Prediction of perioperative myocardial infarction/injury in high-risk patients after noncardiac surgery

• Published in: European heart journal. Acute cardiovascular care Vol. 12; no. 11; pp. 729 - 739
• Main Authors: Meister, Rebecca, Puelacher, Christian, Glarner, Noemi, Gualandro, Danielle Menosi, Andersson, Henrik A, Pargger, Mirjam, Huré, Gabrielle, Virant, Georgiana, Bolliger, Daniel, Lampart, Andreas, Steiner, Luzius, Hidvegi, Reka, Lurati Buse, Giovanna, Kindler, Christoph, Gürke, Lorenz, Mujagic, Edin, Schaeren, Stefan, Clauss, Martin, Lardinois, Didier, Hammerer-Lercher, Angelika, Chew, Michelle, Mueller, Christian
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 16-11-2023
• Subjects: Diagnostic screening programme; Troponin; Perioperative myocardial injury; Perioperative care; High-sensitivity troponin; Preoperative care; preoperative care; high-sensitivity troponin; diagnostic screening program; perioperative myocardial injury; perioperative care
• ISSN: 2048-8726; 2048-8734; 2048-8734
• DOI: 10.1093/ehjacc/zuad090

Abstract
Aims
Perioperative myocardial infarction/injury (PMI) is a surprisingly common yet difficult-to-predict cardiac complication in patients undergoing noncardiac surgery. We aimed to assess the incremental value of preoperative cardiac troponin (cTn) concentration in the prediction of PMI.
Methods and results
Among prospectively recruited patients at high cardiovascular risk (age ≥65 years or ≥45 years with preexisting cardiovascular disease), PMI was defined as an absolute increase in high-sensitivity cTnT (hs-cTnT) concentration of ≥14 ng/L (the 99th percentile) above the preoperative concentration. Perioperative myocardial infarction/injury was centrally adjudicated by two independent cardiologists using serial measurements of hs-cTnT. Using logistic regression, three models were derived: Model 1 including patient- and procedure-related information, Model 2 adding routinely available laboratory values, and Model 3 further adding preoperative hs-cTnT concentration. Models were also compared vs. preoperative hs-cTnT alone. The findings were validated in two independent cohorts. Among 6944 patients, PMI occurred in 1058 patients (15.2%). The predictive accuracy as quantified by the area under the receiver operating characteristic curve was 0.73 [95% confidence interval (CI) 0.71–0.74] for Model 1, 0.75 (95% CI 0.74–0.77) for Model 2, 0.79 (95% CI 0.77–0.80) for Model 3, and 0.74 for hs-cTnT alone. Model 3 included 10 preoperative variables: age, body mass index, known coronary artery disease, metabolic equivalent >4, risk of surgery, emergency surgery, planned duration of surgery, haemoglobin, platelet count, and hs-cTnT. These findings were confirmed in both independent validation cohorts (n = 722 and n = 966).
Conclusion
Preoperative cTn adds incremental value above patient- and procedure-related variables as well as routine laboratory variables in the prediction of PMI.
Graphical Abstract
Graphical Abstract
ASA, American society of anesthesiology; AUC, area under the receiver operating characteristics curve; Hb, haemoglobin; Na, potassium; RCRI, revised cardiac risk index