Antibiotic use among older adults on an acute care general surgery service
Bibliographic record
Abstract
BACKGROUND: Antibiotics play an important role in the treatment of many surgical diseases that affect older adults, and the potential for inappropriate use of these drugs is high. Our objective was to describe antibiotic use among older adults admitted to an acute care surgery service at a tertiary care teaching hospital. METHODS: Detailed data regarding diagnosis, comorbidities, surgery and antibiotic use were retrospectively collected for patients 70 years and older admitted to an acute care surgery service. We evaluated antibiotic use (perioperative prophylaxis and treatment) for appropriateness based on published guidelines. RESULTS: During the study period 453 patients were admitted to the acute care surgery service, and 229 underwent surgery. The most common diagnoses were small bowel obstruction (27.2%) and acute cholecystitis (11.0%). In total 251 nonelective abdominal operations were performed, and perioperative antibiotic prophylaxis was appropriate in 49.5% of cases. The most common prophylaxis errors were incorrect timing (15.5%) and incorrect dose (12.4%). Overall 206 patients received treatment with antibiotics for their underlying disease process, and 44.2% received appropriate first-line drug therapy. The most common therapeutic errors were administration of second- or third-line antibiotics without indication (37.9%) and use of antibiotics when not indicated (12.1%). There was considerable variation in the duration of treatment for patients with the same diagnoses. CONCLUSION: Inappropriate antibiotic use was common among older patients admitted to an acute care surgery service. Quality improvement initiatives are needed to ensure patients receive optimal care in this complex hospital environment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".