PMC:7301188 / 6180-8813 JSON TXT

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LitCovid-PMC-OGER-BB

{"project":"LitCovid-PMC-OGER-BB","denotations":[{"id":"T40","span":{"begin":84,"end":92},"obj":"SP_7"},{"id":"T41","span":{"begin":603,"end":606},"obj":"PR:Q8VYM2"},{"id":"T42","span":{"begin":943,"end":951},"obj":"SP_7"},{"id":"T43","span":{"begin":1182,"end":1186},"obj":"GO:0016265"},{"id":"T44","span":{"begin":1543,"end":1551},"obj":"SP_7"},{"id":"T45","span":{"begin":1990,"end":1998},"obj":"SP_7"},{"id":"T46","span":{"begin":2340,"end":2351},"obj":"GO:0050817"},{"id":"T47","span":{"begin":2484,"end":2489},"obj":"UBERON:0001443"},{"id":"T48","span":{"begin":2572,"end":2581},"obj":"UBERON:0002048"},{"id":"T43606","span":{"begin":84,"end":92},"obj":"SP_7"},{"id":"T48867","span":{"begin":603,"end":606},"obj":"PR:Q8VYM2"},{"id":"T64409","span":{"begin":943,"end":951},"obj":"SP_7"},{"id":"T25291","span":{"begin":1182,"end":1186},"obj":"GO:0016265"},{"id":"T67512","span":{"begin":1543,"end":1551},"obj":"SP_7"},{"id":"T27565","span":{"begin":1990,"end":1998},"obj":"SP_7"},{"id":"T28750","span":{"begin":2340,"end":2351},"obj":"GO:0050817"},{"id":"T64018","span":{"begin":2484,"end":2489},"obj":"UBERON:0001443"},{"id":"T32263","span":{"begin":2572,"end":2581},"obj":"UBERON:0002048"}],"text":"3. Results and Discussion\n\n3.1. Demographic Characteristics\nAmong 115 patients with COVID-19, the median ages were 63.55 ± 13.86 (27-96) years old, male were 66 (57.4%) cases, female were 49 (42.6%) cases, and over 60 years old were 78 (67.8%) cases. At the time of admission, mild and ordinary patients were 39 (33.9%) cases, severe patients were 48 (41.7%) cases, and critical patients were 28 (24.3%) cases (Table 1). In this study, more patients were male and more patients were more than 60 years, consistently with previous literature report [1].\n\n3.2. The Relationship between the Levels of DD1, PT1, APTT1, Fg1, and Clinical Classification\nThere are significant differences in DD1 between different clinical classifications (P \u003c 0.05). The severity of the disease increased as DD1 increased. 81 (70.4%) patients had Fg1 increased (Table 2).\n\n3.3. Relationship between the Dynamics Changes of DD, PT, APTT, TT, Fg, and the Prognosis of COVID-19\nSignificant difference (P \u003c 0.05) and positive correlation were found between DD, PT, and outcomes at composite endpoints. Correlation in third detection was stronger than that in first and second detection.\nAmong 23 patients who died, 18 (78.3%) cases had DD1 increased, 12 of 18 had DD1 two times higher (\u003e1.10 mg/L), 22 cases had DD2 and DD3 increased, 21 of 22 had DD2 and DD3 two times higher (\u003e1.10 mg/L). Eight cases in exacerbated patients occurred increased DD2 and DD3 all higher (1.10 mg/L) (Table 3).\n\n3.4. Analysis of DD and PT in Predicting Hospital Discharge and Mortality of COVID-19\nWe used the ROC curve analysis to evaluate the diagnostic value of hospital discharge and mortality in 115 patients. The AUCs of DD1, DD2, and DD3 to predict hospital discharge and mortality were 0.742, 0.818, and 0.851, respectively (Figure 1(a)). The AUCs of PT1, PT2, and PT3 to predict hospital discharge and mortality were 0.643, 0.824, and 0.937, respectively (Figure 1(b)).\n\n3.5. Dynamic Changes of Chest CT Imaging, DD and CTA in COVID-19 Patients\nAt the early stage of the disease, the correlation between CT imaging changes and DD value was not obvious; however, with the progression of the disease, the change of CT was closely related to the increase of DD value, and there was a significant statistical difference (Table 4).\nThe clinical observation showed that the abnormal coagulation factor was consistent with the CT imaging results. In this paper, a typical patient was taken as an example. The dynamic changes of chest CT imaging and DD were consistent (Figure 2(a)). Increased DD was associated with pulmonary embolism, which was confirmed by CTA (Figure 2(b))."}

