Impact of Reported Beta-Lactam Allergy on Inpatient Outcomes: A Multicenter Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Reported allergy to beta-lactam antibiotics is common and often leads to unnecessary avoidance in patients who could tolerate these antibiotics. We prospectively evaluated the impact of these reported allergies on clinical outcomes. METHODS: We conducted a trainee-led prospective cohort study to determine the burden and clinical impact of reported beta-lactam allergy on patients seen by infectious diseases consultation services at 3 academic hospitals. The primary outcome was a composite measure of readmission for the same infection, acute kidney injury, Clostridium difficile infection, or drug-related adverse reactions requiring discontinuation. Predictors of interest were history of beta-lactam allergy and receipt of preferred beta-lactam therapy. RESULTS: Among 507 patients, 95 (19%) reported beta-lactam allergy; preferred therapy was a beta-lactam in 72 (76%). When beta-lactam therapy was preferred, 25 (35%) did not receive preferred therapy due to their report of allergy even though 13 (52%) reported non-severe prior reactions. After adjustment for confounders, patients who did not receive preferred beta-lactam therapy were at greater risk of adverse events (adjusted odds ratio [aOR], 3.1; 95% confidence interval [CI], 1.28-7.89) compared with those without reported allergy. In contrast, patients who received preferred beta-lactam therapy had a similar risk of adverse events compared with patients not reporting allergy (aOR, 1.33; 95% CI, .62-2.87). CONCLUSIONS: Avoidance of preferred beta-lactam therapy in patients who report allergy is associated with an increased risk of adverse events. Development of inpatient programs aimed at accurately identifying beta-lactam allergies to safely promote beta-lactam administration among these patients is warranted.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".