical and laboratory findings.
T70 8822-8917 Sentence denotes The radiological semantic features included both qualitative and quantitative imaging features.
T71 8918-9066 Sentence denotes The lesions in the outer third of the lung were defined as peripheral, and lesions in the inner two-thirds of the lung were defined as central [22].
T72 9067-9297 Sentence denotes The progression of COVID-19 lesions within each lung lobe was evaluated by scoring each lobe from 0 to 4 [7], corresponding to normal, 1~25% infection, 26~50% infection, 51~75% infection, and more than 75% infection, respectively.
T73 9298-9388 Sentence denotes The scores were combined for all five lobes to provide a total score ranging from 0 to 20.
T74 9389-9494 Sentence denotes A total of 41 radiological features (26 quantitative and 15 qualitative) were extracted for the analysis.
T75 9495-9598 Sentence denotes The descriptions of radiological semantic features are listed in the Supplementary Material (Table E2).
T76 9599-9655 Sentence denotes Figure 1 is one example of the evaluation of CT imaging.
T77 9656-9737 Sentence denotes Fig. 1 A 23-year-old female with a travel history to Wuhan presenting with fever.
T78 9738-9864 Sentence denotes Axial noncontrast CT image shows a consolidation with ground-glass opacities in the peripheral region by the right upper lobe.
T79 9865-9900 Sentence denotes Air bronchogram is found in lesion.
T80 9901-9942 Sentence denotes The maximum diameter of lesion is 2.8 cm.
T81 9943-10028 Sentence denotes The right upper lobe score is 1 because of the involved lung parenchyma less than 1/4
T82 10030-10073 Sentence denotes Clinical and radiological feature selection
T83 10074-10276 Sentence denotes To obtain the most valuable clinical and radiological semantic features, statistical analysis, univariate analysis, and the least absolute shrinkage and selection operator (LASSO) method were performed.
T84 10277-10475 Sentence denotes In statistical analysis, the chi-square test, the Kruskal-Wallis H test, and t test were utilized to compare the radiological semantic and clinical features between COVID-19 and non-COVID-19 groups.
T85 10476-10534 Sentence denotes The features with p value smaller than 0.05 were selected.
T86 10535-10663 Sentence denotes Then, univariate analysis was performed for clinical and radiological candidate features to determine the COVID-19 risk factors.
T87 10664-10750 Sentence denotes The features with p value smaller than 0.05 in univariate analysis were also selected.
T88 10751-10974 Sentence denotes The least absolute shrinkage and selection operator (LASSO) method [23] was utilized to select the most useful features with penalty parameter tuning that was conducted by 10-fold cross-validation based on minimum criteria.
T89 10975-11078 Sentence denotes Diagnostic models were then constructed by multivariate logistic regression with the selected features.
T90 11079-11197 Sentence denotes The flowchart of the feature selection process for these models was presented in the Supplementary Material (Fig. E2).
T91 11199-11249 Sentence denotes Development and validation of the diagnostic model
T92 11250-11545 Sentence denotes To develop an optimal model, we evaluated 3 models by analyzing (i) the clinical features model (C model), (ii) radiological semantic features model (R model), and (iii) the combination of clinical and radiological semantic features model (CR model) by multivariate logistic regression analysis.
T93 11546-11675 Sentence denotes The classification performances of the models were evaluated by the area under the receiver operating characteristic (ROC) curve.
T94 11676-11768 Sentence denotes The area under the curve (AUC), accuracy, sensitivity, and specificity were also calculated.
T95 11769-11970 Sentence denotes A decision curve analysis was conducted to determine the clinical usefulness of the diagnostic model by quantifying the net benefits at different threshold probabilities in the validation dataset [24].
T96 11971-12050 Sentence denotes The development of decision curve was described in the Supplementary Materials.
T97 12051-12132 Sentence denotes Figure 2 depicts the flowchart of the proposed analysis pipeline described above.
T98 12133-12337 Sentence denotes We also built a nomogram, which was a quantitative tool to predict the individual probability of infection by COVID-19, based on the multivariate logistic analysis of the CR model with the primary cohort.
T99 12338-12494 Sentence denotes Depending on the coefficient of the predictive factors in multivariate logistic regression model, all values of each predictive factor were assigned points.
