Postoperative troponin surveillance to detect myocardial infarction: an observational cohort modelling study.

myocardial infarction myocardial injury noncardiac surgery postoperative surveillance troponin

Journal

British journal of anaesthesia
ISSN: 1471-6771
Titre abrégé: Br J Anaesth
Pays: England
ID NLM: 0372541

Informations de publication

Date de publication:
16 Jan 2024
Historique:
received: 16 10 2023
revised: 29 11 2023
accepted: 18 12 2023
medline: 18 1 2024
pubmed: 18 1 2024
entrez: 17 1 2024
Statut: aheadofprint

Résumé

Clinical presentation of postoperative myocardial infarction (POMI) is often silent. Several international guidelines recommend routine troponin surveillance in patients at risk. We compared how these different guidelines select patients for surveillance after noncardiac surgery with our established risk stratification model. We used outcome data from two prospective studies: Measurement of Exercise Tolerance before Surgery (METS) and Troponin Elevation After Major non-cardiac Surgery (TEAMS). We compared the major American, Canadian, and European guideline recommendations for troponin surveillance with our established risk stratification model. For each guideline and model, we quantified the number of patients requiring monitoring, % POMI detected, sensitivity, specificity, diagnostic odds ratio, and number needed to screen (NNS). METS and TEAMS contributed 2350 patients, of whom 319 (14%) had myocardial injury, 61 (2.5%) developed POMI, and 14 (0.6%) died. Our risk stratification model selected fewer patients for troponin monitoring (20%), compared with the Canadian (78%) and European (79%) guidelines. The sensitivity to detect POMI was highest with the Canadian and European guidelines (0.85; 95% confidence interval [CI] 0.74-0.92). Specificity was highest using the American guidelines (0.91; 95% CI 0.90-0.92). Our risk stratification model had the best diagnostic odds ratio (2.5; 95% CI 1.4-4.2) and a lower NNS (21 vs 35) compared with the guidelines. Most postoperative myocardial infarctions were detected by the Canadian and European guidelines but at the cost of low specificity and a higher number of patients undergoing screening. Patient selection based on our risk stratification model was optimal.

Sections du résumé

BACKGROUND BACKGROUND
Clinical presentation of postoperative myocardial infarction (POMI) is often silent. Several international guidelines recommend routine troponin surveillance in patients at risk. We compared how these different guidelines select patients for surveillance after noncardiac surgery with our established risk stratification model.
METHODS METHODS
We used outcome data from two prospective studies: Measurement of Exercise Tolerance before Surgery (METS) and Troponin Elevation After Major non-cardiac Surgery (TEAMS). We compared the major American, Canadian, and European guideline recommendations for troponin surveillance with our established risk stratification model. For each guideline and model, we quantified the number of patients requiring monitoring, % POMI detected, sensitivity, specificity, diagnostic odds ratio, and number needed to screen (NNS).
RESULTS RESULTS
METS and TEAMS contributed 2350 patients, of whom 319 (14%) had myocardial injury, 61 (2.5%) developed POMI, and 14 (0.6%) died. Our risk stratification model selected fewer patients for troponin monitoring (20%), compared with the Canadian (78%) and European (79%) guidelines. The sensitivity to detect POMI was highest with the Canadian and European guidelines (0.85; 95% confidence interval [CI] 0.74-0.92). Specificity was highest using the American guidelines (0.91; 95% CI 0.90-0.92). Our risk stratification model had the best diagnostic odds ratio (2.5; 95% CI 1.4-4.2) and a lower NNS (21 vs 35) compared with the guidelines.
CONCLUSIONS CONCLUSIONS
Most postoperative myocardial infarctions were detected by the Canadian and European guidelines but at the cost of low specificity and a higher number of patients undergoing screening. Patient selection based on our risk stratification model was optimal.

Identifiants

DOI: 10.1016/j.bja.2023.12.019 PMID: 38233301
pubmed: 38233301
pii: S0007-0912(23)00736-5
doi: 10.1016/j.bja.2023.12.019
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.

Auteurs

Selene Martinez-Perez (S)

Department of Anesthesiology and Pain Management, Toronto General Hospital/University Health Network Toronto, Toronto, ON, Canada.

Judith A R van Waes (JAR)

Department of Anesthesiology, Intensive Care and Emergency Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.

Lisette M Vernooij (LM)

Department of Anesthesiology, Intensive Care and Emergency Medicine, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Anesthesiology, Intensive Care and Pain Medicine, St. Antonius Hospital, Nieuwegein, The Netherlands.

Brian H Cuthbertson (BH)

Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; Department of Anesthesiology and Pain Medicine, University of Toronto, Toronto, ON, Canada.

W Scott Beattie (WS)

Department of Anesthesiology and Pain Management, Toronto General Hospital/University Health Network Toronto, Toronto, ON, Canada; Department of Anesthesiology and Pain Medicine, University of Toronto, Toronto, ON, Canada.

Duminda N Wijeysundera (DN)

Department of Anesthesiology and Pain Medicine, University of Toronto, Toronto, ON, Canada; Department of Anesthesiology, St. Michael's Hospital, Toronto, ON, Canada.

Wilton A van Klei (WA)

Department of Anesthesiology and Pain Management, Toronto General Hospital/University Health Network Toronto, Toronto, ON, Canada; Department of Anesthesiology, Intensive Care and Emergency Medicine, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Anesthesiology and Pain Medicine, University of Toronto, Toronto, ON, Canada. Electronic address: wilton.vanklei@uhn.ca.

Classifications MeSH