Bibliographic record
Abstract
PURPOSE OF REVIEW: This review examines the epidemiology, diagnosis, prognosis, treatment and prevention of community-acquired pneumonia (CAP) in adults. RECENT FINDINGS: CAP is a significant cause of morbidity and mortality. Streptococcus pneumoniae is the most common CAP pathogen; however, microbial cause varies by geographic location and host factors. Identification of a microbial cause in CAP remains challenging - 30-65% of cases do not have a pathogen isolated. The use of molecular techniques in addition to culture, serology and urinary antigen testing has improved diagnostic yield. Scoring systems are useful for CAP prognostication and site of care decisions. Studies evaluating novel biomarkers including pro-B-type natriuretic peptide and procalcitonin suggest potential adjunctive roles in CAP prognosis. Guideline-based treatment for CAP has changed little in recent years. Effective and timely antimicrobial therapy is crucial in optimizing outcomes and should be based on local antimicrobial susceptibility patterns. Macrolides may have additional anti-inflammatory properties and a mortality benefit in severe CAP. Preventive strategies include immunization and modification of specific patient risk factors. SUMMARY: CAP is common and causes considerable morbidity and mortality. A comprehensive approach including advanced diagnostic testing, effective and timely antimicrobial therapy and prevention is required to optimize CAP outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".