T100 12495-12574 Sentence denotes A total point was obtained by summing all the points of each predictive factor.
T101 12575-12685 Sentence denotes The scale also showed the relationship between the total point and the prediction probability in the nomogram.
T102 12686-12833 Sentence denotes The corresponding calibration curves of the CR model in the primary cohort and validation cohort are shown in the Supplementary Material (Fig. E3).
T103 12834-12893 Sentence denotes Fig. 2 Workflow of data process and analysis in this study.
T104 12894-13024 Sentence denotes Radiological semantic features, including qualitative and quantitative imaging features, are extracted from axial lung CT section.
T105 13025-13117 Sentence denotes The clinical manifestation and laboratory parameters are provided by electronic case system.
T106 13118-13232 Sentence denotes Statistical analysis is performed for comparing the different features between COVID-19 and non-COVID-19 patients.
T107 13233-13410 Sentence denotes Univariate analysis, least absolute shrinkage, and selection operator (LASSO) are further performed to determine the COVID-19 risk factors with p < 0.05 in statistical analysis.
T108 13411-13507 Sentence denotes Three models based on the selected features are established by multivariate logistic regression.
T109 13508-13650 Sentence denotes These models include radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model).
T110 13651-13828 Sentence denotes The performance and clinical benefits of the prediction model are assessed by the area under a receiver operating characteristic (ROC) curve and the decision curve, respectively
T111 13830-13850 Sentence denotes Statistical analysis
T112 13851-13911 Sentence denotes Statistical analysis was conducted with R software (Version:
T113 13912-13945 Sentence denotes 3.6.4, http: www.r-project.org/).
T114 13946-14054 Sentence denotes The reported significance levels were all two-sided, and the statistical significance level was set to 0.05.
T115 14055-14140 Sentence denotes The multivariate logistic regression analysis was performed with the “stats” package.
T116 14141-14201 Sentence denotes Nomogram construction was performed using the “rms” package.
T117 14202-14255 Sentence denotes Decision curve analysis was performed using the “dca.
T118 14256-14267 Sentence denotes R” package.
T119 14269-14276 Sentence denotes Results
T120 14278-14328 Sentence denotes Imaging and clinical manifestations between groups
T121 14329-14534 Sentence denotes The differences between patients with and without COVID-19 for all 67 features (41 imaging and 26 critical clinical features) are shown in Tables 1 and 2 and the Supplementary Materials (Tables E3 and E4).
T122 14535-14682 Sentence denotes The differences between the primary cohort and validation cohort for the same features are shown in the Supplementary Materials (Tables E5 and E6).
T123 14683-14840 Sentence denotes All characteristics except fatigue and white blood cell count in the CR model presented no significant difference between the primary and validation cohorts.
T124 14841-14952 Sentence denotes A total of 1745 lesions were identified, with 1062 from the COVID-19 group and 683 from the non-COVID-19 group.
T125 14953-15032 Sentence denotes Table 1 Radiological semantic features of patients in COVID-19 and non-COVID-19
T126 15033-15088 Sentence denotes Feature Non-COVID-19 (n = 66) COVID-19 (n = 70) p value
T127 15089-15107 Sentence denotes Number of pure GGO
