Bibliographic record
Abstract
Purpose Timely administration of antimicrobials in patients with community‐acquired pneumonia is now a standard of care. The purpose of this paper is to present a large observational study to understand the issues that result in a delay in the administration of antibiotics to patients with community‐acquired pneumonia Design/methodology/approach This prospective study involved all six hospitals in the Edmonton area: patients were enrolled at the time of hospitalization if they were adults aged ≥17 years with a clinical presentation consistent with community‐acquired pneumonia. A retrospective chart review was performed to determine the reasons why it took more than eight hours to administer the first dose of antibiotics. Findings The paper finds that of all 3,394 hospitalized patients, 646 (19.0 percent) received antibiotics over four hours after admission to the emergency department and in most instances the delay was more than 12 hours. A total of 30 percent of the delays were justifiable – 17 percent due to diagnostic indecision and 13 percent due to recent receipt of an antibiotic at home or at another institution prior to transfer. All the other delays were unnecessary and easily correctable. In this paper the data indicate that only 5.6 percent of 3,394 patients had an adequate reason for delay in antibiotic administration. Thus a reasonable target for timely administration of antibiotics is at least 90 percent of the patient population. Originality/value The strengths of this study lie in its large number of patients, inclusiveness and real world context.
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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".