LitCovid-PD-FMA-UBERON

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T6","span":{"begin":1958,"end":1963},"obj":"Body_part"},{"id":"T7","span":{"begin":2484,"end":2489},"obj":"Body_part"}],"attributes":[{"id":"A6","pred":"fma_id","subj":"T6","obj":"http://purl.org/sig/ont/fma/fma9576"},{"id":"A7","pred":"fma_id","subj":"T7","obj":"http://purl.org/sig/ont/fma/fma9576"}],"text":"3. Results and Discussion\n\n3.1. Demographic Characteristics\nAmong 115 patients with COVID-19, the median ages were 63.55 ± 13.86 (27-96) years old, male were 66 (57.4%) cases, female were 49 (42.6%) cases, and over 60 years old were 78 (67.8%) cases. At the time of admission, mild and ordinary patients were 39 (33.9%) cases, severe patients were 48 (41.7%) cases, and critical patients were 28 (24.3%) cases (Table 1). In this study, more patients were male and more patients were more than 60 years, consistently with previous literature report [1].\n\n3.2. The Relationship between the Levels of DD1, PT1, APTT1, Fg1, and Clinical Classification\nThere are significant differences in DD1 between different clinical classifications (P \u003c 0.05). The severity of the disease increased as DD1 increased. 81 (70.4%) patients had Fg1 increased (Table 2).\n\n3.3. Relationship between the Dynamics Changes of DD, PT, APTT, TT, Fg, and the Prognosis of COVID-19\nSignificant difference (P \u003c 0.05) and positive correlation were found between DD, PT, and outcomes at composite endpoints. Correlation in third detection was stronger than that in first and second detection.\nAmong 23 patients who died, 18 (78.3%) cases had DD1 increased, 12 of 18 had DD1 two times higher (\u003e1.10 mg/L), 22 cases had DD2 and DD3 increased, 21 of 22 had DD2 and DD3 two times higher (\u003e1.10 mg/L). Eight cases in exacerbated patients occurred increased DD2 and DD3 all higher (1.10 mg/L) (Table 3).\n\n3.4. Analysis of DD and PT in Predicting Hospital Discharge and Mortality of COVID-19\nWe used the ROC curve analysis to evaluate the diagnostic value of hospital discharge and mortality in 115 patients. The AUCs of DD1, DD2, and DD3 to predict hospital discharge and mortality were 0.742, 0.818, and 0.851, respectively (Figure 1(a)). The AUCs of PT1, PT2, and PT3 to predict hospital discharge and mortality were 0.643, 0.824, and 0.937, respectively (Figure 1(b)).\n\n3.5. Dynamic Changes of Chest CT Imaging, DD and CTA in COVID-19 Patients\nAt the early stage of the disease, the correlation between CT imaging changes and DD value was not obvious; however, with the progression of the disease, the change of CT was closely related to the increase of DD value, and there was a significant statistical difference (Table 4).\nThe clinical observation showed that the abnormal coagulation factor was consistent with the CT imaging results. In this paper, a typical patient was taken as an example. The dynamic changes of chest CT imaging and DD were consistent (Figure 2(a)). Increased DD was associated with pulmonary embolism, which was confirmed by CTA (Figure 2(b))."}

