1788. Cost-Effectiveness of Penicillin Skin Testing Among Patients With Methicillin-Sensitive <i>Staphylococcus aureus</i> Bacteremia and Reported Penicillin Allergy
Bibliographic record
Abstract
Methicillin sensitive Staphylococcus aureus (MSSA) bacteremia is a highly lethal infection; first-line therapy with a β-lactam, commonly cefazolin, provides a significant mortality benefit over the second-line therapy, vancomycin, which is often used in patients reporting β-lactam allergy. We designed a simulation model of inpatients aged 55–75 years with MSSA bacteremia and a self-reported history of β-lactam allergy. The model adopted a US health-system perspective, a lifetime horizon, and a willingness-to-pay threshold of $100,000 per quality-adjusted life year (QALY). We compared routine care (vancomycin), history screening (questionnaire assessing anaphylaxis history), and bedside penicillin skin testing. Incremental cost-effectiveness ratio (ICER) was measured using 2017 US dollars per QALY. Baseline co-morbid states (diabetes, malignancy, and end-stage renal disease [ESRD] requiring dialysis) were also modeled. Future costs and benefits were discounted at 3% per year. Among patients with MSSA bacteremia and a self-reported penicillin allergy, skin testing produced the best clinical outcomes and was cost-effective relative to history screening, generating 0.51 additional QALYs at an ICER of $22,062 per QALY gained. Among patients with diabetes, malignancy, or ESRD, the ICER for skin testing relative to history screening increased to $30,830–$127,182, reflecting the overall lower life expectancy and high annual survivor healthcare cost in these higher risk groups. Results were robust to wide variations in the cost and diagnostic performance of skin testing: in sensitivity analyses, skin testing remained the optimal strategy when cost was <$5600, specificity >60%, and sensitivity >10%. Among adults with MSSA bacteremia and a self-reported β-lactam allergy, skin testing is cost-effective relative to history screening and routine care at conventional willingness-to-pay thresholds and should be widely adopted given the mortality benefit of β-lactams over alternate antibiotics in MSSA bacteremia. All authors: No reported disclosures.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.018 | 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".