Anesthesiology · University of Illinois at Chicago

Michael R. Fettiplace,
MD, PhD

Identification, prevention and treatment of adverse events from local anesthetics.

I am a clinician scientist interested in safety and efficacy within anesthesia, with a specific focus on local anesthetics. I study the identification, prevention and treatment of adverse events from local anesthetics — from signal detection in national and global adverse-event databases, through the dosing limits that determine whether toxicity occurs at all, to the evidence behind the treatments given when it does.

Michael R. Fettiplace

01 Pharmacovigilance

Finding the harm

Randomized trials are not powered to detect the rare catastrophes that define the safety of local anesthetics and other anesthetic drugs. Therefore we need to turn to case reports and large databases in order to identify such events. We use systematic methods to evaluate such rare events including systematic reviews of case reports and disproportionality methods. We have previously interrogated the FDA Adverse Event Reporting System, the WHO VigiBase database and the National Poison Data System in order to identify signals of anesthetic drug induced morbidity and mortality.

We have previously evaluated local anesthetics' contribution to mortality and identified associations with high-dose lidocaine, neuraxial methods and ropivacaine catheters. Second, we have recently identified novel sources of cardiac arrest associated with anesthetic agents with signals for sugammadex, sevoflurane, dexmedetomidine and remifentanil.

Forest plot of reporting odds ratios for cardiac arrest by anesthetic drug class. Reversal agents 2.00, paralytics 1.37 and volatile agents 1.25 sit above 1.0; IV anesthetics 0.90, amide-linked local anesthetics 0.64, ester-linked local anesthetics 0.41, opioids 0.33 and anti-emetics 0.19 sit below.
Class-level reporting odds ratio of cardiac arrest in VigiBase. Data from Perez & Fettiplace, Br J Anaesth 2026.

    02 Toxicity & dosing

    Preventing it

    The familiar milligram per patient ceilings for bupivacaine and ropivacaine derived from single-injection techniques studied decades ago. Modern practice looks nothing like that: large-volume fascial plane blocks, bilateral truncal catheters running for days, and combinations layered on top of surgical infiltration. Applied to those techniques the old ceilings are simultaneously too permissive in some situations and needlessly restrictive in others.

    This work reconstructs dosing guidance from what is known about absorption, accumulation and clearance — cataloguing published adult and pediatric truncal catheter practice, comparing the methods available for predicting safe redosing, and examining weight-based scaling in the blocks where it most often goes wrong. The output is meant to be usable at the bedside to prevent dose-based adverse events. It is also the evidence base that practice advisories on systemic toxicity draw from.

    Schematic line chart: cumulative local anesthetic dose from a continuous catheter rises over 24 hours toward the conventional single-injection ceiling, with a shaded band showing the plausible range across elimination rates.
    Schematic. Cumulative dose from a continuous catheter approaches the conventional 24-hour ceiling well within a single day; where it lands depends on elimination rate, which varies widely between patients.

      03 Lipid emulsion

      How well does it work?

      Intravenous lipid emulsion is part of the treatment regimen for local anesthetic systemic toxicity, and is given widely for other lipophilic drug overdoses. My PhD work began evaluating the mechanism by which lipid reverses bupivacaine induced cardiac toxicity. Since then I have broadened the quesion to understand what the cumulative evidence says: how well does it work and what toxicities may benefit from treatment with lipid emulsion.

      The answer depends on what you pool. Our recent 2026 systematic review and meta-analysis of lipid emulsion for non-local-anesthetic poisoning found the benefit was agent-dependent with many low-quality studies contributing to the conclusions. Earlier meta-analytic work established a survival benefit in animal models of local anesthetic toxicity, but a subsequent systematic review of that same literature documented substantial heterogeneity and risk of bias — small studies, inconsistent controls, and experimental models poorly matched to the clinical question. Efficacy claims are only as good as the experiments underneath them, and a large part of this work is holding that literature to a proper standard.

      Schematic forest plot of a meta-analysis: individual study estimates with confidence intervals sized by weight, summarised by a pooled diamond favouring lipid emulsion but with an interval running close to no effect.
      Schematic. Pooling small, heterogeneous studies produces a summary estimate whose confidence interval carries the uncertainty of its inputs.

        04 Artificial intelligence

        Disclosure standards

        Large language models entered medical writing faster than the norms governing them. Authors, reviewers and editors are all now using them, often without a shared understanding of what must be declared. Blanket prohibitions are unenforceable; blanket permissiveness erodes accountability for what appears in the literature.

        I have used modified Delphi methodology — first within the Regional Anesthesia & Pain Medicine community, then across the editors-in-chief of anaesthesia and pain medicine journals internationally — to converge on what should be disclosed, by whom, and in what form. The recommendations separate uses that require declaration from those that do not, and place responsibility for verification squarely with the human author.

        Disclosure framework for AI use in scientific writing: where to declare it (submission system and methods), what to declare (software model and version, publisher and location, date used), and nine categories of use requiring detail.
        The disclosure framework, condensed. From Fettiplace et al., Reg Anesth Pain Med 2026.

          Contact

          Get in touch

          Collaborations on pharmacovigilance, dosing and guideline work are welcome, as are residents and students looking for a research project.

          Email

          michael@fettiplace.net

          Department

          Anesthesiology
          University of Illinois at Chicago
          College of Medicine

          Full publication list

          PubMed
          Google Scholar