Maxim A. Terekhov

Nondepolarizing Neuromuscular Blocking Agents, Reversal, and Risk of Postoperative Pneumonia.

Background:Residual postoperative paralysis from nondepolarizing neuromuscular blocking agents (NMBAs) is a known problem. This paralysis has been associated with impaired respiratory function, but the clinical significance remains unclear. The aims of this analysis were two-fold: (1) to investigate if intermediate-acting NMBA use during surgery is associated with postoperative pneumonia and (2) to investigate if nonreversal of NMBAs is associated with postoperative pneumonia. Methods:Surgical cases (n = 13,100) from the Vanderbilt University Medical Center National Surgical Quality Improvement Program database who received general anesthesia were included. The authors compared 1,455 surgical cases who received an intermediate-acting nondepolarizing NMBA to 1,455 propensity score–matched cases who did not and 1,320 surgical cases who received an NMBA and reversal with neostigmine to 1,320 propensity score–matched cases who did not receive reversal. Postoperative pneumonia incidence rate ratios (IRRs) and bootstrapped 95% CIs were calculated. Results:Patients receiving an NMBA had a higher absolute incidence rate of postoperative pneumonia (9.00 vs. 5.22 per 10,000 person-days at risk), and the IRR was statistically significant (1.79; 95% bootstrapped CI, 1.08 to 3.07). Among surgical cases who received an NMBA, cases who were not reversed were 2.26 times as likely to develop pneumonia after surgery compared to cases who received reversal with neostigmine (IRR, 2.26; 95% bootstrapped CI, 1.65 to 3.03). Conclusions:Intraoperative use of intermediate nondepolarizing NMBAs is associated with developing pneumonia after surgery. Among patients who receive these agents, nonreversal is associated with an increased risk of postoperative pneumonia.

A Perioperative Systems Design to Improve Intraoperative Glucose Monitoring Is Associated with a Reduction in Surgical Site Infections in a Diabetic Patient Population

Background: Diabetic patients receiving insulin should have periodic intraoperative glucose measurement. The authors conducted a care redesign effort to improve intraoperative glucose monitoring. Methods: With approval from Vanderbilt University Human Research Protection Program (Nashville, Tennessee), the authors created an automatic system to identify diabetic patients, detect insulin administration, check for recent glucose measurement, and remind clinicians to check intraoperative glucose. Interrupted time series and propensity score matching were used to quantify pre- and postintervention impact on outcomes. Chi-square/likelihood ratio tests were used to compare surgical site infections at patient follow-up. Results: The authors analyzed 15,895 cases (3,994 preintervention and 11,901 postintervention; similar patient characteristics between groups). Intraoperative glucose monitoring rose from 61.6 to 87.3% in cases after intervention (P = 0.0001). Recovery room entry hyperglycemia (fraction of initial postoperative glucose readings greater than 250) fell from 11.0 to 7.2% after intervention (P = 0.0019), while hypoglycemia (fraction of initial postoperative glucose readings less than 75) was unchanged (0.6 vs. 0.9%; P = 0.2155). Eighty-seven percent of patients had follow-up care. After intervention the unadjusted surgical site infection rate fell from 1.5 to 1.0% (P = 0.0061), a 55.4% relative risk reduction. Interrupted time series analysis confirmed a statistically significant surgical site infection rate reduction (P = 0.01). Propensity score matching to adjust for confounders generated a cohort of 7,604 well-matched patients and confirmed a statistically significant surgical site infection rate reduction (P = 0.02). Conclusions: Anesthesiologists add healthcare value by improving perioperative systems. The authors leveraged the one-time cost of programming to improve reliability of intraoperative glucose management and observed improved glucose monitoring, increased insulin administration, reduced recovery room hyperglycemia, and fewer surgical site infections. Their analysis is limited by its applied quasiexperimental design.

