Risk of Severe Outcomes From COVID-19 in Comorbid Populations in the Omicron Era: A Meta-analysis
Bibliographic record
Abstract
Abstract Importance This is the first meta-analysis to investigate risk of death and hospitalization in individuals with comorbidities, specifically during the Omicron era. Objective To assess the risk of mortality and hospitalization from COVID-19 in individuals with comorbidities in comparison with individuals without comorbidities during the Omicron era. Data Sources A systematic search of Embase, MEDLINE, PubMed, Europe PMC, Latin American and Caribbean Health Sciences Literature, Cochrane COVID-19 Study Register, and WHO COVID-19 Database was performed to identify studies published between 1 January 2022 and 13 March 2024. Study Selection Inclusion criteria were observational studies including people (all ages) with at least 1 of the following comorbidities: cardiovascular/ cerebrovascular disease, chronic lung conditions, diabetes, and obesity. In total, 72 studies were included in the review, of which 68 were meta-analyzed. Data Extraction and Synthesis Data were extracted by one reviewer and verified by a second. Studies were synthesized quantitively (meta-analysis) using random-effect models. PRISMA guidelines were followed. Main Outcomes and Measures Evaluated outcomes were the risks of death, hospitalization, intensive care unit (ICU) admission, and any combination of these outcomes. Odds ratios, hazard ratios, and rate ratios were extracted; pooled relative risk (RR) and 95% confidence intervals (CI) were calculated. Results Minimum numbers of participants per comorbidity across included studies ranged from 328 870 for thrombosis to 13 720 480 for hypertension. Risks of death, hospitalization, and the combined outcome were increased in individuals with cerebrovascular disease, COPD, diabetes, respiratory diseases, heart disease, and heart failure versus those without (pooled RRs ranged from 1.27 [heart disease, hospitalization; 95% CI, 1.17-1.38, P < .001] to 1.78 [heart failure, death: 95% CI, 1.46-2.16, P < .001]). Individuals with diabetes and obesity had increased risk of ICU admission (RR: 1.20; 95% CI: 1.04-1.38, P = .0141 and RR: 1.32; 95% CI: 1.11-1.57, P = .00158, respectively). Conclusions During the Omicron era, risk of death and hospitalization from COVID-19 is increased amongst individuals with comorbidities including cerebrovascular/cardiovascular conditions, chronic lung diseases, and diabetes, with the highest risk in those with heart failure. Individuals with diabetes and obesity are at increased risk of ICU admission. Key Points Question What are the risks of severe outcomes from COVID-19 in individuals with comorbidities during the Omicron era? Findings This systematic review and meta-analysis found increased risk of mortality and hospitalization among individuals with a range of comorbidities, including cerebrovascular/cardiovascular conditions, chronic lung diseases, and diabetes, with the highest risk in those with heart failure, versus those without. Risk of ICU admission was higher in individuals with obesity and diabetes. Meaning This study identified comorbid populations most at risk of severe outcomes from COVID-19. Targeting these populations with public health measures, such as vaccination, may be beneficial.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.068 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".