Factors Influencing Early and Late Mortality in Adults with Invasive Pneumococcal Disease in Calgary, Canada: A Prospective Surveillance Study
Bibliographic record
Abstract
BACKGROUND: Invasive pneumococcal disease continues to be an important cause of mortality. In Calgary, 60% of deaths occur within 5 days of presenting to hospital. This proportion has not changed since before the era of penicillin. The purpose of this study was to investigate what factors may influence death within 5 days of presentation with pneumococcal disease. METHODS AND FINDINGS: Demographic and clinical data from the CASPER (Calgary Area Streptococcus pneumoniae Epidemiology Research) study on 1065 episodes of invasive pneumococcal disease in adults (≥18 years) from 2000 to 2010 were analyzed. Adjusted multinomial regression was performed to analyze 3 outcomes: early mortality (<5 days post-presentation), late mortality (5-30 days post-presentation), and survival, generating relative risk ratios (RRR). Patients with severe disease had increased risk of early and late death. In multinomial regression with survivors as baseline, the risk of early death increased in those with a Charlson index ≥2 (RRR: 6.3, 95% CI: 1.8-21.9); the risk of late death increased in those with less severe disease and a Charlson ≥2 (RRR: 6.1, 95% CI: 1.4-27.7). Patients who never received appropriate antibiotics had 5.6X (95% CI: 2.4-13.1) the risk of early death. Risk of both early and late death increased by a RRR of 1.3 (95% CI: 1.2-1.4) per 5-year increase in age. In multinomial regression, there were no significant differences in the effects of the factors tested between early and late mortality. CONCLUSIONS: Presenting with severe invasive pneumococcal disease, multiple comorbidities, and older age increases the risk of both early and late death. Patients who died early often presented too late for effective antibiotic therapy, highlighting the need for an effective vaccine.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".