The association between non-communicable diseases and COVID-19 severity and mortality among infected hospitalized healthcare workers in 29 countries: a cohort study
Bibliographic record
Abstract
Background: Due to occupational exposure, healthcare workers (HCWs) have a higher risk of Coronavirus Disease 2019(COVID-19) infection than the general population. Non-communicable diseases (NCDs) may increase the risk of COVID-19-related morbidity and mortality among HCWs, potentially reducing the available health workforce. We examined the association between NCDs and COVID-19 disease severity and mortality among infected HCWs. Methods: This cohort study used data from the International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) database. HCWs hospitalized between January 2020 and January 2023 due to clinically suspected or laboratory-confirmed COVID-19 were eligible for inclusion. Variables collected included demographic data, comorbidities, and hospitalization outcomes. Descriptive statistics were reported using mean/standard deviation (SD), median/interquartile range (IQR), or frequencies and proportions. For each NCD, the relative risk of death, adjusted for age and sex, was calculated using log-binomial regression as well as the population-attributable fraction. Results: There were 17,502 HCWs, 95.7% of whom had a confirmed COVID-19 diagnosis. The majority were female (66.5%) and the mean age (SD) was 49.8 (14.3) years. Roughly, half (51.42%) of HCWs had no comorbidities, 29.28% had one comorbidity, 14.68% had 2 comorbidities and <5% had ≥3 comorbidities. The most common comorbidities were diabetes mellitus (49.40%) and cardiovascular disease (36.90%). Approximately one-fifth of the HCWs had severe COVID-19 (16.95%) and 10.68% of the HCWs with COVID-19 died. Being ≥45 years old, male gender, smoking, obesity, and certain NCDs increased the risk of COVID-19 severity and mortality. Obesity and diabetes mellitus were the leading risk factors in terms of the population-attributable risk for COVID-19 severity (6.89%) and mortality (36.00%) respectively. Conclusions: Many HCWs with COVID-19 had one or more NCDs. Obesity and diabetes mellitus increased COVID-19 severity and mortality risk. Reducing the prevalence of obesity and diabetes mellitus would yield the biggest reduction in COVID-19-related morbidity and mortality among HCWs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.117 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".