Ten-Year Mortality after Community-acquired Pneumonia. A Prospective Cohort
Bibliographic record
Abstract
RATIONALE: Information on the long-term prognosis after community-acquired pneumonia (CAP) is limited. OBJECTIVES: To determine if CAP increases adverse long-term outcomes relative to a control population. METHODS: Between 2000 and 2002, 6,078 adults with CAP from six hospitals and seven emergency departments in Edmonton (AB, Canada) were prospectively recruited and matched on age, sex, and site of treatment with five control subjects without pneumonia (n = 29,402). Mortality, hospitalizations, and emergency department admissions through 2012 were evaluated using multivariable Cox proportional hazards analyses adjusted for socioeconomic status and comorbidities. MEASUREMENTS AND MAIN RESULTS: Average age was 59 years (2,682 [44%] ≥ 65 yr), 3,214 (53%) were men, and 3,425 (56%) were managed as outpatients. Over a median of 9.8 years, 2,858 patients with CAP died compared with 9,399 control subjects (absolute risk difference, 30 per 1,000 patient years [py]; adjusted hazard ratio [aHR], 1.65; 95% confidence interval, 1.57-1.73; P < 0.001). Patients with CAP who were younger than 25 years old had the lowest absolute rate difference for mortality (4 per 1,000 py; aHR, 2.40), and patients older than 80 years old had the highest absolute rate difference (92 per 1,000 py; aHR, 1.42). Absolute rates of all-cause hospitalization, emergency department visits, and CAP-related visits were all significantly higher in patients with CAP compared with control subjects (P < 0.001 for all comparisons). CONCLUSIONS: Our results indicate that an episode of CAP confers a high risk of long-term adverse events compared with the general population who have not experienced CAP, and this is irrespective of age.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".