Postoperative visits by dedicated anesthesiologists in patients with elevated troponin: a retrospective cohort study evaluating postoperative care utility and early detection of complications

Background: An elevated cardiac troponin level after noncardiac surgery is associated with both morbidity and mortality. Guidelines suggest routine troponin monitoring in high-risk patients. We implemented a dedicated anesthesia team to conduct follow-up on patients with postoperative troponin elevation. We hypothesized that these visits would facilitate early detection of complications. Therefore, the aim of this study was to evaluate the effect of postoperative visits by dedicated anesthesiologists on early detection of complications and care utility. Methods: This retrospective observational study included patients aged ≥ 60 years with an elevated troponin within the first 3 days after noncardiac surgery. Troponin elevation was detected by routine biomarker monitoring. The primary outcome was early detected myocardial infarctions by the dedicated anesthesiologist. Other outcomes were overall detected complications, additional diagnostic tests and treatment advised by the anesthesiologist, consultation of another medical specialist, and advised postoperative follow-up at the outpatient cardiac clinic within 1 week after surgery. Results: Of the 811 patients, 509 (63%) received a postoperative consultation by the anesthesiologist. Anesthesiologists were involved in the early detection of 59% of all myocardial infarctions and in 12% of all complications. Besides cardiac ischemia, patients were also often diagnosed with noncardiac complications, including respiratory failure (8.9%), pneumonia (13.2%), and acute kidney injury (17.5%) within 1 week after surgery. In 75% of patients, anesthesiologists ordered additional diagnostics, most frequently existing of electrocardiograms and additional cardiac enzyme testing. Additionally, change in treatment was advised, most often a medication change, in 16% of patients. Conclusions: Standard consultation of a dedicated anesthesiologist resulted in an early detection of 59% of all myocardial infarctions and involved a change in treatment in a considerable number of patients with postoperative troponin elevation. Whether this may improve patient outcomes remains to be elucidated

Prediction models for clustered data: comparison of a random intercept and standard regression model

BACKGROUND: When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. METHODS: Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. RESULTS: The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. CONCLUSION: The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters

Autonomous patient consent for anaesthesia without preoperative consultation: a qualitative feasibility study including low-risk procedures

Background: Informed consent for anaesthesia is mandatory and requires provision of information and subsequent consent during consultation between anaesthesiologist and patient. Although information can be provided in an electronic format, it is unknown whether this a valid substitute for a consultation. We explored whether provision of digital information is equivalent to oral consultation and whether it enables patients to give electronic informed consent (e-consent) for anaesthesia. Methods: Qualitative feasibility study using semi-structured interviews in 20 low-risk adults scheduled for minor surgery under general anaesthesia or procedural sedation at a university hospital. Data were analysed using a thematic content analysis approach. During the interviews, patients followed an application that provides information and subsequent e-consenting. Results: The mean age was 50 yr and patients had good digital skills. Fifteen patients (75%) had previous experience of anaesthesia. The digital application provided enough information for all patients, but eight (40%) preferred consultation with an anaesthesiologist, mainly for personal contact. Patients had different information needs, with previous experiences leading to lower information needs. Nineteen patients had sufficient information to consent autonomously. Most patients considered separate anaesthesia consent superfluous to the surgical consent. Conclusion: The digital application provided sufficient information and patients valued the information offered and the advantage of processing information at their own pace. This information made patients feel empowered to autonomously consent to anaesthesia without consultation. Remarkably, consent for anaesthesia was considered unimportant, because patients felt they had ‘no choice’ if they wanted to undergo surgery

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

Myocardial injury after noncardiac surgery and its association with short-term mortality

