Predicting Out-of-Hospital Cardiac Arrest in the General Population Using Electronic Health Records.

BACKGROUND: The majority of out-of-hospital cardiac arrests (OHCAs) occur among individuals in the general population, for whom there is no established strategy to identify risk. In this study, we assess the use of electronic health record (EHR) data to identify OHCA in the general population and define salient factors contributing to OHCA risk. METHODS: The analytical cohort included 2366 individuals with OHCA and 23 660 age- and sex-matched controls receiving health care at the University of Washington. Comorbidities, electrocardiographic measures, vital signs, and medication prescription were abstracted from the EHR. The primary outcome was OHCA. Secondary outcomes included shockable and nonshockable OHCA. Model performance including area under the receiver operating characteristic curve and positive predictive value were assessed and adjusted for observed rate of OHCA across the health system. RESULTS: There were significant differences in demographic characteristics, vital signs, electrocardiographic measures, comorbidities, and medication distribution between individuals with OHCA and controls. In external validation, discrimination in machine learning models (area under the receiver operating characteristic curve 0.80-0.85) was superior to a baseline model with conventional cardiovascular risk factors (area under the receiver operating characteristic curve 0.66). At a specificity threshold of 99%, correcting for baseline OHCA incidence across the health system, positive predictive value was 2.5% to 3.1% in machine learning models compared with 0.8% for the baseline model. Longer corrected QT interval, substance abuse disorder, fluid and electrolyte disorder, alcohol abuse, and higher heart rate were identified as salient predictors of OHCA risk across all machine learning models. Established cardiovascular risk factors retained predictive importance for shockable OHCA, but demographic characteristics (minority race, single marital status) and noncardiovascular comorbidities (substance abuse disorder) also contributed to risk prediction. For nonshockable OHCA, a range of salient predictors, including comorbidities, habits, vital signs, demographic characteristics, and electrocardiographic measures, were identified. CONCLUSIONS: In a population-based case-control study, machine learning models incorporating readily available EHR data showed reasonable discrimination and risk enrichment for OHCA in the general population. Salient factors associated with OCHA risk were myriad across the cardiovascular and noncardiovascular spectrum. Public health and tailored strategies for OHCA prediction and prevention will require incorporation of this complexity.

Perioperative Mortality of the COVID-19 Recovered Patient Compared to a Matched Control: A Multicenter Retrospective Cohort Study.

BACKGROUND: Surgical procedures performed on patients with recent exposure to COVID-19 infection have been associated with increased mortality risk in previous studies. Accordingly, elective surgery is often delayed after infection. The study aimed to compare 30-day hospital mortality and postoperative complications (acute kidney injury, pulmonary complications) of surgical patients with a previous COVID-19 infection to a matched cohort of patients without known previous COVID-19. The authors hypothesized that COVID-19 exposure would be associated with an increased mortality risk. METHODS: In this retrospective observational cohort study, patients presenting for elective inpatient surgery across a multicenter cohort of academic and community hospitals from April 2020 to April 2021 who had previously tested positive for COVID-19 were compared to controls who had received at least one previous COVID-19 test but without a known previous COVID-19-positive test. The cases were matched based on anthropometric data, institution, and comorbidities. Further, the outcomes were analyzed stratified by timing of a positive test result in relation to surgery. RESULTS: Thirty-day mortality occurred in 229 of 4,951 (4.6%) COVID-19-exposed patients and 122 of 4,951 (2.5%) controls. Acute kidney injury was observed in 172 of 1,814 (9.5%) exposed patients and 156 of 1,814 (8.6%) controls. Pulmonary complications were observed in 237 of 1,637 (14%) exposed patients and 164 of 1,637 (10%) controls. COVID-19 exposure was associated with an increased 30-day mortality risk (adjusted odds ratio, 1.63; 95% CI, 1.38 to 1.91) and an increased risk of pulmonary complications (1.60; 1.36 to 1.88), but was not associated with an increased risk of acute kidney injury (1.03; 0.87 to 1.22). Surgery within 2 weeks of infection was associated with a significantly increased risk of mortality and pulmonary complications, but that effect was nonsignificant after 2 weeks. CONCLUSIONS: Patients with a positive test for COVID-19 before elective surgery early in the pandemic have an elevated risk of perioperative mortality and pulmonary complications but not acute kidney injury as compared to matched controls. The span of time from positive test to time of surgery affected the mortality and pulmonary risk, which subsided after 2 weeks.

