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The incidence of myocardial injury after non-cardiac surgery (MINS) is approximately 12-15% and is associated with an increased risk of 30-day mortality, 1-year mortality, and 2-year major vascular events. Using both traditional longitudinal analysis techniques and novel methods in machine learning, investigators will explore whether intraoperative and postoperative vital signs can enhance MINS surveillance by providing temporal prediction of MINS events.
Full description
The incidence of myocardial injury after non-cardiac surgery (MINS) is approximately 12-15% and is associated with an increased risk of 30-day mortality, 1-year mortality, and 2-year major vascular events. Since more than 90% of patients with MINS are asymptomatic, routine troponin monitoring is required for detection. The postoperative days 0, 1, and 2 accounts for approximately 40%, 40%, and 10% of MINS, respectively. Presently, the Canadian Cardiovascular Society (CCS) perioperative guidelines recommend patients identified to be at risk according to the Revised Cardiac Risk Index (RCRI) and BNP/NT-pro B-type Natriuretic Peptide (NT-pro BNP) receive daily postoperative troponin monitoring for three days to identify MINS events (5). European and American societies have similar recommendations for troponin monitoring to detect MINS.
Current risk stratification models have multiple limitations. Most importantly, they predict an elevated risk over the postoperative period but cannot pinpoint when MINS may happen in the postoperative course given the patients' changing condition. Moreover, prescription of troponin monitoring is not universal, infrequent and inconsistent troponin monitoring may lead to delayed detection and management, and the rise of troponin is delayed by 3-4 hours from the time of injury.
Retrospective cohort studies show association amongst intraoperative and postoperative derangements in vital signs and MINS. Vital signs are routinely available within the electronic medical record, and may serve as objective predictors (i.e. as opposed to free text and disease names that have higher risks of misclassification and errors).
Using both traditional longitudinal analysis techniques and novel methods in machine learning, investigators will explore whether intraoperative and postoperative vital signs can enhance MINS surveillance by providing temporal prediction of MINS events.
Objectives
Preoperative laboratory values are collected within 30 days before surgery. Preoperative vitals are collected within 24 hours before surgery. The total duration of subsequent data collection will be from the time of surgery up to postoperative day 3 (since the MINS protocol monitors for 3 days) or hospital discharge or death, whichever occurs first. Since 90% of MINS happen between postoperative days zero and two and the frequency of monitoring would likely decrease by postoperative day 3, investigators will model troponin from postoperative day 0 to postoperative day 2 for the primary analysis to balance utility of the temporal model and prediction data quality.
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750 participants in 1 patient group
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