tetano
Editor, Senior Moderator
PLoS One
. 2025 Mar 31;20(3):e0319585.
doi: 10.1371/journal.pone.0319585. eCollection 2025. Health diagnosis associated with COVID-19 death in the United States: A retrospective cohort study using electronic health records
Mariam Joseph[SUP] 1 [/SUP], Qiwei Li[SUP] 2 [/SUP], Sunyoung Shin[SUP] 3 [/SUP]
Affiliations
Background: 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.
Objective: 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.
Methods: 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.
Results: 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, Complications mainly related to pregnancy (Adjusted Odds Ratio, OR:2.95; 95% Confidence Interval, CI:1.4 - 6.23) hold the highest odds ratio in influencing COVID-19 death followed by Other diseases of the respiratory system (OR:2.0; CI:1.84 - 2.18), Renal failure (OR:1.76; CI:1.61 - 1.93), Influenza and pneumonia (OR:1.53; CI:1.41 - 1.67), Other bacterial diseases (OR:1.45; CI:1.31 - 1.61), Coagulation defects, purpura and other hemorrhagic conditions(OR:1.37; CI:1.22 - 1.54), Injuries to the head (OR:1.27; CI:1.1 - 1.46), Mood [affective] disorders (OR:1.24; CI:1.12 - 1.36), Aplastic and other anemias (OR:1.22; CI:1.12 - 1.34), Chronic obstructive pulmonary disease and allied conditions (OR:1.18; CI:1.06 - 1.32), Other forms of heart disease (OR:1.18; CI:1.09 - 1.28), Infections of the skin and subcutaneous tissue (OR: 1.15; CI:1.04 - 1.27), Diabetes mellitus (OR:1.14; CI:1.03 - 1.26), and Other diseases of the urinary system (OR:1.12; CI:1.03 - 1.21).
Conclusion: 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.
. 2025 Mar 31;20(3):e0319585.
doi: 10.1371/journal.pone.0319585. eCollection 2025. Health diagnosis associated with COVID-19 death in the United States: A retrospective cohort study using electronic health records
Mariam Joseph[SUP] 1 [/SUP], Qiwei Li[SUP] 2 [/SUP], Sunyoung Shin[SUP] 3 [/SUP]
Affiliations
- PMID: 40163461
- DOI: 10.1371/journal.pone.0319585
Background: 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.
Objective: 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.
Methods: 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.
Results: 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, Complications mainly related to pregnancy (Adjusted Odds Ratio, OR:2.95; 95% Confidence Interval, CI:1.4 - 6.23) hold the highest odds ratio in influencing COVID-19 death followed by Other diseases of the respiratory system (OR:2.0; CI:1.84 - 2.18), Renal failure (OR:1.76; CI:1.61 - 1.93), Influenza and pneumonia (OR:1.53; CI:1.41 - 1.67), Other bacterial diseases (OR:1.45; CI:1.31 - 1.61), Coagulation defects, purpura and other hemorrhagic conditions(OR:1.37; CI:1.22 - 1.54), Injuries to the head (OR:1.27; CI:1.1 - 1.46), Mood [affective] disorders (OR:1.24; CI:1.12 - 1.36), Aplastic and other anemias (OR:1.22; CI:1.12 - 1.34), Chronic obstructive pulmonary disease and allied conditions (OR:1.18; CI:1.06 - 1.32), Other forms of heart disease (OR:1.18; CI:1.09 - 1.28), Infections of the skin and subcutaneous tissue (OR: 1.15; CI:1.04 - 1.27), Diabetes mellitus (OR:1.14; CI:1.03 - 1.26), and Other diseases of the urinary system (OR:1.12; CI:1.03 - 1.21).
Conclusion: 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.