Public Health Informatics and the Perioperative Physician: Looking to the Future.

The role of informatics in public health has increased over the past few decades, and the coronavirus disease 2019 (COVID-19) pandemic has underscored the critical importance of aggregated, multicenter, high-quality, near-real-time data to inform decision-making by physicians, hospital systems, and governments. Given the impact of the pandemic on perioperative and critical care services (eg, elective procedure delays; information sharing related to interventions in critically ill patients; regional bed-management under crisis conditions), anesthesiologists must recognize and advocate for improved informatic frameworks in their local environments. Most anesthesiologists receive little formal training in public health informatics (PHI) during clinical residency or through continuing medical education. The COVID-19 pandemic demonstrated that this knowledge gap represents a missed opportunity for our specialty to participate in informatics-related, public health-oriented clinical care and policy decision-making. This article briefly outlines the background of PHI, its relevance to perioperative care, and conceives intersections with PHI that could evolve over the next quarter century.

Cardiometabolic disease and obesity patterns differentially predict acute kidney injury after total joint replacement: a retrospective analysis.

BACKGROUND: Acute kidney injury (AKI) is a frequent yet understudied postoperative total joint arthroplasty complication. This study aimed to describe cardiometabolic disease co-occurrence using latent class analysis, and associated postoperative AKI risk. METHODS: This retrospective analysis examined patients ≥18 years old undergoing primary total knee or hip arthroplasties within the US Multicenter Perioperative Outcomes Group of hospitals from 2008 to 2019. AKI was defined using modified Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Latent classes were constructed from eight cardiometabolic diseases including hypertension, diabetes, and coronary artery disease, excluding obesity. A mixed-effects logistic regression model was constructed for the outcome of any AKI and the exposure of interaction between latent class and obesity status adjusting for preoperative and intraoperative covariates. RESULTS: Of 81 639 cases, 4007 (4.9%) developed AKI. Patients with AKI were more commonly older and non-Hispanic Black, with more significant comorbidity. A latent class model selected three groups of cardiometabolic patterning, labelled 'hypertension only' (n=37 223), 'metabolic syndrome (MetS)' (n=36 503), and 'MetS+cardiovascular disease (CVD)' (n=7913). After adjustment, latent class/obesity interaction groups had differential risk of AKI compared with those in 'hypertension only'/non-obese. Those 'hypertension only'/obese had 1.7-fold increased odds of AKI (95% confidence interval [CI]: 1.5-2.0). Compared with 'hypertension only'/non-obese, those 'MetS+CVD'/obese had the highest odds of AKI (odds ratio 3.1, 95% CI: 2.6-3.7), whereas 'MetS+CVD'/non-obese had 2.2 times the odds of AKI (95% CI: 1.8-2.7; model area under the curve 0.76). CONCLUSIONS: The risk of postoperative AKI varies widely between patients. The current study suggests that the co-occurrence of metabolic conditions (diabetes mellitus, hypertension), with or without obesity, is a more important risk factor for acute kidney injury than individual comorbid diseases.

Prediction of American Society of Anesthesiologists Physical Status Classification from preoperative clinical text narratives using natural language processing.

BACKGROUND: Electronic health records (EHR) contain large volumes of unstructured free-form text notes that richly describe a patient's health and medical comorbidities. It is unclear if perioperative risk stratification can be performed directly from these notes without manual data extraction. We conduct a feasibility study using natural language processing (NLP) to predict the American Society of Anesthesiologists Physical Status Classification (ASA-PS) as a surrogate measure for perioperative risk. We explore prediction performance using four different model types and compare the use of different note sections versus the whole note. We use Shapley values to explain model predictions and analyze disagreement between model and human anesthesiologist predictions. METHODS: Single-center retrospective cohort analysis of EHR notes from patients undergoing procedures with anesthesia care spanning all procedural specialties during a 5 year period who were not assigned ASA VI and also had a preoperative evaluation note filed within 90 days prior to the procedure. NLP models were trained for each combination of 4 models and 8 text snippets from notes. Model performance was compared using area under the receiver operating characteristic curve (AUROC) and area under the precision recall curve (AUPRC). Shapley values were used to explain model predictions. Error analysis and model explanation using Shapley values was conducted for the best performing model. RESULTS: Final dataset includes 38,566 patients undergoing 61,503 procedures with anesthesia care. Prevalence of ASA-PS was 8.81% for ASA I, 31.4% for ASA II, 43.25% for ASA III, and 16.54% for ASA IV-V. The best performing models were the BioClinicalBERT model on the truncated note task (macro-average AUROC 0.845) and the fastText model on the full note task (macro-average AUROC 0.865). Shapley values reveal human-interpretable model predictions. Error analysis reveals that some original ASA-PS assignments may be incorrect and the model is making a reasonable prediction in these cases. CONCLUSIONS: Text classification models can accurately predict a patient's illness severity using only free-form text descriptions of patients without any manual data extraction. They can be an additional patient safety tool in the perioperative setting and reduce manual chart review for medical billing. Shapley feature attributions produce explanations that logically support model predictions and are understandable to clinicians.