LitCovid-PD-UBERON

{"project":"LitCovid-PD-UBERON","denotations":[{"id":"T5","span":{"begin":1958,"end":1963},"obj":"Body_part"},{"id":"T6","span":{"begin":2484,"end":2489},"obj":"Body_part"}],"attributes":[{"id":"A5","pred":"uberon_id","subj":"T5","obj":"http://purl.obolibrary.org/obo/UBERON_0001443"},{"id":"A6","pred":"uberon_id","subj":"T6","obj":"http://purl.obolibrary.org/obo/UBERON_0001443"}],"text":"3. Results and Discussion\n\n3.1. Demographic Characteristics\nAmong 115 patients with COVID-19, the median ages were 63.55 ± 13.86 (27-96) years old, male were 66 (57.4%) cases, female were 49 (42.6%) cases, and over 60 years old were 78 (67.8%) cases. At the time of admission, mild and ordinary patients were 39 (33.9%) cases, severe patients were 48 (41.7%) cases, and critical patients were 28 (24.3%) cases (Table 1). In this study, more patients were male and more patients were more than 60 years, consistently with previous literature report [1].\n\n3.2. The Relationship between the Levels of DD1, PT1, APTT1, Fg1, and Clinical Classification\nThere are significant differences in DD1 between different clinical classifications (P \u003c 0.05). The severity of the disease increased as DD1 increased. 81 (70.4%) patients had Fg1 increased (Table 2).\n\n3.3. Relationship between the Dynamics Changes of DD, PT, APTT, TT, Fg, and the Prognosis of COVID-19\nSignificant difference (P \u003c 0.05) and positive correlation were found between DD, PT, and outcomes at composite endpoints. Correlation in third detection was stronger than that in first and second detection.\nAmong 23 patients who died, 18 (78.3%) cases had DD1 increased, 12 of 18 had DD1 two times higher (\u003e1.10 mg/L), 22 cases had DD2 and DD3 increased, 21 of 22 had DD2 and DD3 two times higher (\u003e1.10 mg/L). Eight cases in exacerbated patients occurred increased DD2 and DD3 all higher (1.10 mg/L) (Table 3).\n\n3.4. Analysis of DD and PT in Predicting Hospital Discharge and Mortality of COVID-19\nWe used the ROC curve analysis to evaluate the diagnostic value of hospital discharge and mortality in 115 patients. The AUCs of DD1, DD2, and DD3 to predict hospital discharge and mortality were 0.742, 0.818, and 0.851, respectively (Figure 1(a)). The AUCs of PT1, PT2, and PT3 to predict hospital discharge and mortality were 0.643, 0.824, and 0.937, respectively (Figure 1(b)).\n\n3.5. Dynamic Changes of Chest CT Imaging, DD and CTA in COVID-19 Patients\nAt the early stage of the disease, the correlation between CT imaging changes and DD value was not obvious; however, with the progression of the disease, the change of CT was closely related to the increase of DD value, and there was a significant statistical difference (Table 4).\nThe clinical observation showed that the abnormal coagulation factor was consistent with the CT imaging results. In this paper, a typical patient was taken as an example. The dynamic changes of chest CT imaging and DD were consistent (Figure 2(a)). Increased DD was associated with pulmonary embolism, which was confirmed by CTA (Figure 2(b))."}

LitCovid-PubTator

LitCovid-PD-MONDO

LitCovid-PD-CLO

LitCovid-PD-CHEBI

LitCovid-PD-GO-BP

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T7","span":{"begin":2340,"end":2351},"obj":"http://purl.obolibrary.org/obo/GO_0050817"}],"text":"3. Results and Discussion\n\n3.1. Demographic Characteristics\nAmong 115 patients with COVID-19, the median ages were 63.55 ± 13.86 (27-96) years old, male were 66 (57.4%) cases, female were 49 (42.6%) cases, and over 60 years old were 78 (67.8%) cases. At the time of admission, mild and ordinary patients were 39 (33.9%) cases, severe patients were 48 (41.7%) cases, and critical patients were 28 (24.3%) cases (Table 1). In this study, more patients were male and more patients were more than 60 years, consistently with previous literature report [1].\n\n3.2. The Relationship between the Levels of DD1, PT1, APTT1, Fg1, and Clinical Classification\nThere are significant differences in DD1 between different clinical classifications (P \u003c 0.05). The severity of the disease increased as DD1 increased. 81 (70.4%) patients had Fg1 increased (Table 2).\n\n3.3. Relationship between the Dynamics Changes of DD, PT, APTT, TT, Fg, and the Prognosis of COVID-19\nSignificant difference (P \u003c 0.05) and positive correlation were found between DD, PT, and outcomes at composite endpoints. Correlation in third detection was stronger than that in first and second detection.\nAmong 23 patients who died, 18 (78.3%) cases had DD1 increased, 12 of 18 had DD1 two times higher (\u003e1.10 mg/L), 22 cases had DD2 and DD3 increased, 21 of 22 had DD2 and DD3 two times higher (\u003e1.10 mg/L). Eight cases in exacerbated patients occurred increased DD2 and DD3 all higher (1.10 mg/L) (Table 3).\n\n3.4. Analysis of DD and PT in Predicting Hospital Discharge and Mortality of COVID-19\nWe used the ROC curve analysis to evaluate the diagnostic value of hospital discharge and mortality in 115 patients. The AUCs of DD1, DD2, and DD3 to predict hospital discharge and mortality were 0.742, 0.818, and 0.851, respectively (Figure 1(a)). The AUCs of PT1, PT2, and PT3 to predict hospital discharge and mortality were 0.643, 0.824, and 0.937, respectively (Figure 1(b)).\n\n3.5. Dynamic Changes of Chest CT Imaging, DD and CTA in COVID-19 Patients\nAt the early stage of the disease, the correlation between CT imaging changes and DD value was not obvious; however, with the progression of the disease, the change of CT was closely related to the increase of DD value, and there was a significant statistical difference (Table 4).\nThe clinical observation showed that the abnormal coagulation factor was consistent with the CT imaging results. In this paper, a typical patient was taken as an example. The dynamic changes of chest CT imaging and DD were consistent (Figure 2(a)). Increased DD was associated with pulmonary embolism, which was confirmed by CTA (Figure 2(b))."}

