Patient Selection for Routine Troponin Monitoring After Noncardiac Surgery.

Background Myocardial infarction is an important complication after noncardiac surgery. Therefore, perioperative troponin surveillance is recommended for patients at risk. The aim of this study was to identify patients at high risk of perioperative myocardial infarction (POMI), in order to aid appropriate selection and to omit redundant laboratory measurements in patients at low risk. Methods and Results This observational cohort study included patients ≥60 years of age who underwent intermediate to high risk noncardiac surgery. Routine postoperative troponin I monitoring was performed. The primary outcome was POMI. Classification and regression tree analysis was used to identify patient groups with varying risks of POMI. In each subgroup, the number needed to screen to identify 1 patient with POMI was calculated. POMI occurred in 216 (4%) patients and other myocardial injury in 842 (15%) of the 5590 included patients. Classification and regression tree analysis divided patients into 14 subgroups in which the risk of POMI ranged from 1.7% to 42%. Using a risk of POMI ≥2% to select patients for routine troponin I monitoring, this monitoring would be advocated in patients ≥60 years of age undergoing emergency surgery, or those undergoing elective surgery with a Revised Cardiac Risk Index class >2 (ie >1 risk factor). The number needed to screen to detect a patient with POMI would be 14 (95% CI 14-14) and 26% of patients with POMI would be missed. Conclusions To improve selection of high-risk patients ≥60 years of age, routine postoperative troponin I monitoring could be considered in patients undergoing emergency surgery, or in patients undergoing elective surgery classified as having a revised cardiac risk index class >2.

Added value of subjective assessed functional capacity before non-cardiac surgery in predicting postoperative myocardial injury.

BACKGROUND: Functional capacity is used as an indicator for cardiac testing before non-cardiac surgery and is often performed subjectively. However, the value of subjectively estimated functional capacity in predicting cardiac complications is under debate. We determined the predictive value of subjectively assessed functional capacity on postoperative cardiac complications and mortality. DESIGN: An observational cohort study in patients aged 60 years and over undergoing elective inpatient non-cardiac surgery in a tertiary referral hospital. METHODS: Subjective functional capacity was determined by anaesthesiologists. The primary outcome was postoperative myocardial injury. Secondary outcomes were postoperative inhospital myocardial infarction and one year mortality. Logistic regression analysis and area under the receiver operating curves were used to determine the added value of functional capacity. RESULTS: A total of 4879 patients was included; 824 (17%) patients had a poor subjective functional capacity. Postoperative myocardial injury occurred in 718 patients (15%). Poor functional capacity was associated with myocardial injury (relative risk (RR) 1.7, 95% confidence interval (CI) 1.5-2.0; P < 0.001), postoperative myocardial infarction (RR 2.9, 95% CI 1.9-4.2; P < 0.001) and one year mortality (RR 1.7, 95% CI 1.4-2.0; P < 0.001). After adjustment for other predictors, functional capacity was still a significant predictor for myocardial injury (odds ratio (OR) 1.3, 95% CI 1.0-1.7; P = 0.023), postoperative myocardial infarction (OR 2.0, 95% CI 1.3-3.0; P = 0.002) and one year mortality (OR 1.4, 95% CI 1.1-1.8; P = 0.003), but had no added value on top of other predictors. CONCLUSIONS: Subjectively assessed functional capacity is a predictor of postoperative myocardial injury and death, but had no added value on top of other preoperative predictors.

Clinical and Physiological Events That Contribute to the Success Rate of Finding "Optimal" Cerebral Perfusion Pressure in Severe Brain Trauma Patients.

OBJECTIVE: Recently, a concept of an individually targeted level of cerebral perfusion pressure that aims to restore impaired cerebral vasoreactivity has been advocated after traumatic brain injury. The relationship between cerebral perfusion pressure and pressure reactivity index normally is supposed to have a U-shape with its minimum interpreted as the value of "optimal" cerebral perfusion pressure. The aim of this study is to investigate the relation between the absence of the optimal cerebral perfusion pressure curve and physiological variables, clinical factors, and interventions. DESIGN: Retrospective analysis of prospectively collected data. SETTING: Neurocritical care units in two university centers. PATIENTS: Between May 2012 and December 2013, a total of 48 traumatic brain injury patients were studied with real-time annotation of predefined clinical events. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All patients had continuous monitoring of arterial blood pressure, intracranial pressure, and cerebral perfusion pressure, with real-time calculations of pressure reactivity index and optimal cerebral perfusion pressure using ICM+ software (Cambridge Enterprise, University of Cambridge, Cambridge, UK). Selected clinical events were inserted on a daily basis, including changes in physiological variables, sedativeanalgesic drugs, vasoactive drugs, and medical/surgical therapies for intracranial hypertension. The collected data were divided into 4-hour periods, with the primary outcome being absence of the optimal cerebral perfusion pressure curve. For every period, mean values (± SDs) of arterial blood pressure, intracranial pressure, pressure reactivity index, and other physiological variables were calculated; clinical events were organized using predefined scales. In 28% of all 1,561 periods, an optimal cerebral perfusion pressure curve was absent. A generalized linear mixed model with binary logistic regression was fitted. Absence of slow arterial blood pressure waves (odds ratio, 2.7; p < 0.001), higher pressure reactivity index values (odds ratio, 2.9; p < 0.001), lower amount of sedative-analgesic drugs (odds ratio, 1.9; p = 0.03), higher vasoactive medication dose (odds ratio, 3.2; p = 0.02), no administration of maintenance neuromuscular blockers (odds ratio, 1.7; p < 0.01), and following decompressive craniectomy (odds ratio, 1.8; p < 0.01) were independently associated with optimal cerebral perfusion pressure curve absence. CONCLUSIONS: This study identified six factors that were independently associated with absence of optimal cerebral perfusion pressure curves.