Supplementary Material for: Pneumonia Is Associated with Increased Mortality in Hospitalized COPD Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Patients with chronic obstructive pulmonary disease (COPD) are at a heightened risk of pneumonia. Whether coexisting community-acquired pneumonia (CAP) can predict increased mortality in hospitalized COPD patients is still controversial. Objective: This systematic review and meta-analysis aims to assess the association between CAP and mortality and morbidity in COPD patients hospitalized for acute worsening of respiratory symptoms. Methods: In this review, cohort studies and case-control studies investigating the impact of CAP in hospitalized COPD patients were retrieved from 4 electronic databases from inception until December 2019. Methodological quality of included studies was assessed using Newcastle-Ottawa Quality Assessment Scale. The primary outcome was mortality. The secondary outcomes included length of hospital stay, need for mechanical ventilation, intensive care unit (ICU) admission, length of ICU stay, and readmission rate. The Mantel-Haenszel method and inverse variance method were used to calculate pooled relative risk (RR) and mean difference (MD), respectively. Results: A total of 18 studies were included. The presence of CAP was associated with higher mortality (RR = 1.85; 95% CI: 1.50–2.30; p < 0.00001), longer length of hospital stay (MD = 1.89; 95% CI: 1.19–2.59; p < 0.00001), more need for mechanical ventilation (RR = 1.48; 95% CI: 1.32–1.67; p < 0.00001), and more ICU admissions (RR = 1.58; 95% CI: 1.24–2.03; p = 0.0002) in hospitalized COPD patients. CAP was not associated with longer ICU stay (MD = 5.2; 95% CI: −2.35 to 12.74; p = 0.18) or higher readmission rate (RR = 1.02; 95% CI: 0.96–1.09; p = 0.47). Conclusion: Coexisting CAP may be associated with increased mortality and morbidity in hospitalized COPD patients, so radiological confirmation of CAP should be required and more attention should be paid to these patients.
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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 | 0.004 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.493 | 0.018 |
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".