Liver Fibrosis Marker and Postoperative Mortality in Patients Without Overt Liver Disease.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) can progress to advanced fibrosis, which, in the nonsurgical population, is associated with poor hepatic and extrahepatic outcomes. Despite its high prevalence, NAFLD and related liver fibrosis may be overlooked during the preoperative evaluation, and the role of liver fibrosis as an independent risk factor for surgical-related mortality has yet to be tested. The aim of this study was to assess whether fibrosis-4 (FIB-4), which consists of age, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and platelets, a validated marker of liver fibrosis, is associated with postoperative mortality in the general surgical population. METHODS: A historical cohort of patients undergoing general anesthesia at an academic medical center between 2014 and 2018 was analyzed. Exclusion criteria included known liver disease, acute liver disease or hepatic failure, and alcohol use disorder. FIB-4 score was categorized into 3 validated predefined categories: FIB-4 ≤1.3, ruling out advanced fibrosis; >1.3 and <2.67, inconclusive; and ≥2.67, suggesting advanced fibrosis. The primary analytic method was propensity score matching (FIB-4 was dichotomized to indicate advanced fibrosis), and a secondary analysis included a multivariable logistic regression. RESULTS: Of 19,861 included subjects, 1995 (10%) had advanced fibrosis per FIB-4 criteria. Mortality occurred intraoperatively in 15 patients (0.1%), during hospitalization in 272 patients (1.4%), and within 30 days of surgery in 417 patients (2.1%). FIB-4 ≥2.67 was associated with increased intraoperative mortality (odds ratio [OR], 3.63; 95% confidence interval [CI], 1.25-10.58), mortality during hospitalization (OR, 3.14; 95% CI, 2.37-4.16), and within 30 days from surgery (OR, 2.46; 95% CI, 1.95-3.10), after adjusting for other risk factors. FIB-4 was related to increased mortality in a dose-dependent manner for the 3 FIB-4 categories ≤1.3 (reference), >1.3 and <2.67, and ≥2.67, respectively; during hospitalization (OR, 1.89; 95% CI, 1.34-2.65 and OR, 4.70; 95% CI, 3.27-6.76) and within 30 days from surgery (OR, 1.77; 95% CI, 1.36-2.31 and OR, 3.55; 95% CI, 2.65-4.77). In a 1:1 propensity-matched sample (N = 1994 per group), the differences in mortality remained. Comparing the FIB-4 ≥2.67 versus the FIB-4 <2.67 groups, respectively, mortality during hospitalization was 5.1% vs 2.2% (OR, 2.70; 95% CI, 1.81-4.02), and 30-day mortality was 6.6% vs 3.4% (OR, 2.26; 95% CI, 1.62-3.14). CONCLUSIONS: A simple liver fibrosis marker is strongly associated with perioperative mortality in a population without apparent liver disease, and may aid in future surgical risk stratification and preoperative optimization.

Completion of an Enhanced Recovery Program in a Pediatric Ambulatory Surgery Center: A Quality Improvement Initiative.