T128 15108-15160 Sentence denotes   Total# 1.00 (0.00, 5.05) 3.50 (0.95, 8.05) 0.018b*
T129 15161-15223 Sentence denotes   Peripheral area# 1.00 (0.00, 4.05) 2.00 (0.00, 6.05) 0.032b*
T130 15224-15311 Sentence denotes   Central/both peripheral and central area# 0.00 (0.00, 0.00) 0.00 (0.00, 2.00) 0.001b*
T131 15312-15331 Sentence denotes Number of mixed GGO
T132 15332-15384 Sentence denotes   Total# 1.00 (0.00, 3.05) 3.00 (1.00, 9.00) 0.001b*
T133 15385-15449 Sentence denotes   Peripheral area# 0.00 (0.00, 2.00) 2.50 (1.00, 6.00) < 0.001b*
T134 15450-15536 Sentence denotes   Central/both peripheral and central area# 0.00 (0.00, 1.05) 0.00 (0.00, 2.00) 0.657b
T135 15537-15566 Sentence denotes Total number of consolidation
T136 15567-15627 Sentence denotes   Consolidation# 1.00 (0.00, 3.00) 0.00 (0.00, 0.05) 0.001b*
T137 15628-15692 Sentence denotes   Pure solid nodules# 0.00 (0.00, 0.00) 0.00 (0.00, 0.00) 0.309b
T138 15693-15762 Sentence denotes   Solid nodules with GGO# 0.00 (0.00, 0.00) 0.00 (0.00, 1.00) 0.033b*
T139 15763-15786 Sentence denotes Total number of lesions
T140 15787-15849 Sentence denotes   Peripheral area# 5.00 (2.00, 9.05) 7.00 (2.00, 13.00) 0.112b
T141 15850-15908 Sentence denotes   Central area# 0.00 (0.00, 3.00) 0.00 (0.00, 1.05) 0.960b
T142 15909-15987 Sentence denotes   Both peripheral and central area# 0.00 (0.00, 2.00) 0.00 (0.00, 2.05) 0.582b
T143 15988-16026 Sentence denotes Interlobular septal thickening 0.009a*
T144 16027-16061 Sentence denotes   Negative 44 (66.67%) 31 (44.29%)
T145 16062-16096 Sentence denotes   Positive 22 (33.33%) 39 (55.71%)
T146 16097-16127 Sentence denotes Crazy paving pattern < 0.001a*
T147 16128-16162 Sentence denotes   Negative 60 (90.91%) 32 (45.71%)
T148 16163-16195 Sentence denotes   Positive 6 (9.09%) 38 (54.29%)
T149 16196-16222 Sentence denotes Tree-in-bud sign < 0.001a*
T150 16223-16257 Sentence denotes   Negative 37 (56.06%) 61 (87.14%)
T151 16258-16291 Sentence denotes   Positive 29 (43.94%) 9 (12.86%)
T152 16292-16318 Sentence denotes Pleural thickening 0.030a*
T153 16319-16353 Sentence denotes   Negative 46 (69.70%) 36 (51.43%)
T154 16354-16388 Sentence denotes   Positive 20 (30.30%) 34 (48.57%)
T155 16389-16439 Sentence denotes Offending vessel augmentation in lesions < 0.001a*
T156 16440-16474 Sentence denotes   Negative 55 (83.33%) 17 (24.29%)
T157 16475-16509 Sentence denotes   Positive 11 (16.67%) 53 (75.71%)
T158 16510-16536 Sentence denotes GGO ground-glass opacities
T159 16537-16680 Sentence denotes #Results are median with interquartile range in parentheses, and the remainder results are measurements with corresponding ratio in parentheses
T160 16681-16742 Sentence denotes *Data with statistical significance. pa: chi-square test, pb:
T161 16743-16759 Sentence denotes Student’s t test
T162 16760-16826 Sentence denotes Table 2 Clinical features of patients in COVID-19 and non-COVID-19
T163 16827-16882 Sentence denotes Feature Non-COVID-19 (n = 66) COVID-19 (n = 70) p value
T164 16883-16886 Sentence denotes Sex
T165 16887-16925 Sentence denotes   Male# 43 (65.15%) 41 (58.57%) 0.430a
T166 16926-16959 Sentence denotes   Female# 23 (34.85%) 29 (41.43%)
T167 16960-17008 Sentence denotes   Age (years) 46.73 ± 25.00 42.93 ± 13.32 0.275b
T168 17009-17020 Sentence denotes Vital signs
T169 17021-17090 Sentence denotes   Systolic blood pressure (mmHg) 126.92 ± 23.07 127.07 ± 15.16 0.965b
T170 17091-17159 Sentence denotes   Diastolic blood pressure (mmHg) 77.74 ± 15.72 80.39 ± 10.51 0.254b
T171 17160-17220 Sentence denotes   Respiration rate (bpm) 25.20 ± 7.29 19.86 ± 1.90 < 0.001b*