LitCovid-PD-GlycoEpitope

{"project":"LitCovid-PD-GlycoEpitope","denotations":[{"id":"T2","span":{"begin":598,"end":601},"obj":"GlycoEpitope"},{"id":"T3","span":{"begin":685,"end":688},"obj":"GlycoEpitope"},{"id":"T4","span":{"begin":785,"end":788},"obj":"GlycoEpitope"},{"id":"T5","span":{"begin":1209,"end":1212},"obj":"GlycoEpitope"},{"id":"T6","span":{"begin":1237,"end":1240},"obj":"GlycoEpitope"},{"id":"T7","span":{"begin":1285,"end":1288},"obj":"GlycoEpitope"},{"id":"T8","span":{"begin":1321,"end":1324},"obj":"GlycoEpitope"},{"id":"T9","span":{"begin":1419,"end":1422},"obj":"GlycoEpitope"},{"id":"T10","span":{"begin":1681,"end":1684},"obj":"GlycoEpitope"},{"id":"T11","span":{"begin":1686,"end":1689},"obj":"GlycoEpitope"}],"attributes":[{"id":"A6","pred":"glyco_epitope_db_id","subj":"T6","obj":"http://www.glycoepitope.jp/epitopes/AN0523"},{"id":"A8","pred":"glyco_epitope_db_id","subj":"T8","obj":"http://www.glycoepitope.jp/epitopes/AN0524"},{"id":"A2","pred":"glyco_epitope_db_id","subj":"T2","obj":"http://www.glycoepitope.jp/epitopes/AN0523"},{"id":"A5","pred":"glyco_epitope_db_id","subj":"T5","obj":"http://www.glycoepitope.jp/epitopes/AN0523"},{"id":"A9","pred":"glyco_epitope_db_id","subj":"T9","obj":"http://www.glycoepitope.jp/epitopes/AN0524"},{"id":"A7","pred":"glyco_epitope_db_id","subj":"T7","obj":"http://www.glycoepitope.jp/epitopes/AN0524"},{"id":"A10","pred":"glyco_epitope_db_id","subj":"T10","obj":"http://www.glycoepitope.jp/epitopes/AN0523"},{"id":"A11","pred":"glyco_epitope_db_id","subj":"T11","obj":"http://www.glycoepitope.jp/epitopes/AN0524"},{"id":"A3","pred":"glyco_epitope_db_id","subj":"T3","obj":"http://www.glycoepitope.jp/epitopes/AN0523"},{"id":"A4","pred":"glyco_epitope_db_id","subj":"T4","obj":"http://www.glycoepitope.jp/epitopes/AN0523"}],"text":"3. Results and Discussion\n\n3.1. Demographic Characteristics\nAmong 115 patients with COVID-19, the median ages were 63.55 ± 13.86 (27-96) years old, male were 66 (57.4%) cases, female were 49 (42.6%) cases, and over 60 years old were 78 (67.8%) cases. At the time of admission, mild and ordinary patients were 39 (33.9%) cases, severe patients were 48 (41.7%) cases, and critical patients were 28 (24.3%) cases (Table 1). In this study, more patients were male and more patients were more than 60 years, consistently with previous literature report [1].\n\n3.2. The Relationship between the Levels of DD1, PT1, APTT1, Fg1, and Clinical Classification\nThere are significant differences in DD1 between different clinical classifications (P \u003c 0.05). The severity of the disease increased as DD1 increased. 81 (70.4%) patients had Fg1 increased (Table 2).\n\n3.3. Relationship between the Dynamics Changes of DD, PT, APTT, TT, Fg, and the Prognosis of COVID-19\nSignificant difference (P \u003c 0.05) and positive correlation were found between DD, PT, and outcomes at composite endpoints. Correlation in third detection was stronger than that in first and second detection.\nAmong 23 patients who died, 18 (78.3%) cases had DD1 increased, 12 of 18 had DD1 two times higher (\u003e1.10 mg/L), 22 cases had DD2 and DD3 increased, 21 of 22 had DD2 and DD3 two times higher (\u003e1.10 mg/L). Eight cases in exacerbated patients occurred increased DD2 and DD3 all higher (1.10 mg/L) (Table 3).\n\n3.4. Analysis of DD and PT in Predicting Hospital Discharge and Mortality of COVID-19\nWe used the ROC curve analysis to evaluate the diagnostic value of hospital discharge and mortality in 115 patients. The AUCs of DD1, DD2, and DD3 to predict hospital discharge and mortality were 0.742, 0.818, and 0.851, respectively (Figure 1(a)). The AUCs of PT1, PT2, and PT3 to predict hospital discharge and mortality were 0.643, 0.824, and 0.937, respectively (Figure 1(b)).\n\n3.5. Dynamic Changes of Chest CT Imaging, DD and CTA in COVID-19 Patients\nAt the early stage of the disease, the correlation between CT imaging changes and DD value was not obvious; however, with the progression of the disease, the change of CT was closely related to the increase of DD value, and there was a significant statistical difference (Table 4).\nThe clinical observation showed that the abnormal coagulation factor was consistent with the CT imaging results. In this paper, a typical patient was taken as an example. The dynamic changes of chest CT imaging and DD were consistent (Figure 2(a)). Increased DD was associated with pulmonary embolism, which was confirmed by CTA (Figure 2(b))."}

