Adherence to Treatment Guideline Improves Patient Outcomes in a Prospective Cohort of Adults Hospitalized for Community-Acquired Pneumonia
Bibliographic record
Abstract
Abstract Background Understanding local epidemiology and etiologies of community-acquired pneumonia in hospitalized patients is crucial for determining the appropriateness of treatment guidelines. We aim to determine the etiologies, severity, and outcomes in adults hospitalized for community-acquired pneumonia and to study the impact of empirical antibiotic therapy on patient outcomes. Methods We performed a prospective observational cohort study involving adults hospitalized for community-acquired pneumonia in Hong Kong. Sputum, nasopharyngeal aspirate, blood, and urine were collected for bacterial culture, molecular tests for detection of viruses and atypical pathogens, and antigen tests. Multivariable logistic regression model and Cox proportional hazard models were performed to determine independent factors associated with prolonged hospitalization and mortality. Results From February 2017 to July 2018, 258 patients were enrolled. The median age was 73 (interquartile range, 61–80) years, 66% were male, 57% had underlying chronic illnesses, 13% had CURB-65 score ≥3, and 10% had higher 1-year mortality. Pathogens were identified in 45% of patients; 20% had viral, 15% had bacterial, and 9% had polymicrobial pneumonia. Streptococcus pneumoniae (12%), influenza virus (12%), and Mycoplasma pneumoniae (1.2%) were the most common bacterial, viral, and atypical pathogens, respectively. Nonadherence to local empirical antibiotic treatment guidelines (primarily recommending beta-lactam and doxycycline) was observed in 25% and was independently associated with prolonged hospitalization (≥7 days) and higher mortality, after adjustment for age, underlying chronic illness, and disease severity. Conclusions Adherence to treatment guidelines was associated with shorter hospitalization and improved survival. We provided evidence for the use of doxycycline for coverage of atypical pathogens in nonsevere pneumonia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".