T172 17221-17278 Sentence denotes   Heart rate (bpm) 101.59 ± 20.36 86.06 ± 13.34 < 0.001b*
T173 17279-17331 Sentence denotes   Temperature (°C) 37.61 ± 1.06 37.12 ± 0.83 0.003b*
T174 17332-17337 Sentence denotes Signs
T175 17338-17382 Sentence denotes   Dry cough# 56 (84.85%) 48 (68.57%) 0.025a*
T176 17383-17424 Sentence denotes   Fatigue# 8 (12.12%) 22 (31.43%) 0.007a*
T177 17425-17467 Sentence denotes   Sore throat# 6 (9.09%) 9 (12.86%) 0.483a
T178 17468-17504 Sentence denotes   Stuffy# 4 (6.06%) 2 (2.86%) 0.623a
T179 17505-17545 Sentence denotes   Runny nose# 3 (4.55%) 3 (4.29%) 0.731a
T180 17546-17613 Sentence denotes White blood cell count (× 109/L) 11.48 ± 5.36 5.27 ± 2.33 < 0.001b*
T181 17614-17655 Sentence denotes White blood cell count category < 0.001c*
T182 17656-17682 Sentence denotes   Low# 0 (0.00%) 2 (2.86%)
T183 17683-17716 Sentence denotes   Normal# 27 (40.91%) 63 (90.00%)
T184 17717-17746 Sentence denotes   High# 39 (59.09%) 5 (7.14%)
T185 17747-17804 Sentence denotes Lymphocyte count (× 109/L) 1.57 ± 1.33 1.25 ± 0.68 0.086b
T186 17805-17840 Sentence denotes Lymphocyte count category < 0.001c*
T187 17841-17871 Sentence denotes   Low# 24 (36.36%) 32 (45.71%)
T188 17872-17905 Sentence denotes   Normal# 35 (53.03%) 37 (52.86%)
T189 17906-17934 Sentence denotes   High# 7 (10.61%) 1 (1.43%)
T190 17935-17995 Sentence denotes Neutrophil count (× 109/L) 8.97 ± 4.90 3.53 ± 2.17 < 0.001b*
T191 17996-18031 Sentence denotes Neutrophil count category < 0.001c*
T192 18032-18059 Sentence denotes   Low# 3 (4.55%) 8 (11.43%)
T193 18060-18093 Sentence denotes   Normal# 23 (34.85%) 59 (84.29%)
T194 18094-18123 Sentence denotes   High# 40 (60.61%) 3 (4.29%)
T195 18124-18187 Sentence denotes C-reactive protein (mg/L) 69.30 ± 65.88 26.37 ± 30.97 < 0.001b*
T196 18188-18241 Sentence denotes Procalcitonin (ng/mL) 3.36 ± 8.98 0.26 ± 0.84 0.007b*
T197 18242-18303 Sentence denotes *Data with statistical significance. pa: chi-square test, pb:
T198 18304-18325 Sentence denotes Student’s t test. pc:
T199 18326-18347 Sentence denotes Kruskal-Wallis H test
T200 18348-18413 Sentence denotes #Results are measurements with corresponding ratio in parentheses
T201 18414-18504 Sentence denotes For imaging manifestations, 7 patients in the COVID-19 group showed normal chest CT (10%).
T202 18505-18638 Sentence denotes COVID-19 patients have a greater number of pure GGO and mixed GGO than non-COVID-19 patients (p = 0.018 and p = 0.001, respectively).
T203 18639-18757 Sentence denotes For pure GGO lesions, the differences are significant both in peripheral (p = 0.032) and in central areas (p = 0.001).
T204 18758-18915 Sentence denotes However, the number of mixed GGO is mainly distributed at the periphery in COVID-19 patients (p < 0.001), with no statistical difference in the central area.
T205 18916-19001 Sentence denotes The consolidation lesions without GGO occurred less in COVID-19 patients (p = 0.001).
T206 19002-19143 Sentence denotes More lesions are between 1 and 3 cm (p = 0.027), and fewer lesions are larger than half of the lung segment (p = 0.017) in COVID-19 patients.
T207 19144-19502 Sentence denotes Other significant differences between the two groups include the pleural traction sign (p = 0.019), bronchial wall thickening (p < 0.001), interlobular septal thickening (p = 0.009), crazy paving (p < 0.001), tree-in-bud (p < 0.001), pleural effusions (p < 0.001), pleural thickening (p = 0.030), and the offending vessel augmentation in lesions (p < 0.001).