Intraoperative Care Transitions Are Not Associated with Postoperative Adverse Outcomes

Background:Whether anesthesia care transitions and provision of short breaks affect patient outcomes remains unclear. Methods:The authors determined the number of anesthesia handovers and breaks during each case for adults admitted between 2005 and 2014, along with age, sex, race, American Society of Anesthesiologists physical status, start time and duration of surgery, and diagnosis and procedure codes. The authors defined a collapsed composite of in-hospital mortality and major morbidities based on primary and secondary diagnoses. The relationship between the total number of anesthesia handovers during a case and the collapsed composite outcome was assessed with a multivariable logistic regression. The relationship between the total number of anesthesia handovers during a case and the components of the composite outcome was assessed using multivariate generalized estimating equation methods. Additionally, the authors analyzed major complications and/or death within 30 days of surgery based on the American College of Surgeons National Surgical Quality Improvement Program–defined events. Results:A total of 140,754 anesthetics were identified for the primary analysis. The number of anesthesia handovers was not found to be associated (P = 0.19) with increased odds of postoperative mortality and serious complications, as measured by the collapsed composite, with odds ratio for a one unit increase in handovers of 0.957; 95% CI, 0.895 to 1.022, when controlled for potential confounding variables. A total of 8,404 anesthetics were identified for the NSQIP analysis (collapsed composite odds ratio, 0.868; 95% CI, 0.718 to 1.049 for handovers). Conclusions:In the analysis of intraoperative handovers, anesthesia care transitions were not associated with an increased risk of postoperative adverse outcomes.

Preoperative Surgical Risk Predictions Are Not Meaningfully Improved by Including the Surgical Apgar Score: An Analysis of the Risk Quantification Index and Present-On-Admission Risk Models.

Background: Estimating surgical risk is critical for perioperative decision making and risk stratification. Current risk-adjustment measures do not integrate dynamic clinical parameters along with baseline patient characteristics, which may allow a more accurate prediction of surgical risk. The goal of this study was to determine whether the preoperative Risk Quantification Index (RQI) and Present-On-Admission Risk (POARisk) models would be improved by including the intraoperative Surgical Apgar Score (SAS). Methods: The authors identified adult patients admitted after noncardiac surgery. The RQI and POARisk were calculated using published methodologies, and model performance was compared with and without the SAS. Relative quality was measured using Akaike and Bayesian information criteria. Calibration was compared by the Brier score. Discrimination was compared by the area under the receiver operating curves (AUROCs) using a bootstrapping procedure for bias correction. Results: SAS alone was a statistically significant predictor of both 30-day mortality and in-hospital mortality (P < 0.0001). The RQI had excellent discrimination with an AUROC of 0.8433, which increased to 0.8529 with the addition of the SAS. The POARisk had excellent discrimination with an AUROC of 0.8608, which increased to 0.8645 by including the SAS. Similarly, overall performance and relative quality increased. Conclusions: While AUROC values increased, the RQI and POARisk preoperative risk models were not meaningfully improved by adding intraoperative risk using the SAS. In addition to the estimated blood loss, lowest heart rate, and lowest mean arterial pressure, other dynamic clinical parameters from the patient’s intraoperative course may need to be combined with procedural risk estimate models to improve risk stratification.

Compliance is Contagious: Using Informatics Methods to Measure the Spread of a Documentation Standard From a Preoperative Clinic

Purpose: Preoperative documentation is essential to coordinated care and has the potential for standardization, which may facilitate downstream clinical management. Design: An observational pre/post standardization design was used. Methods: We analyzed the implementation of a preoperative documentation standardization intervention in Vanderbilts Preoperative Evaluation Clinic (VPEC) and its impact outside VPEC. A phased intervention consisted of clinician education with monthly feedback, followed by the development of a compliance dashboard and inclusion in Ongoing Professional Performance Evaluation system by VPEC. A follow‐up survey was administered to measure the impact on clinical management. Findings: Adherence to standardization was improved with the addition of electronic feedback. Implementation of this system in the preoperative clinic had significant impact outside VPEC. Trainee status was a significant predictor of adoption of the standardized format. Conclusions: Adoption of a preoperative documentation standard in a clinic had a positive impact on standardization practices in a perioperative system.

