A Worldwide Perspective of Atypical Pathogens in Community-acquired Pneumonia
Bibliographic record
Abstract
RATIONALE: Controversy still exists in the international literature regarding the need to use antimicrobials covering atypical pathogens when initially treating hospitalized patients with community-acquired pneumonia (CAP). In different regions of the world, monotherapy with a beta-lactam antimicrobial is common. OBJECTIVES: We sought to correlate the incidence of CAP due to atypical pathogens in different regions of the world with the proportion of patients treated with an atypical regimen in those same regions. In addition, we sought to compare clinical outcomes of patients with CAP treated with and without atypical coverage. METHODS: A secondary analysis was performed using two comprehensive international databases. World regions were defined as North America (I), Europe (II), Latin America (III), and Asia and Africa (IV). Time to reach clinical stability, length of hospital stay, and mortality were compared between patients treated with and without atypical coverage. MEASUREMENTS AND MAIN RESULTS: The incidence of CAP due to atypical pathogens from 4,337 patients was 22, 28, 21, and 20% in regions I-IV, respectively. The proportion of patients treated with atypical coverage from 2,208 patients was 91, 74, 53, and 10% in regions I-IV, respectively. Patients treated with atypical coverage had decreased time to clinical stability (3.7 vs. 3.2 d, p < 0.001), decreased length of stay (7.1 vs. 6.1 d, p < 0.01), decreased total mortality (11.1 vs. 7%, p < 0.01), and decreased CAP-related mortality (6.4 vs. 3.8%, p = 0.05). CONCLUSIONS: The significant global presence of atypical pathogens and the better outcomes associated with antimicrobial regimens with atypical coverage support empiric therapy for all hospitalized patients with CAP with a regimen that covers atypical pathogens.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".