T208 19503-19598 Sentence denotes The lung score presents no significant difference between the COVID-19 and non-COVID-19 groups.
T209 19599-19715 Sentence denotes Comparison of clinical features between the two groups of patients with and without COVID-19 is reported in Table 2.
T210 19716-19789 Sentence denotes There is no significant difference in age and sex between the two groups.
T211 19790-19935 Sentence denotes Significant differences are found in common symptoms between groups, including fever (p = 0.003), dry cough (p = 0.025), and fatigue (p = 0.007).
T212 19936-20046 Sentence denotes The respiration rate and heart rate also show significant differences between the two groups (both p < 0.001).
T213 20047-20168 Sentence denotes Compared with non-COVID-19 pneumonia, the reduction of the WBC count is more pronounced in COVID-19 patients (p < 0.001).
T214 20169-20293 Sentence denotes The ratio of lymphocyte and ratio of neutrophil also show a significant difference between COVID-19 and non-COVID-19 groups.
T215 20294-20441 Sentence denotes Although lymphopenia was observed in 32 COVID-19 patients (45.71%), it is not statistically different compared with that in the non-COVID-19 group.
T216 20442-20593 Sentence denotes C-creative protein (CRP) level and procalcitonin level are also significantly different between the two groups (p < 0.001 and p = 0.007, respectively).
T217 20594-20661 Sentence denotes Most COVID-19 patients present normal procalcitonin level (82.86%).
T218 20663-20706 Sentence denotes Clinical and radiological feature selection
T219 20707-20851 Sentence denotes Of the features, 18 radiological features and 17 clinical features were selected to form the predictors based on the result from Tables 1 and 2.
T220 20852-20921 Sentence denotes Table 3 lists the features selected by univariate analysis and LASSO.
T221 20922-20970 Sentence denotes Table 3 Selected features in C, R, and CR models
T222 20971-21013 Sentence denotes Model and individual features Coefficients
T223 21014-21028 Sentence denotes R, n = 8 (41)*
T224 21029-21048 Sentence denotes   Intercept − 0.307
T225 21049-21101 Sentence denotes   Total number of mixed GGO in peripheral area 0.359
T226 21102-21141 Sentence denotes   Total number of consolidation − 1.262
T227 21142-21207 Sentence denotes   Total number of solid nodules with ground-glass opacities 0.452
T228 21208-21248 Sentence denotes   Interlobular septal thickening − 5.559
T229 21249-21277 Sentence denotes   Crazy paving pattern 3.566
T230 21278-21299 Sentence denotes   Tree-in-bud − 2.548
T231 21300-21326 Sentence denotes   Pleural thickening 3.265
T232 21327-21375 Sentence denotes   Offending vessel augmentation in lesions 5.504
T233 21376-21390 Sentence denotes C, n = 7 (26)*
T234 21391-21409 Sentence denotes   Intercept 29.273
T235 21410-21431 Sentence denotes   Respiration − 0.359
T236 21432-21452 Sentence denotes   Heart rate − 0.054
T237 21453-21474 Sentence denotes   Temperature − 0.289
T238 21475-21507 Sentence denotes   White blood cell count − 0.175
T239 21508-21523 Sentence denotes   Cough − 1.866
T240 21524-21539 Sentence denotes   Fatigue 2.855
T241 21540-21575 Sentence denotes   Lymphocyte count category − 0.028
T242 21576-21592 Sentence denotes CR, n = 10 (67)*
T243 21593-21611 Sentence denotes   Intercept 45.117
T244 21612-21664 Sentence denotes   Total number of mixed GGO in peripheral area 0.108
T245 21665-21686 Sentence denotes   Tree-in-bud − 1.853
T246 21687-21735 Sentence denotes   Offending vessel augmentation in lesions 6.000
T247 21736-21757 Sentence denotes   Respiration − 0.583
T248 21758-21779 Sentence denotes   Heart ratio − 0.084
T249 21780-21801 Sentence denotes   Temperature − 0.536
T250 21802-21834 Sentence denotes   White blood cell count − 0.471
T251 21835-21850 Sentence denotes   Cough − 0.997
T252 21851-21868 Sentence denotes   Fatigue − 0.228
T253 21869-21904 Sentence denotes   Lymphocyte count category − 2.177
T254 21905-22087 Sentence denotes C, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively
T255 22088-22173 Sentence denotes *n means corresponding selected features, and data in parentheses are total features.