LitCovid-sentences

LitCovid-PD-HP

{"project":"LitCovid-PD-HP","denotations":[{"id":"T9","span":{"begin":2331,"end":2351},"obj":"Phenotype"},{"id":"T10","span":{"begin":2572,"end":2590},"obj":"Phenotype"}],"attributes":[{"id":"A9","pred":"hp_id","subj":"T9","obj":"http://purl.obolibrary.org/obo/HP_0001928"},{"id":"A10","pred":"hp_id","subj":"T10","obj":"http://purl.obolibrary.org/obo/HP_0002204"}],"text":"3. Results and Discussion\n\n3.1. Demographic Characteristics\nAmong 115 patients with COVID-19, the median ages were 63.55 ± 13.86 (27-96) years old, male were 66 (57.4%) cases, female were 49 (42.6%) cases, and over 60 years old were 78 (67.8%) cases. At the time of admission, mild and ordinary patients were 39 (33.9%) cases, severe patients were 48 (41.7%) cases, and critical patients were 28 (24.3%) cases (Table 1). In this study, more patients were male and more patients were more than 60 years, consistently with previous literature report [1].\n\n3.2. The Relationship between the Levels of DD1, PT1, APTT1, Fg1, and Clinical Classification\nThere are significant differences in DD1 between different clinical classifications (P \u003c 0.05). The severity of the disease increased as DD1 increased. 81 (70.4%) patients had Fg1 increased (Table 2).\n\n3.3. Relationship between the Dynamics Changes of DD, PT, APTT, TT, Fg, and the Prognosis of COVID-19\nSignificant difference (P \u003c 0.05) and positive correlation were found between DD, PT, and outcomes at composite endpoints. Correlation in third detection was stronger than that in first and second detection.\nAmong 23 patients who died, 18 (78.3%) cases had DD1 increased, 12 of 18 had DD1 two times higher (\u003e1.10 mg/L), 22 cases had DD2 and DD3 increased, 21 of 22 had DD2 and DD3 two times higher (\u003e1.10 mg/L). Eight cases in exacerbated patients occurred increased DD2 and DD3 all higher (1.10 mg/L) (Table 3).\n\n3.4. Analysis of DD and PT in Predicting Hospital Discharge and Mortality of COVID-19\nWe used the ROC curve analysis to evaluate the diagnostic value of hospital discharge and mortality in 115 patients. The AUCs of DD1, DD2, and DD3 to predict hospital discharge and mortality were 0.742, 0.818, and 0.851, respectively (Figure 1(a)). The AUCs of PT1, PT2, and PT3 to predict hospital discharge and mortality were 0.643, 0.824, and 0.937, respectively (Figure 1(b)).\n\n3.5. Dynamic Changes of Chest CT Imaging, DD and CTA in COVID-19 Patients\nAt the early stage of the disease, the correlation between CT imaging changes and DD value was not obvious; however, with the progression of the disease, the change of CT was closely related to the increase of DD value, and there was a significant statistical difference (Table 4).\nThe clinical observation showed that the abnormal coagulation factor was consistent with the CT imaging results. In this paper, a typical patient was taken as an example. The dynamic changes of chest CT imaging and DD were consistent (Figure 2(a)). Increased DD was associated with pulmonary embolism, which was confirmed by CTA (Figure 2(b))."}

