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Penicillin allergy as an instrumental variable for estimating antibiotic effects on resistance

Author

Listed:
  • Yaki Saciuk

    (Faculty of Medical & Health Sciences Tel Aviv University)

  • Daniel Nevo

    (Tel Aviv University)

  • Michal Chowers

    (Tel Aviv University
    Meir Medical Center)

  • Uri Obolski

    (Faculty of Medical & Health Sciences Tel Aviv University)

Abstract

Antibiotic resistance is influenced by prior antibiotic use, but precise causal estimates are limited. This study uses penicillin allergy as an instrumental variable (IV) to estimate the causal effect of antibiotics on resistance. A retrospective cohort of 36,351 individuals with E. coli positive urine cultures and prior outpatient antibiotic use, with outcomes assessed up to one year post-exposure, was analyzed using data from Maccabi Healthcare Services (MHS), the second-largest non-profit health fund in Israel. IV methods estimated risk differences (RD) and numbers needed to harm (NNH) for penicillin versus other antibiotics. The RD for resistance was 11.4% (95% CI: 7.6%, 15.4%) for amoxicillin/clavulanic acid, 14.1% (95% CI: 9.0%, 19.4%) for ampicillin, and 0.8% (95% CI: 0.2%, 1.4%) for piperacillin/tazobactam, with NNHs of 8.8, 7.1, and 122.0, respectively. Risks declined over time since exposure. Gentamicin, used as a negative control, showed no effect (95% CI: −2.4%, 1.8%). When directly comparing penicillin and quinolone effects on their respective AMR, penicillin use within 180 days increased resistance to amoxicillin/clavulanic acid by an RD of 17.8% (95% CI: 2.1%, 35.2%; NNH: 5.6), while quinolones raised ciprofloxacin resistance by 43.9% (95% CI: 29.9%, 59.4%; NNH: 2.3). These findings provide quantitative evidence of the impact of prior penicillin use on resistance, with implications for clinical practice and prescription policies.

Suggested Citation

  • Yaki Saciuk & Daniel Nevo & Michal Chowers & Uri Obolski, 2025. "Penicillin allergy as an instrumental variable for estimating antibiotic effects on resistance," Nature Communications, Nature, vol. 16(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56287-x
    DOI: 10.1038/s41467-025-56287-x
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    References listed on IDEAS

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    2. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    3. Ben B. Hansen, 2004. "Full Matching in an Observational Study of Coaching for the SAT," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 609-618, January.
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