T256 22174-22286 Sentence denotes Coefficients: the estimate value of each feature in multivariate logistic regression model by “glm” package in R
T257 22288-22320 Sentence denotes Model development and validation
T258 22321-22522 Sentence denotes The prediction models based on (i) clinical features (C model), (ii) radiological features (R model), and (iii) the combination of clinical features and radiological features (CR model) were developed.
T259 22523-22606 Sentence denotes ROC analyses for the primary and validation cohort are shown in Table 4 and Fig. 3.
T260 22607-22799 Sentence denotes The CR model yielded a maximum AUC of 0.986 (95% CI 0.966~1.000) in the primary cohort with the highest accuracy and specificity, which was 0.936 (95% CI 0.866~1.000) in the validation cohort.
T261 22800-22938 Sentence denotes The AUC for the C model was 0.952 (95% CI 0.988~0.915) and 0.967 (95% CI 0.919~1.000) in the primary and validation cohorts, respectively.
T262 22939-23059 Sentence denotes For the R model, the AUC of the two cohorts was 0.969 (95% CI 0.940~0.997) and 0.809 (95% CI 0.669~0.948), respectively.
T263 23060-23119 Sentence denotes Table 4 Performance of the individualized prediction models
T264 23120-23170 Sentence denotes Primary cohort (n = 98) Validation cohort (n = 38)
T265 23171-23265 Sentence denotes Models AUC 95% CI Accuracy Specificity Sensitivity AUC 95% CI Accuracy Specificity Sensitivity
T266 23266-23345 Sentence denotes C model 0.952 0.915~0.988 0.888 0.894 0.882 0.967 0.919~1.000 0.868 0.859 0.842
T267 23346-23425 Sentence denotes R model 0.969 0.940~0.997 0.929 0.851 1.000 0.809 0.669~0.948 0.684 0.368 1.000
T268 23426-23506 Sentence denotes CR model 0.986 0.966~1.000 0.959 0.957 0.961 0.936 0.866~1.000 0.763 0.789 0.737
T269 23507-23690 Sentence denotes C, R, and CR indicate the predicted model based on clinical features, radiological features, and the combination of clinical features and clinical radiological features, respectively.
T270 23691-23713 Sentence denotes CI confidence interval
T271 23714-23785 Sentence denotes Fig. 3 ROC of the three models in primary and validation cohort curves.
T272 23786-24053 Sentence denotes Comparison of receiver operating characteristic (ROC) curves among the radiological mode (R model), clinical model (C model), and the combination of clinical and radiological model (CR model) for the diagnosis of COVID-19 in the primary (a) and validation (b) cohorts
T273 24054-24259 Sentence denotes To determine the clinical usefulness of the diagnostic model, we developed the decision curve (Fig. 4), which showed better performances for the CR model compared with that for the C model and the R model.
T274 24260-24443 Sentence denotes Across the majority of the range of reasonable threshold probabilities, the decision curve analysis showed that the CR model had a higher overall benefit than the C model and R model.
T275 24444-24513 Sentence denotes Fig. 4 Decision curve analysis for each model in the primary dataset.
T276 24514-24808 Sentence denotes The y-axis measures the net benefit, which is calculated by summing the benefits (true-positive findings) and subtracting the harms (false-positive findings), weighting the latter by a factor related to the relative harm of undetected metastasis compared with the harm of unnecessary treatment.
T277 24809-25067 Sentence denotes The decision curve shows that if the threshold probability is over 10%, the application of the combination of clinical and radiological model (CR model) to diagnose COVID-19 adds more benefit than the clinical model (C model) and radiological model (R model)
T278 25068-25415 Sentence denotes The nomogram (Fig. 5) was developed by the CR model in the primary cohort, with the factors of the total number of mixed GGO in peripheral area (TN_Mixed_GGO_IP), tree-in-bud, offending vessel augmentation in lesions (OVAIL), respiration, heart ratio, temperature, white blood cell count, cough, fatigue and lymphocyte count category incorporated.
