{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T15:59:38Z","timestamp":1787068778884,"version":"build-2736575974"},"reference-count":42,"publisher":"Public Library of Science (PLoS)","issue":"3","license":[{"start":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T00:00:00Z","timestamp":1743379200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"POSCO HOLDINGS","award":["2023Q033"],"award-info":[{"award-number":["2023Q033"]}]},{"DOI":"10.13039\/100000121","name":"Division of Mathematical Sciences","doi-asserted-by":"publisher","award":["DMS-2113674"],"award-info":[{"award-number":["DMS-2113674"]}],"id":[{"id":"10.13039\/100000121","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000121","name":"Division of Mathematical Sciences","doi-asserted-by":"publisher","award":["DMS-2113674"],"award-info":[{"award-number":["DMS-2113674"]}],"id":[{"id":"10.13039\/100000121","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000121","name":"Division of Mathematical Sciences","doi-asserted-by":"publisher","award":["DMS-2210912"],"award-info":[{"award-number":["DMS-2210912"]}],"id":[{"id":"10.13039\/100000121","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["R01GM141519"],"award-info":[{"award-number":["R01GM141519"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"crossref","award":["RS-2023-00243012"],"award-info":[{"award-number":["RS-2023-00243012"]}],"id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"crossref","award":["RS-2023-00219980"],"award-info":[{"award-number":["RS-2023-00219980"]}],"id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"crossref","award":["NRF-2021R1A6A1A10042944"],"award-info":[{"award-number":["NRF-2021R1A6A1A10042944"]}],"id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The United States has experienced high surge in COVID-19 cases since the dawn of 2020. Identifying the types of diagnoses that pose a risk in leading COVID-19 death casualties will enable our community to obtain a better perspective in identifying the most vulnerable populations and enable these populations to implement better precautionary measures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To identify demographic factors and health diagnosis codes that pose a high or a low risk to COVID-19 death from individual health record data sourced from the United States.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used logistic regression models to analyze the top 500 health diagnosis codes and demographics that have been identified as being associated with COVID-19 death.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among 223,286 patients tested positive at least once, 218,831 (98%) patients were alive and 4,455 (2%) patients died during the duration of the study period. Through our logistic regression analysis, four demographic characteristics of patients; age, gender, race and region, were deemed to be associated with COVID-19 mortality. Patients from the West region of the United States: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming had the highest odds ratio of COVID-19 mortality across the United States. In terms of diagnoses,\n                      <jats:italic>Complications mainly related to pregnancy<\/jats:italic>\n                      (Adjusted Odds Ratio, OR:2.95; 95% Confidence Interval, CI:1.4 - 6.23\n                      <jats:italic>)<\/jats:italic>\n                      hold the highest odds ratio in influencing COVID-19 death followed by\n                      <jats:italic>Other diseases of the respiratory system<\/jats:italic>\n                      (OR:2.0; CI:1.84 \u2013 2.18)\n                      <jats:italic>, Renal failure<\/jats:italic>\n                      (OR:1.76; CI:1.61 \u2013 1.93)\n                      <jats:italic>, Influenza and pneumonia<\/jats:italic>\n                      (OR:1.53; CI:1.41 \u2013 1.67)\n                      <jats:italic>, Other bacterial diseases<\/jats:italic>\n                      (OR:1.45; CI:1.31 \u2013 1.61)\n                      <jats:italic>, Coagulation defects, purpura and other hemorrhagic conditions<\/jats:italic>\n                      (OR:1.37; CI:1.22 \u2013 1.54)\n                      <jats:italic>, Injuries to the head<\/jats:italic>\n                      (OR:1.27; CI:1.1 - 1.46),\n                      <jats:italic>Mood [affective] disorders<\/jats:italic>\n                      (OR:1.24; CI:1.12 \u2013 1.36\n                      <jats:italic>), Aplastic and other anemias<\/jats:italic>\n                      (OR:1.22; CI:1.12 \u2013 1.34)\n                      <jats:italic>, Chronic obstructive pulmonary disease and allied conditions<\/jats:italic>\n                      (OR:1.18; CI:1.06 \u2013 1.32)\n                      <jats:italic>, Other forms of heart disease<\/jats:italic>\n                      (OR:1.18; CI:1.09 \u2013 1.28)\n                      <jats:italic>, Infections of the skin and subcutaneous tissue<\/jats:italic>\n                      (OR: 1.15; CI:1.04 \u2013 1.27),\n                      <jats:italic>Diabetes mellitus<\/jats:italic>\n                      (OR:1.14; CI:1.03 \u2013 1.26)\n                      <jats:italic>, and Other diseases of the urinary system<\/jats:italic>\n                      (OR:1.12; CI:1.03 \u2013 1.21).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We found demographic factors and medical conditions, including some novel ones which are associated with COVID-19 death. These findings can be used for clinical and public awareness and for future research purposes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0319585","type":"journal-article","created":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T15:30:24Z","timestamp":1743435024000},"page":"e0319585","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Health diagnosis associated with COVID-19 death in the United States: A retrospective cohort study using electronic health 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