COPD and the risk of poor outcomes in COVID-19: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) are highly susceptible from respiratory exacerbations from viral respiratory tract infections. However, it is unclear whether they are at increased risk of COVID-19 pneumonia or COVID-19-related mortality. We aimed to determine whether COPD is a risk factor for adverse COVID-19 outcomes including hospitalization, severe COVID-19, or death. METHODS: , 2021 (PROSPERO ID: CRD42020191491). We included studies that quantified the number of COPD patients, and reported at least one of the following outcomes stratified by COPD status: hospitalization; severe COVID-19; ICU admission; mechanical ventilation; acute respiratory distress syndrome; or mortality. We meta-analyzed the results of individual studies to determine the odds ratio (OR) of these outcomes in patients with COPD compared to those without COPD. FINDINGS: Fifty-nine studies met the inclusion criteria, and underwent data extraction. Most studies were retrospective cohort studies/case series of hospitalized patients. Only four studies examined the effects of COPD on COVID-19 outcomes as their primary endpoint. In aggregate, COPD was associated with increased odds of hospitalization (OR 4.23, 95% confidence interval [CI] 3.65-4.90), ICU admission (OR 1.35, 95% CI 1.02-1.78), and mortality (OR 2.47, 95% CI 2.18-2.79). INTERPRETATION: Having a clinical diagnosis of COPD significantly increases the odds of poor clinical outcomes in patients with COVID-19. COPD patients should thus be considered a high-risk group, and targeted for preventative measures and aggressive treatment for COVID-19 including vaccination.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.042 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".