T279 25416-25520 Sentence denotes The total points were calculated by summing the points identified on the “points” scale for each factor.
T280 25521-25655 Sentence denotes By comparing the “total points” scale and the “probability” scale, the individual probability of COVID-19 infection could be obtained.
T281 25656-25710 Sentence denotes Fig. 5 Nomogram of the CR model in the primary cohort.
T282 25711-25788 Sentence denotes TN_Mixed_GGO_IP represented the total number of mixed GGO in peripheral area.
T283 25789-25848 Sentence denotes AVAIL represented offending vessel segmentation in lesions.
T284 25849-25902 Sentence denotes N was a negative result, and P was a positive result.
T285 25903-25927 Sentence denotes Norm represented normal.
T286 25928-25990 Sentence denotes Note that in probability scale, 0 = non-COVID-19, 1 = COVID-19
T287 25992-26002 Sentence denotes Discussion
T288 26003-26168 Sentence denotes In this multi-center study, statistical analysis was performed in comparing imaging and clinical manifestations between pneumonia patients with and without COVID-19.
T289 26169-26321 Sentence denotes Eighteen radiological semantic features and seventeen clinical features were identified to be significantly different between the two groups (p < 0.05).
T290 26322-26403 Sentence denotes Three models for COVID-19 diagnosis were developed based on the refined features.
T291 26404-26510 Sentence denotes The models were validated in the both primary and validation cohorts and achieved an AUC as high as 0.986.
T292 26511-26702 Sentence denotes These models will play an essential role for early and easy-to-access diagnosis, especially when there are not enough RT-PCT kits or experimental platforms to test for the COVID-19 infection.
T293 26703-26804 Sentence denotes A total of 1745 lesions were evaluated for the qualitative feature, location, and size in this study.
T294 26805-26998 Sentence denotes Consistent with the previous studies, the ground-glass opacities and consolidation in the lung periphery were considered to be the imaging hallmark in patients with COVID-19 infection [11, 25].
T295 26999-27142 Sentence denotes However, when we subdivided the GGO into pure GGO and mixed GGO, we found that the distribution pattern is different between these two lesions.
T296 27143-27305 Sentence denotes Pure GGO show differences between groups in every location of the lungs, whereas mixed GGO only have significant differences between groups in the lung periphery.
T297 27306-27378 Sentence denotes Recent studies defined four stages of lung involvement in COVID-19 [26].
T298 27379-27455 Sentence denotes Therefore, a follow-up analysis of these distributions would be significant.
T299 27456-27544 Sentence denotes The lesion size in patients with COVID-19 infection was another interesting observation.
T300 27545-27688 Sentence denotes Most lesions were between 1 and 3 cm, with few lesions larger than half of the lung segment, which was similar to the finding in MERS_CoV [22].
T301 27689-27873 Sentence denotes Other features similar to MERS_CoV and SARS_CoV were observed in the laboratory abnormalities, such as lymphopenia, which may be associated with the cellular immune deficiency [3, 27].
T302 27874-27990 Sentence denotes However, our results showed no significant difference in lymphopenia between the COVID-19 and non-COVID-19 patients.
T303 27991-28122 Sentence denotes To our knowledge, no diagnostic model based on imaging and clinical features alone has been proposed for the diagnosis of COVID-19.
T304 28123-28428 Sentence denotes Our clinical and radiological semantic (CR) models consisted of the following features: total number of GGO with consolidation in the peripheral area, tree-in-bud, offending vessel augmentation in lesions, temperature, heart ratio, respiration, cough and fatigue, WBC count, and lymphocyte count category.
T305 28429-28500 Sentence denotes The CR model outperformed the individual clinical and radiologic model.
T306 28501-28700 Sentence denotes This result was in accordance with that in previous study in breast cancer, in which the model based on the combination of radiomics features and clinical features achieved a higher performance [24].
T307 28701-28894 Sentence denotes Compared with the radiomics-based model, the extraction of radiological semantic features can overcome the image discrepancy caused by different scanning parameters and/or different CT vendors.
T308 28895-29091 Sentence denotes A previous study [28] also indicated that models based on semantic features determined by an experienced thoracic radiologist slightly outperformed models based on computed texture features alone.