Electronically self-assessed functional capacity and exercise testing: A comparison of the Duke Activity Status Index and Patient-Reported Outcomes Measurement Information System tools

Purpose Electronic screening tools, such as Patient‐Reported Outcomes Measurement Information System (PROMIS) Physical Function Short‐Form 12a (PF‐SF12a), may aid in the assessment of functional capacity. However, PROMIS PF‐SF12a has not been validated against exercise capacity, or compared with established questionnaires, including the Duke Activity Status Index (DASI). We compared the DASI and PROMIS PF‐SF12a to the maximum metabolic equivalents (METs) achieved during exercise stress testing. Methods DASI and PROMIS PF‐SF12a were electronically administered to 100 adult patients (median age 56 years, 61% male) immediately before exercise stress testing. DASI‐predicted METs and PROMIS T score were calculated. Correlations with exercise METs with and without age adjustment were examined. Linear regression lines were derived and adjusted r2 statistic was calculated. We compared models with the Davidson‐Mackinnon J test. Results The median (interquartile range) DASI‐predicted METs, PROMIS Tscore, and exercise METs were 8.97 (7.61‐9.89), 47.90 (43.33‐52.40), and 10.10 (10.10‐12.80), respectively. In unadjusted correlation analyses, PROMIS accounted for 26% of the variance in exercise METs compared with 38% with DASI. With age adjustment, the r2values increased to 0.36 (PROMIS) and 0.46 (DASI). In both unadjusted and age‐adjusted analyses, inclusion of DASI improved prediction of exercise METs beyond PROMIS T score (P < .0001). In contrast, PROMIS T score did not improve exercise MET prediction compared with DASI alone (P > .10). Conclusion Among patients undergoing clinically indicated exercise stress testing, DASI outperformed PROMIS PF‐SF12a as a predictor of exercise METs.

Estimating virtual neck circumference for preoperative STOP-BANG assessment: a retrospective cohort study.

To the Editor, Obstructive sleep apnea (OSA) is associated with increased perioperative morbidity and mortality, and moderate-severe OSA remains undiagnosed in up to 82% of males and 92% of females. Risk for OSA is commonly assessed using the STOP-BANG tool, which requires a measurement of neck circumference. There is currently no established method to assess patient neck circumference virtually (i.e., via electronic communication). With increasing numbers of patients having access to techn ology, telemedicine may be able to replace conventional on-site preoperative clinic assessments with convenient and cost-effective virtual patient assessments. Therefore, we investigated using estimates of neck circumference, derived virtually from previously collected photographs, to replace the traditional preoperative clinic measurements. With institutional review board approval, we completed a retrospective cohort study at the Vanderbilt Preoperative Evaluation Clinic from March 1, 2013 to March 1, 2014. We selected all patients having two preoperative asse ssments within the study period (Cohort-1). Though duplicating assessments is not standard practice in the clinic, some patients receive multiple preoperative asses sments when they undergo multiple unrelated procedures or repeat procedures or experience extended delays between assessment and surgery. We excluded patients with more than a 10% change in weight between visits. At each preoperative visit, a clinic technician used a tape measure to determine the patients’ neck circumference measurement. We then compared the two neck circum ference measurements. We separately selected a patient population (Cohort-2) of 110 individuals with both a preoperative facial photograph (which we routinely obtain) and an in-clinic neck circumference measurement. Each patient’s photo graph was taken with an iPad and wirelessly transmitted into their medical record. We excluded patients from the study if their neck view was obstructed in the photograph. Using this preoperative image, we estimated a virtual neck circumference and compared our calculation with the neck circumference measurement (taken on-site) for analysis. The photograph included a one-inch square reference image in the background used to scale the photograph according to pixel length (Figure A). We used the following equation to determine an estimate for the neck circumference (which we assumed was circular):