Risk Factors and Outcomes Associated with Chronic Obstructive Pulmonary Disease Exacerbations Requiring Hospitalization
Bibliographic record
Abstract
BACKGROUND: Acute respiratory exacerbations are the most frequent cause of medical visits, hospitalization and death for chronic obstructive pulmonary disease (COPD) patients and, thus, exert a significant social and economic burden on society. OBJECTIVE: To identify the risk factors associated with hospital readmission(s) for acute exacerbation(s) of COPD (AECOPD). METHODS: A review of admission records from three large urban hospitals in Vancouver, British Columbia, identified 310 consecutive patients admitted for an AECOPD between April 1, 2001, and December 31, 2002. Logistic regression analysis was performed to identify risk factors for readmissions following an AECOPD. RESULTS: During the study period, 38% of subjects were readmitted at least once. The mean (+/- SD) duration from the index admission to the first readmission was 5+/-4.08 months. Comparative analysis among the three hospitals identified a significant difference in readmission rates (54%, 36% and 18%, respectively). Logistic regression analysis revealed that preadmission home oxygen use (OR 2.55; 95%CI 1.45 to 4.42; P=0.001), history of a lung infection within the previous year (OR 1.73; 95% CI 1.01 to 2.97; P=0.048), other chronic respiratory disease (OR 1.78; 95% CI 1.06 to 2.99; P=0.03) and shorter length of hospital stay (OR 0.97; 95% CI 0.945 to 0.995; P=0.021) were independently associated with frequent readmissions for an AECOPD. CONCLUSIONS: Hospital readmission rates for AECOPD were high. Only four clinical factors were found to be independently associated with COPD readmission. There was significant variability in the readmission rate among hospitals. This variability may be a result of differences in the patient populations that each hospital serves or may reflect variability in health care delivery at different institutions.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".