T309 29092-29134 Sentence denotes There are a few limitations in this study.
T310 29135-29293 Sentence denotes First, the sample size is relatively small because this is a retrospective analysis of a new disease and most of the cases outside of Wuhan City are imported.
T311 29294-29611 Sentence denotes Second, with the multi-center retrospective design, there is a potential bias of patient selection [29], since there may be some deviations in marking semantic features among readers, though we have taken the effort to reduce this by creating pictorial examples and setting feature criteria (Supplementary Materials).
T312 29612-29659 Sentence denotes Third, longitudinal CT study was not performed.
T313 29660-29799 Sentence denotes Whether or not this model can be used to evaluate the follow-ups and help to guide therapy remains an open question to be further explored.
T314 29800-29983 Sentence denotes Moreover, the rich high-order features of the CT image combined with radiomics or deep learning have not been studied, which may be another way to identify the patients with COVID-19.
T315 29984-30119 Sentence denotes Besides, one can also focus on the role of radiological features in disease monitoring, treatment evaluation, and prognosis prediction.
T316 30120-30231 Sentence denotes In conclusion, 1745 lesions and 67 features were compared between pneumonia patients with and without COVID-19.
T317 30232-30305 Sentence denotes Thirty-five features were significantly different between the two groups.
T318 30306-30476 Sentence denotes A diagnostic model with AUC as high as 0.986 was developed and validated both in the primary and in the validation cohorts, which may help improve the COVID-19 diagnosis.
T319 30478-30511 Sentence denotes Electronic supplementary material
T320 30513-30532 Sentence denotes ESM 1 (DOCX 404 kb)
T321 30534-30550 Sentence denotes Publisher’s note
T322 30551-30669 Sentence denotes Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
T323 30670-30733 Sentence denotes Xiaofeng Chen and Yanyan Tang contributed equally to this work.
T324 30735-30754 Sentence denotes Funding information
T325 30755-31116 Sentence denotes This study has received funding by the Natural Science Foundation of China (grant numbers 81471730, 31870981) to R.W.; the Natural Science Foundation of Guangdong Province (grant number 2018A030307057) to Z.D.; and the Special Project on Prevention and Control of COVID-19 for Colleges and Universities in Guangdong Province (grant number 2020KZDZX1085) to Z.D.
T326 31118-31151 Sentence denotes Compliance with ethical standards
T327 31153-31162 Sentence denotes Guarantor
T328 31163-31223 Sentence denotes The scientific guarantor of this publication is Zhuozhi Dai.
T329 31225-31245 Sentence denotes Conflict of interest
T330 31246-31330 Sentence denotes One of the authors of this manuscript (Yuting Liao) is an employee of GE Healthcare.
T331 31331-31476 Sentence denotes The remaining authors declare no relationships with any companies whose products or services may be related to the subject matter of the article.
T332 31478-31501 Sentence denotes Statistics and biometry
T333 31502-31577 Sentence denotes One of the authors, Dr. Yuting Liao, has significant statistical expertise.
T334 31579-31595 Sentence denotes Informed consent
T335 31596-31666 Sentence denotes Written informed consent was waived by the Institutional Review Board.
T336 31668-31684 Sentence denotes Ethical approval
T337 31685-31734 Sentence denotes Institutional Review Board approval was obtained.
T338 31736-31747 Sentence denotes Methodology
T339 31748-31763 Sentence denotes • retrospective
T340 31764-31784 Sentence denotes • case-control study
T341 31785-31805 Sentence denotes • multi-center study

MyTest

Id Subject Object Predicate Lexical cue
32300971-29948074-29373584 6610-6612 29948074 denotes 19
32300971-30093881-29373584 6610-6612 30093881 denotes 19
32300971-30546304-29373584 6610-6612 30546304 denotes 19
32300971-26037317-29373585 10819-10821 26037317 denotes 23
32300971-30842125-29373586 11966-11968 30842125 denotes 24
32300971-30842125-29373587 28696-28698 30842125 denotes 24
32300971-31115618-29373588 28913-28915 31115618 denotes 28
32300971-16505391-29373589 29394-29396 16505391 denotes 29