BACKGROUND: Enhanced Recovery After Surgery (ERAS) was first established in 2001 focusing on recovery from complex surgical procedures in adults and recently expanded to ambulatory surgery. The evidence for ERAS in children is limited. In 2018, recognized experts began developing needed pediatric evidence. Center-wide efforts involving all ambulatory surgical patients and procedures have not previously been described. METHODS: A comprehensive assessment and gap analysis of ERAS elements in our ambulatory center identified 11 of 19 existing elements. The leadership committed to implementing an Enhanced Recovery Program (ERP) to improve existing elements and close as many remaining gaps as possible. A quality improvement (QI) team was launched to improve 5 existing ERP elements and to introduce 6 new elements (target 17/19 ERP elements). The project plan was broken into 1 preparation phase to collect baseline data and 3 implementation phases to enhance existing and implement new elements. Statistical process control methodology was used. Team countermeasures were based on available evidence. A consensus process was used to resolve disagreement. Monthly meetings were held to share real-time data, gather new feedback, and modify countermeasure plans as needed. The primary outcome measure selected was mean postanesthesia care unit (PACU) length of stay (LOS). Secondary outcomes measures were mean maximum pain score in PACU and patient/family satisfaction scores. RESULTS: The team had expanded the pool of active ERP elements from 11 to 16 of 19. The mean PACU LOS demonstrated significant reduction (early in phase 1 and again in phase 3). No change was seen for the mean maximum pain score in PACU or surgical complication rates. Patient/family satisfaction scores were high and sustained throughout the period of study (91.1% ± 5.7%). Patient/family and provider engagement/compliance were high. CONCLUSIONS: This QI project demonstrated the feasibility of pediatric ERP in an ambulatory surgical setting. Furthermore, a center-wide approach was shown to be possible. Additional studies are needed to determine the relevance of this project to other institutions.

Implementation of App-Based Diabetes Medication Management: Outpatient and Perioperative Clinical Decision Support.

PURPOSE OF REVIEW: Outpatient and perioperative therapeutic decision making for patients with diabetes involves increasingly complex medical-decision making due to rapid advances in knowledge and treatment modalities. We sought to review mobile decision support tools available to clinicians for this essential and increasingly difficult task, and to highlight the development and implementation of novel mobile applications for these purposes. RECENT FINDINGS: We found 211 mobile applications related to diabetes from the search, but only five were found to provide clinical decision support for outpatient diabetes management and none for perioperative decision support. We found a dearth of tools for clinicians to navigate these tasks. We highlight key aspects for effective development of future diabetes decision support. These include just-in-time availability, respect for the five rights of clinical decision support, and integration with clinical workflows including the electronic medical record.

Erector Spinae Regional Anesthesia for Robotic Coronary Artery Bypass Surgery Is Not Associated With Reduced Postoperative Opioid Use: A Retrospective Observational Study.

OBJECTIVE: Regional anesthesia techniques are gaining traction in cardiac surgery. The aim of this study was to compare the analgesic efficacy of erector spinae plane block catheters (ESPBC), serratus anterior plane block catheters (SAPBC), and paravertebral single-shot block (PVB) versus no block after robotic minimally invasive direct coronary artery bypass (MIDCAB). DESIGN: This was a retrospective observational study of routinely recorded data. SETTING: The study was performed at a single healthcare system. PARTICIPANTS: All patients underwent robotic MIDCAB. INTERVENTION: Data were analyzed from 346 patients during a 53-month period. The clinical data warehouse was queried for all robotic MIDCAB surgeries. Variables abstracted included type of nerve block, age, sex, use of adjuncts, Society of Thoracic Surgeons predicted short length of stay (PSLOS), total opioid consumption during the 72 hours after surgery, and postoperative hospital length of stay (LOS). The primary outcome was total oral morphine milligram equivalents (MME) consumed during the first 72 hours after surgery. The secondary outcome was hospital LOS. MEASUREMENTS AND MAIN RESULTS: In a model adjusting for PSLOS, the authors did not observe an association between ESPBC and the reduction of total administered oral MME within 72 hours after surgery. There was no significant difference in MME when comparing patients who received PVB to patients with ESPBC. Older age and female sex were associated with significantly lower MME. Patients who received ESPBC had a significantly shorter hospital LOS than patients with SAPBC. CONCLUSIONS: These findings suggested that postoperative pain after MIDCAB surgery might not be completely covered by ESPBC. Prospective studies are needed to further elucidate the value of this technique for robotic MIDCAB.

Impact of COVID-19 response on global surgical volumes: an ongoing observational study.

OBJECTIVE: To determine whether location-linked anaesthesiology calculator mobile application (app) data can serve as a qualitative proxy for global surgical case volumes and therefore monitor the impact of the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We collected data provided by users of the mobile app "Anesthesiologist" during 1 October 2018-30 June 2020. We analysed these using RStudio and generated 7-day moving-average app use plots. We calculated country-level reductions in app use as a percentage of baseline. We obtained data on COVID-19 case counts from the European Centre for Disease Prevention and Control. We plotted changing app use and COVID-19 case counts for several countries and regions. FINDINGS: A total of 100 099 app users within 214 countries and territories provided data. We observed that app use was reduced during holidays, weekends and at night, correlating with expected fluctuations in surgical volume. We observed that the onset of the pandemic prompted substantial reductions in app use. We noted strong cross-correlation between COVID-19 case count and reductions in app use in low- and middle-income countries, but not in high-income countries. Of the 112 countries and territories with non-zero app use during baseline and during the pandemic, we calculated a median reduction in app use to 73.6% of baseline. CONCLUSION: App data provide a proxy for surgical case volumes, and can therefore be used as a real-time monitor of the impact of COVID-19 on surgical capacity. We have created a dashboard for ongoing visualization of these data, allowing policy-makers to direct resources to areas of greatest need.

