Search

Background: The accurate diagnosis of heart failure (HF) before major noncardiac surgery is frequently challenging. The impact of diagnostic accuracy for HF on intraoperative practice patterns and clinical outcomes remains unknown., Methods: We performed an observational study of adult patients undergoing major noncardiac surgery at an academic hospital from 2015 to 2019. A preoperative clinical diagnosis of HF was defined by keywords in the preoperative assessment or a diagnosis code. Medical records of patients with and without HF clinical diagnoses were reviewed by a multispecialty panel of physician experts to develop an adjudicated HF reference standard. The exposure of interest was an adjudicated diagnosis of heart failure. The primary outcome was volume of intraoperative fluid administered. The secondary outcome was postoperative acute kidney injury (AKI)., Results: From 40 659 surgeries, a stratified subsample of 1018 patients were reviewed by a physician panel. Among patients with adjudicated diagnoses of HF, those without a clinical diagnosis (false negatives) more commonly had preserved left ventricular ejection fractions and fewer comorbidities. Compared with false negatives, an accurate diagnosis of HF (true positives) was associated with 470 ml (95% confidence interval: 120-830; P=0.009) lower intraoperative fluid administration and lower risk of AKI (adjusted odds ratio:0.39, 95% confidence interval 0.18-0.89). For patients without adjudicated diagnoses of HF, non-HF was not associated with differences in either fluids administered or AKI., Conclusions: An accurate preoperative diagnosis of heart failure before noncardiac surgery is associated with reduced intraoperative fluid administration and less acute kidney injury. Targeted efforts to improve preoperative diagnostic accuracy for heart failure may improve perioperative outcomes., (Published by Elsevier Ltd.)

Background: Postoperative nausea and vomiting (PONV) is a key driver of unplanned admission and patient satisfaction following surgery. Because traditional risk factors do not completely explain variability in risk, we hypothesize that genetics may contribute to the overall risk for this complication. The objective of this research is to perform a genome-wide association study of PONV, derive a polygenic risk score for PONV, assess associations between the risk score and PONV in a validation cohort, and compare any genetic contributions to known clinical risks for PONV., Methods: Surgeries with integrated genetic and perioperative data performed under general anesthesia at Michigan Medicine and Vanderbilt University Medical Center were studied. PONV was defined as nausea or emesis occurring and documented in the PACU. In the Discovery Phase, genome-wide association studies were performed on each genetic cohort and the results were meta-analyzed. Next, in the Polygenic Phase, we assessed whether a polygenic score, derived from genome-wide association study in a derivation cohort from Vanderbilt University Medical Center, improved prediction within a validation cohort from Michigan Medicine, as quantified by discrimination (C-statistic) and net reclassification index., Results: Of 64,523 total patients, 5,703 developed PONV (8.8%). We identified 46 genetic variants exceeding P<1x10-5 threshold, occurring with minor allele frequency > 1%, and demonstrating concordant effects in both cohorts. Standardized polygenic score was associated with PONV in a basic model, controlling for age and sex, (aOR 1.027 per standard deviation increase in overall genetic risk, 95% CI 1.001-1.053, P=0.044), a model based on known clinical risks (aOR 1.029, 95% CI 1.003-1.055, P=0.030), and a full clinical regression, controlling for 21 demographic, surgical, and anesthetic factors, (aOR 1.029, 95% CI 1.002-1.056, P=0.033). The addition of polygenic score improved overall discrimination in models based on known clinical risk factors (c-statistic: 0.616 compared to 0.613, P=0.028) and improved net reclassification of 4.6% of cases., Conclusion: Standardized polygenic risk was associated with PONV in all three of our models, but the genetic influence was smaller than exerted by clinical risk factors. Specifically, a patient with a polygenic risk score > 1 standard deviation above the mean, has 2-3% greater odds of developing PONV when compared to the baseline population, which is at least an order of magnitude smaller than the increase associated with having prior PONV/motion sickness (55%), having a history of migraines (17%), or being female (83%), and is not clinically significant. Furthermore, the use of a polygenic risk score does not meaningfully improve discrimination compared to clinical risk factors and is not clinically useful., Competing Interests: Declarations of Interest: CD is a consultant to Exact Sciences and founder of Belay Diagnostics is compensated with income and equity. Exact Sciences is a molecular diagnostics company specializing in the detection of early-stage cancers. Belay Diagnostic is a platform for the detection of brain and spinal cord cancers using cerebrospinal fluid. The companies named above as well as other companies have licensed previously described technologies. Licenses to these technologies are or will be associated with equity or royalty payments to the inventors as well as Johns Hopkins University. The terms of all of these arrangements are being managed by Johns Hopkins in accordance with its conflict-of-interest policies. CD’s involvement with both companies is unrelated to the scope of the research presented in this manuscript. CJW is currently employed by Regeneron Pharmaceuticals Inc and holds stock and options. KHW is currently employed by Regeneron Pharmaceutical Inc. MM received funding paid to the University of Michigan from Chiesi USA for work unrelated to the scope of the research presented in this manuscript., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Society of Anesthesiologists.)