PMC:7417201 / 14481-15324 JSONTXT

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T26","span":{"begin":323,"end":327},"obj":"Body_part"},{"id":"T27","span":{"begin":378,"end":383},"obj":"Body_part"},{"id":"T28","span":{"begin":820,"end":835},"obj":"Body_part"}],"attributes":[{"id":"A26","pred":"fma_id","subj":"T26","obj":"http://purl.org/sig/ont/fma/fma256135"},{"id":"A27","pred":"fma_id","subj":"T27","obj":"http://purl.org/sig/ont/fma/fma9576"},{"id":"A28","pred":"fma_id","subj":"T28","obj":"http://purl.org/sig/ont/fma/fma49893"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}

{"project":"LitCovid-PD-UBERON","denotations":[{"id":"T28","span":{"begin":378,"end":383},"obj":"Body_part"},{"id":"T29","span":{"begin":820,"end":835},"obj":"Body_part"},{"id":"T30","span":{"begin":829,"end":835},"obj":"Body_part"}],"attributes":[{"id":"A28","pred":"uberon_id","subj":"T28","obj":"http://purl.obolibrary.org/obo/UBERON_0001443"},{"id":"A29","pred":"uberon_id","subj":"T29","obj":"http://purl.obolibrary.org/obo/UBERON_0001621"},{"id":"A30","pred":"uberon_id","subj":"T30","obj":"http://purl.obolibrary.org/obo/UBERON_0001637"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T86","span":{"begin":98,"end":106},"obj":"Disease"},{"id":"T87","span":{"begin":197,"end":199},"obj":"Disease"},{"id":"T88","span":{"begin":222,"end":224},"obj":"Disease"},{"id":"T89","span":{"begin":426,"end":434},"obj":"Disease"},{"id":"T90","span":{"begin":568,"end":580},"obj":"Disease"},{"id":"T91","span":{"begin":619,"end":633},"obj":"Disease"},{"id":"T92","span":{"begin":722,"end":725},"obj":"Disease"},{"id":"T94","span":{"begin":763,"end":765},"obj":"Disease"},{"id":"T95","span":{"begin":816,"end":819},"obj":"Disease"},{"id":"T97","span":{"begin":820,"end":843},"obj":"Disease"},{"id":"T98","span":{"begin":829,"end":843},"obj":"Disease"}],"attributes":[{"id":"A86","pred":"mondo_id","subj":"T86","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A87","pred":"mondo_id","subj":"T87","obj":"http://purl.obolibrary.org/obo/MONDO_0002125"},{"id":"A88","pred":"mondo_id","subj":"T88","obj":"http://purl.obolibrary.org/obo/MONDO_0002125"},{"id":"A89","pred":"mondo_id","subj":"T89","obj":"http://purl.obolibrary.org/obo/MONDO_0005015"},{"id":"A90","pred":"mondo_id","subj":"T90","obj":"http://purl.obolibrary.org/obo/MONDO_0005044"},{"id":"A91","pred":"mondo_id","subj":"T91","obj":"http://purl.obolibrary.org/obo/MONDO_0021187"},{"id":"A92","pred":"mondo_id","subj":"T92","obj":"http://purl.obolibrary.org/obo/MONDO_0005010"},{"id":"A93","pred":"mondo_id","subj":"T92","obj":"http://purl.obolibrary.org/obo/MONDO_0018922"},{"id":"A94","pred":"mondo_id","subj":"T94","obj":"http://purl.obolibrary.org/obo/MONDO_0002125"},{"id":"A95","pred":"mondo_id","subj":"T95","obj":"http://purl.obolibrary.org/obo/MONDO_0005010"},{"id":"A96","pred":"mondo_id","subj":"T95","obj":"http://purl.obolibrary.org/obo/MONDO_0018922"},{"id":"A97","pred":"mondo_id","subj":"T97","obj":"http://purl.obolibrary.org/obo/MONDO_0005010"},{"id":"A98","pred":"mondo_id","subj":"T98","obj":"http://purl.obolibrary.org/obo/MONDO_0000473"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T136","span":{"begin":274,"end":278},"obj":"http://purl.obolibrary.org/obo/UBERON_0003101"},{"id":"T137","span":{"begin":274,"end":278},"obj":"http://www.ebi.ac.uk/efo/EFO_0000970"},{"id":"T138","span":{"begin":378,"end":383},"obj":"http://www.ebi.ac.uk/efo/EFO_0000965"},{"id":"T139","span":{"begin":829,"end":835},"obj":"http://purl.obolibrary.org/obo/UBERON_0001637"},{"id":"T140","span":{"begin":829,"end":835},"obj":"http://www.ebi.ac.uk/efo/EFO_0000814"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T19","span":{"begin":197,"end":199},"obj":"Chemical"},{"id":"T20","span":{"begin":222,"end":224},"obj":"Chemical"},{"id":"T21","span":{"begin":763,"end":765},"obj":"Chemical"}],"attributes":[{"id":"A19","pred":"chebi_id","subj":"T19","obj":"http://purl.obolibrary.org/obo/CHEBI_74813"},{"id":"A20","pred":"chebi_id","subj":"T20","obj":"http://purl.obolibrary.org/obo/CHEBI_74813"},{"id":"A21","pred":"chebi_id","subj":"T21","obj":"http://purl.obolibrary.org/obo/CHEBI_74813"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}