Chronic Atypical Antipsychotic Use Is Associated With Reduced Need for Postoperative Nausea and Vomiting Rescue in the Postanesthesia Care Unit: A Propensity-Matched Retrospective Observational Study.

BACKGROUND: Atypical antipsychotics are efficacious for chemoprophylaxis against chemotherapy-induced nausea and vomiting, but perioperative investigations have been scant. We sought to examine the association between chronic atypical antipsychotic therapy and the likelihood of postoperative nausea and vomiting. METHODS: In this single-center, propensity-matched, retrospective, observational study, elective noncardiac surgical cases from January 2014 to December 2017 were examined with regard to the primary outcome of rescue antiemetic administration in the postanesthesia care unit as a measure of postoperative nausea and vomiting. Chronic administration of olanzapine, aripiprazole, and risperidone was the exposure of interest. Other independent variables included outpatient antiemetics, modified Apfel score, age, American Society of Anesthesiologists physical status score, case length, and exposures to emetogenic and chemoprophylactic agents. Logistic regression was performed using case-level data. Conditional logistic regression was performed after 1:2 propensity matching, sampling without replacement. Monte Carlo simulation was performed to compute the mean patient-level treatment effect on the treated. RESULTS: Of 13,660 cases, 154 cases with patients receiving atypical antipsychotics were matched against 308 cases without, representing 115 and 273 unique patients, respectively. In a well-balanced cohort, the mean patient-level odds of being administered rescue antiemetic was lower for patients chronically taking the 3 atypical antipsychotics under consideration as compared to those not on atypical antipsychotics, with an odds ratio of 0.29 (95% CI, 0.11-0.75; P = .015). CONCLUSIONS: Chronic atypical antipsychotic therapy is associated with reduced risk of postanesthesia care unit antiemetic administration. These findings support the need for prospective studies to establish the safety and efficacy of postoperative nausea and vomiting chemoprophylaxis with these agents.

A Preoperative Cognitive Screening Test Predicts Increased Length of Stay in a Frail Population: A Retrospective Case-Control Study.

BACKGROUND: Frailty is associated with adverse perioperative outcomes including major morbidity, mortality, and increased length of stay. We sought to elucidate the role that a preoperatively assessed Mini-Cog can play in assessing the risk of adverse perioperative outcomes in a population at high risk of frailty. METHODS: In this retrospective case-control study, patients who were >60 years of age, nonambulatory, or had >5 documented medications were preoperatively assessed for handgrip strength, walking speed, and Mini-Cog score. The Emory University Clinical Data Warehouse was then used to extract this information and other perioperative data elements and outcomes data. RESULTS: Data were available for 1132 patients undergoing a wide variety of surgical procedures. For the subset of 747 patients with data for observed-to-expected length of stay, an abnormal Mini-Cog was associated with an increased odds of observed-to-expected >1 (odds ratio, 1.52; 95% CI, 1.05-2.19; P = .025). There was no association of abnormal Mini-Cog with intensive care unit length of stay >3 days (P = .182) discharge to home with self-care (P = .873) or risk of readmission (P = .104). Decreased baseline hemoglobin was associated with increased risk of 2 of the 4 outcomes studied. CONCLUSIONS: In a high-risk pool of patients, Mini-Cog may not be sensitive enough to detect significant differences for most adverse outcomes. Further work is needed to assess whether cognitive screens with greater resolution are of value in this context and to compare tools for assessing overall frailty status.

Lack of association between intraoperative handoff of care and postoperative complications: a retrospective observational study.

