Prognostic factors for mortality due to pneumonia among adults from different age groups in Singapore and mortality predictions based on PSI and CURB-65
Bibliographic record
Abstract
INTRODUCTION: Pneumonia is associated with considerable mortality. However, there is limited information on age-specific prognostic factors for death from pneumonia. METHODS: Patients hospitalised with a diagnosis of pneumonia through the emergency department were stratified into three age groups: 18-64 years, 65-84 years and ≥ 85 years. Multivariate logistic regression and receiver operating characteristic curve analyses were conducted to evaluate prognostic factors for mortality and the performance of pneumonia severity scoring tools for mortality prediction. RESULTS: A total of 1,902 patients were enrolled (18-64 years: 614 [32.3%]; 65-84 years: 944 [49.6%]; ≥ 85 years: 344 [18.1%]). Mortality rates increased with age (18-64 years: 7.3%; 65-84 years: 16.1%; ≥ 85 years: 29.7%; p < 0.001). Malignancy and tachycardia were prognostic of mortality among patients aged 18-64 years. Male gender, malignancy, congestive heart failure and eight other parameters reflecting acute disease severity were associated with mortality among patients aged 65-84 years. For patients aged ≥ 85 years, altered mental status, tachycardia, blood urea nitrogen, hypoxaemia, arterial pH and pleural effusion were significantly predictive of mortality. The Pneumonia Severity Index (PSI) was more sensitive than CURB-65 (confusion, uraemia, respiratory rate ≥ 30 per minute, low blood pressure, age ≥ 65 years) for mortality prediction across all age groups. CONCLUSION: The predictive effect of prognostic factors for mortality varied among patients with pneumonia from the different age groups. PSI performed significantly better than CURB-65 for mortality prediction, but its discriminative power decreased with advancing age.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".