Prognostic value of Pneumonia Severity Index, CURB-65, CRB-65, and procalcitonin in community-acquired pneumonia in Singapore
Bibliographic record
Abstract
Objective: The purpose of this study was to evaluate the performance of three severity scoring tools and procalcitonin (PCT) in severity stratification and mortality prediction among patients with community-acquired pneumonia (CAP) in Singapore. Methods: The method used was a retrospective observational study of all the consecutive patients with CAP admitted through the emergency department of Singapore General Hospital between 2012–2013. Results: Among 1902 study subjects, the overall 30-day mortality was 15.7%. The mortality rates for Pneumonia Severity Index (PSI) class I–III were 0, 0, and 3.7%, which were comparable to the original published data. CURB-65 and CRB-65 had higher mortality rates in all severity levels. In three levels of risk stratification, the low risk group of PSI (class I–III) included 42.6% of the patients with mortality rate of 1.9%, whereas the low risk group defined by CURB-65 (score 0–1) and CRB-65 (score 0) included 52.0% and 24.4% of the patients with higher mortality rates (7.3% and 4.5% respectively). PSI was the most sensitive in mortality prediction with area under receiver operating characteristic (ROC) curve of 0.82, higher than CURB-65 (0.71), CRB-65 (0.67), and PCT (0.63) ( p<0.001). The initial level of PCT was higher in non-survivors and intensive care unit (ICU)-admitted patients compared to survivors (0.91 vs 0.36 ng/ml, p<0.001) and non-ICU patients (3.70 vs 0.38 ng/ml, p<0.001). Incorporating PCT did not improve the discriminatory power of the scoring tools for mortality prediction. Conclusions: PSI was a reliable tool for severity stratification and morality prediction among the patients with CAP in Singapore.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".