BACKGROUND: Instrumental variable (IV) analysis is a statistical method allowing causal inference under certain assumptions. A recent high-profile IV analysis suggested cefepime was superior to piperacillin-tazobactam in treating sepsis. This study used a worldwide piperacillin-tazobactam shortage as an IV to infer mortality effects. However, this result starkly contrasts with the well-powered ACORN trial, which showed no effect. We discuss important limitations of the IV study, potentially explaining this discrepancy. METHODS: We used causal diagrams and the potential outcomes framework to describe potential biases. We identified 2 sources: (1) statistical adjustment for metronidazole treatment, leading to collider bias, and (2) operationalization of the treatment variable (exposure coarsening). We performed simulations demonstrating collider bias can explain the results. Finally, we used summary data from the original paper to obtain alternative causal estimates robust to these biases. RESULTS: Adjusting for metronidazole, a choice influenced by both the IV (via initial antibiotic) and underlying factors such as disease severity, induces collider bias. Analyses not adjusting for metronidazole show no strong evidence for a mortality difference. However, bias risk from exposure coarsening remains even without adjustment. Re-analyzing summary data provides no compelling evidence for a benefit of cefepime over piperacillin-tazobactam. CONCLUSIONS: The recent IV analysis does not support a mortality benefit for cefepime; results appear dependent on incorrect analytical choices introducing bias. Clinicians should be aware of IV analysis complexities and assumptions when making causal inferences from observational data, especially when results contradict high-quality trials and antibiotic choice is the exposure.
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Hamilton et al. (2025) studied this question.
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