Mortality from invasive pneumococcal pneumonia in the era of antibiotic resistance, 1995-1997
Bibliographic record
Abstract
OBJECTIVES: This study examined epidemiologic factors affecting mortality from pneumococcal pneumonia in 1995 through 1997. METHODS: Persons residing in a surveillance area who had community-acquired pneumonia requiring hospitalization and Streptococcus pneumoniae isolated from a sterile site were included in the analysis. Factors affecting mortality were evaluated in univariate and multivariate analyses. The number of deaths from pneumococcal pneumonia requiring hospitalization in the United States in 1996 was estimated. RESULTS: Of 5837 cases, 12% were fatal. Increased mortality was associated with older age, underlying disease. Asian race, and residence in Toronto/Peel, Ontario. When these factors were controlled for, increased mortality was not associated with resistance to penicillin or cefotaxime. However, when deaths during the first 4 hospital days were excluded, mortality was significantly associated with penicillin minimum inhibitory concentrations of 4.0 or higher and cefotaxime minimum inhibitory concentrations of 2.0 or higher. In 1996, about 7000 to 12,500 deaths occurred in the United States from pneumococcal pneumonia requiring hospitalization. CONCLUSIONS: Older age and underlying disease remain the most important factors influencing death from pneumococcal pneumonia. Mortality was not elevated in most infections with beta-lactam-resistant pneumococci.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".