Background: To identify patients at risk for postoperative myocardial injury and death, measuring cardiac troponin routinely after noncardiac surgery has been suggested. Such monitoring was implemented in our hospital. The aim of this study was to determine the predictive value of postoperative myocardial injury, as measured by troponin elevation, on 30-day mortality after noncardiac surgery. Methods and Results: This observational, single-center cohort study included 2232 consecutive intermediate- to highrisk noncardiac surgery patients aged ≥60 years who underwent surgery in 2011. Troponin was measured on the first 3 postoperative days. Log binomial regression analysis was used to estimate the association between postoperative myocardial injury (troponin I level &gt;0.06 μg/L) and all-cause 30-day mortality. Myocardial injury was found in 315 of 1627 patients in whom troponin I was measured (19%). All-cause death occurred in 56 patients (3%). The relative risk of a minor increase in troponin (0.07-0.59 μg/L) was 2.4 (95% confidence interval, 1.3-4.2; P&lt;0.01), and the relative risk of a 10- to 100-fold increase in troponin (≥0.60 μg/L) was 4.2 (95% confidence interval, 2.1-8.6; P&lt;0.01). A myocardial infarction according to the universal definition was diagnosed in 10 patients (0.6%), of whom 1 (0.06%) had ST-segment elevation myocardial infarction. Conclusions: Postoperative myocardial injury is an independent predictor of 30-day mortality after noncardiac surgery. Implementation of postoperative troponin monitoring as standard of care is feasible and may be helpful in improving the prognosis of patients undergoing noncardiac surgery.</p

Myocardial injury after noncardiac surgery and its association with short-term mortality

Background: To identify patients at risk for postoperative myocardial injury and death, measuring cardiac troponin routinely after noncardiac surgery has been suggested. Such monitoring was implemented in our hospital. The aim of this study was to determine the predictive value of postoperative myocardial injury, as measured by troponin elevation, on 30-day mortality after noncardiac surgery. Methods and Results: This observational, single-center cohort study included 2232 consecutive intermediate- to highrisk noncardiac surgery patients aged ≥60 years who underwent surgery in 2011. Troponin was measured on the first 3 postoperative days. Log binomial regression analysis was used to estimate the association between postoperative myocardial injury (troponin I level &gt;0.06 μg/L) and all-cause 30-day mortality. Myocardial injury was found in 315 of 1627 patients in whom troponin I was measured (19%). All-cause death occurred in 56 patients (3%). The relative risk of a minor increase in troponin (0.07-0.59 μg/L) was 2.4 (95% confidence interval, 1.3-4.2; P&lt;0.01), and the relative risk of a 10- to 100-fold increase in troponin (≥0.60 μg/L) was 4.2 (95% confidence interval, 2.1-8.6; P&lt;0.01). A myocardial infarction according to the universal definition was diagnosed in 10 patients (0.6%), of whom 1 (0.06%) had ST-segment elevation myocardial infarction. Conclusions: Postoperative myocardial injury is an independent predictor of 30-day mortality after noncardiac surgery. Implementation of postoperative troponin monitoring as standard of care is feasible and may be helpful in improving the prognosis of patients undergoing noncardiac surgery.</p

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

Associations between intraoperative hypotension, duration of surgery and postoperative myocardial injury after noncardiac surgery: a retrospective single-centre cohort study

Background: Studies of intraoperative hypotension typically specify a blood pressure threshold associated with adverse outcomes. Such thresholds are likely to be study-biased, investigator-biased, or both. We hypothesised that a newly developed modelling method without a threshold, which is biologically more plausible than a threshold-based approach, would reveal a continuous association between exposure to intraoperative hypotension and adverse outcomes. Methods: Single-centre, retrospective cohort study of subjects ≥60 yr old undergoing noncardiac surgery. We modelled intraoperative hypotension using three different approaches: (1) unweighted, (2) weighted for degree of hypotension (depth), and (3) weighted for duration of hypotension. The primary outcome was myocardial injury, defined as elevated troponin I (>60 ng L−1) measured during the first 3 days after surgery. The associations between the three models, postoperative myocardial injury, and mortality (secondary outcome) were reported as penalised adjusted odds ratios (ORs) scaled between the 75th and 25th percentiles. Results: Myocardial injury occurred in 1812/15 452 (12%) procedures, with 554/15 452 (3.6%) procedures resulting in death before discharge from hospital. The unweighted lower blood pressure measure (OR: 0.26, 95% confidence interval [CI]: 0.12–0.53) and the depth-weighted measure (OR: 4.4, 95% CI: 2.6–7.4) were associated with myocardial injury. The duration-weighted measure was not associated with myocardial injury (OR: 0.89, 95% CI: 0.61–1.3). The unweighted measure (OR 0.08, 95% CI: 0.01–0.40) and the depth-weighted measure (OR: 12, 95% CI, 3.8–35) were associated with in-hospital mortality, but not the duration-weighted measure (OR: 1.3, 95% CI: 0.53–3.0). Conclusions: Intraoperative hypotension appears to have a graded association with postoperative myocardial injury and mortality, with depth appearing to contribute more than duration