{"project":"LitCovid-sentences","denotations":[{"id":"T121","span":{"begin":0,"end":167},"obj":"Sentence"},{"id":"T122","span":{"begin":168,"end":182},"obj":"Sentence"},{"id":"T123","span":{"begin":183,"end":232},"obj":"Sentence"},{"id":"T124","span":{"begin":233,"end":273},"obj":"Sentence"},{"id":"T125","span":{"begin":274,"end":322},"obj":"Sentence"},{"id":"T126","span":{"begin":323,"end":377},"obj":"Sentence"},{"id":"T127","span":{"begin":378,"end":425},"obj":"Sentence"},{"id":"T128","span":{"begin":426,"end":470},"obj":"Sentence"},{"id":"T129","span":{"begin":471,"end":522},"obj":"Sentence"},{"id":"T130","span":{"begin":523,"end":567},"obj":"Sentence"},{"id":"T131","span":{"begin":568,"end":618},"obj":"Sentence"},{"id":"T132","span":{"begin":619,"end":670},"obj":"Sentence"},{"id":"T133","span":{"begin":671,"end":715},"obj":"Sentence"},{"id":"T134","span":{"begin":716,"end":762},"obj":"Sentence"},{"id":"T135","span":{"begin":763,"end":843},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}

{"project":"LitCovid-PD-HP","denotations":[{"id":"T23","span":{"begin":378,"end":388},"obj":"Phenotype"},{"id":"T24","span":{"begin":523,"end":530},"obj":"Phenotype"},{"id":"T25","span":{"begin":568,"end":580},"obj":"Phenotype"},{"id":"T26","span":{"begin":619,"end":633},"obj":"Phenotype"}],"attributes":[{"id":"A23","pred":"hp_id","subj":"T23","obj":"http://purl.obolibrary.org/obo/HP_0100749"},{"id":"A24","pred":"hp_id","subj":"T24","obj":"http://purl.obolibrary.org/obo/HP_0002094"},{"id":"A25","pred":"hp_id","subj":"T25","obj":"http://purl.obolibrary.org/obo/HP_0000822"},{"id":"A26","pred":"hp_id","subj":"T26","obj":"http://purl.obolibrary.org/obo/HP_0003077"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}

{"project":"LitCovid-PubTator","denotations":[{"id":"193","span":{"begin":722,"end":725},"obj":"Gene"},{"id":"194","span":{"begin":173,"end":224},"obj":"Disease"},{"id":"195","span":{"begin":384,"end":388},"obj":"Disease"},{"id":"196","span":{"begin":426,"end":434},"obj":"Disease"},{"id":"197","span":{"begin":523,"end":530},"obj":"Disease"},{"id":"198","span":{"begin":568,"end":580},"obj":"Disease"},{"id":"199","span":{"begin":619,"end":633},"obj":"Disease"},{"id":"201","span":{"begin":98,"end":106},"obj":"Disease"},{"id":"204","span":{"begin":763,"end":765},"obj":"Disease"},{"id":"205","span":{"begin":816,"end":843},"obj":"Disease"}],"attributes":[{"id":"A193","pred":"tao:has_database_id","subj":"193","obj":"Gene:730249"},{"id":"A194","pred":"tao:has_database_id","subj":"194","obj":"MESH:C000657245"},{"id":"A195","pred":"tao:has_database_id","subj":"195","obj":"MESH:D010146"},{"id":"A196","pred":"tao:has_database_id","subj":"196","obj":"MESH:D003920"},{"id":"A197","pred":"tao:has_database_id","subj":"197","obj":"MESH:D004417"},{"id":"A198","pred":"tao:has_database_id","subj":"198","obj":"MESH:D006973"},{"id":"A199","pred":"tao:has_database_id","subj":"199","obj":"MESH:D006949"},{"id":"A201","pred":"tao:has_database_id","subj":"201","obj":"MESH:C000657245"},{"id":"A205","pred":"tao:has_database_id","subj":"205","obj":"MESH:D003324"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}

{"project":"LitCovid-PMC-OGER-BB","denotations":[{"id":"T82716","span":{"begin":786,"end":796},"obj":"UBERON:0002349"},{"id":"T1355","span":{"begin":820,"end":835},"obj":"UBERON:0001621"}],"text":"Table 3 Multivariable logistic regression analysis with abnormal MPI as dependent variable during COVID-19 emergency and during 2017–2019 3-year’s corresponding months\n2020 2017–2019\nβ coefficient SE P value β coefficient SE P value\nAge 0.005 0.023 0.834 − 0.004 0.007 0.60\nMale gender 0.162 0.639 0.799 0.671 0.166 \u003c .001\nBody mass index − 0.013 0.049 0.785 − 0.024 0.014 0.08\nChest pain 0.542 0.508 0.286 − 0.264 0.149 0.08\nDiabetes 0.565 0.466 0.225 0.310 0.148 \u003c .05\nFamily history 0.180 0.454 0.692 − 0.163 0.150 0.28\nDyspnea 0.362 0.382 0.343 − 0.085 0.120 0.48\nHypertension − 1.573 0.709 \u003c .05 0.376 0.196 \u003c .05\nHyperlipidemia 0.822 0.621 0.186 − 0.239 0.167 0.15\nSmoking 0.619 0.533 0.245 − 0.102 0.152 0.50\nKnown CAD 0.137 0.541 \u003c.001 1.994 0.154 \u003c .001\nSE standard error, MPI myocardial perfusion imaging, CAD coronary artery disease"}