2_test

{"project":"2_test","denotations":[{"id":"32596339-32109013-7053677","span":{"begin":549,"end":550},"obj":"32109013"}],"text":"3. Results and Discussion\n\n3.1. Demographic Characteristics\nAmong 115 patients with COVID-19, the median ages were 63.55 ± 13.86 (27-96) years old, male were 66 (57.4%) cases, female were 49 (42.6%) cases, and over 60 years old were 78 (67.8%) cases. At the time of admission, mild and ordinary patients were 39 (33.9%) cases, severe patients were 48 (41.7%) cases, and critical patients were 28 (24.3%) cases (Table 1). In this study, more patients were male and more patients were more than 60 years, consistently with previous literature report [1].\n\n3.2. The Relationship between the Levels of DD1, PT1, APTT1, Fg1, and Clinical Classification\nThere are significant differences in DD1 between different clinical classifications (P \u003c 0.05). The severity of the disease increased as DD1 increased. 81 (70.4%) patients had Fg1 increased (Table 2).\n\n3.3. Relationship between the Dynamics Changes of DD, PT, APTT, TT, Fg, and the Prognosis of COVID-19\nSignificant difference (P \u003c 0.05) and positive correlation were found between DD, PT, and outcomes at composite endpoints. Correlation in third detection was stronger than that in first and second detection.\nAmong 23 patients who died, 18 (78.3%) cases had DD1 increased, 12 of 18 had DD1 two times higher (\u003e1.10 mg/L), 22 cases had DD2 and DD3 increased, 21 of 22 had DD2 and DD3 two times higher (\u003e1.10 mg/L). Eight cases in exacerbated patients occurred increased DD2 and DD3 all higher (1.10 mg/L) (Table 3).\n\n3.4. Analysis of DD and PT in Predicting Hospital Discharge and Mortality of COVID-19\nWe used the ROC curve analysis to evaluate the diagnostic value of hospital discharge and mortality in 115 patients. The AUCs of DD1, DD2, and DD3 to predict hospital discharge and mortality were 0.742, 0.818, and 0.851, respectively (Figure 1(a)). The AUCs of PT1, PT2, and PT3 to predict hospital discharge and mortality were 0.643, 0.824, and 0.937, respectively (Figure 1(b)).\n\n3.5. Dynamic Changes of Chest CT Imaging, DD and CTA in COVID-19 Patients\nAt the early stage of the disease, the correlation between CT imaging changes and DD value was not obvious; however, with the progression of the disease, the change of CT was closely related to the increase of DD value, and there was a significant statistical difference (Table 4).\nThe clinical observation showed that the abnormal coagulation factor was consistent with the CT imaging results. In this paper, a typical patient was taken as an example. The dynamic changes of chest CT imaging and DD were consistent (Figure 2(a)). Increased DD was associated with pulmonary embolism, which was confirmed by CTA (Figure 2(b))."}

PMC:7301188 / 6180-8813 JSONTXT

Annnotations TAB JSON ListView MergeView

PMC:7301188 / 6180-8813 JSON TXT