BACKGROUND: The significance of intraoperative anesthesia handoffs on patient outcomes are unclear. One aspect differentiating the disparate results is the treatment of confounding factors, such as patient comorbidities and surgery time of day. We performed this study to quantify the significance of confounding variables on composite adverse events during intraoperative anesthesia handoffs. METHODS: In this retrospective study, we analyzed data from the American College of Surgeons National Surgical Quality Improvement Project (ACS NSQIP). We examined the effects of intraoperative handoffs between anesthesia personnel. A total of 12,111 cases performed examined at two hospitals operated by a single healthcare system that were that included in the ACS NSQIP database performed. The presence of attending and anesthetist or resident handoffs, patient age, sex, body mass index, American Society of Anesthesiologists Physical Status (ASA-PS) classification, case length, surgical case complexity, and evening/weekend start time were measured. RESULTS: A total of 2586 of all cases in the NSQIP dataset experienced a handoff during the case. When analyzed as a single variable, attending handoffs were associated with higher rates of adverse outcomes. However, once confounding variables were added into the analysis, attending handoffs and complete care transitions were no longer statistically significant. CONCLUSIONS: Inclusion of significant covariates is essential to fully understanding the impact provider handoffs have on patient outcomes. Case timing and lengthy case duration are more likely to result in both a handoff and an adverse event. The impact of handoffs on patient outcomes seen in the literature are likely due, in part, to how covariates were addressed.

Global trends in the awareness of sepsis: insights from search engine data between 2012 and 2017.

BACKGROUND: Sepsis is an established global health priority with high mortality that can be curtailed through early recognition and intervention; as such, efforts to raise awareness are potentially impactful and increasingly common. We sought to characterize trends in the awareness of sepsis by examining temporal, geographic, and other changes in search engine utilization for sepsis information-seeking online. METHODS: Using time series analyses and mixed descriptive methods, we retrospectively analyzed publicly available global usage data reported by Google Trends (Google, Palo Alto, CA, USA) concerning web searches for the topic of sepsis between 24 June 2012 and 24 June 2017. Google Trends reports aggregated and de-identified usage data for its search products, including interest over time, interest by region, and details concerning the popularity of related queries where applicable. Outlying epochs of search activity were identified using autoregressive integrated moving average modeling with transfer functions. We then identified awareness campaigns and news media coverage that correlated with epochs of significantly heightened search activity. RESULTS: A second-order autoregressive model with transfer functions was specified following preliminary outlier analysis. Nineteen significant outlying epochs above the modeled baseline were identified in the final analysis that correlated with 14 awareness and news media events. Our model demonstrated that the baseline level of search activity increased in a nonlinear fashion. A recurrent cyclic increase in search volume beginning in 2012 was observed that correlates with World Sepsis Day. Numerous other awareness and media events were correlated with outlying epochs. The average worldwide search volume for sepsis was less than that of influenza, myocardial infarction, and stroke. CONCLUSIONS: Analyzing aggregate search engine utilization data has promise as a mechanism to measure the impact of awareness efforts. Heightened information-seeking about sepsis occurs in close proximity to awareness events and relevant news media coverage. Future work should focus on validating this approach in other contexts and comparing its results to traditional methods of awareness campaign evaluation.

Association of Serratus Anterior Plane Block for Minimally Invasive Direct Coronary Artery Bypass Surgery With Higher Opioid Consumption: A Retrospective Observational Study.

OBJECTIVE: The optimal regional technique for minimally invasive direct coronary artery bypass (MIDCAB) has yet to be determined. The aim of this study was to compare the efficacy of ultrasound-guided serratus anterior plane block (SAPB) with paravertebral block (PVB) and no block for controlling acute thoracotomy pain after robotic-assisted coronary artery bypass grafting (CABG). DESIGN: This is a retrospective study. Multiple variable regression analyses were performed. SETTING: The study was performed as a single institution. PARTICIPANTS: All patients underwent robotic-assisted CABG. INTERVENTION: Data were analyzed from 197 patients during a 27-month period. Charts were abstracted manually to ascertain type of nerve block, age, gender, use of home opioids, use of adjuncts for opioid reduction, Society of Thoracic Surgeons predicted long length of stay (LOS), total opioid consumption during the 72 hours after surgery, and postoperative LOS. The authors' primary outcome was total morphine equivalents consumed during the first 72 hours after surgery. The secondary outcome was hospital LOS. MEASUREMENTS AND MAIN RESULTS: Patients who received SAPB did not have significantly different opioid consumption than patients who had no block (p = 0.15), but it was increased significantly compared to patients administered PVB (PVB v SAPB catheter, p = 0.049; PVB v SAPB single shot, p = 0.049). There were no significant differences between groups in terms of postoperative LOS. CONCLUSION: These findings suggest SAPB might not cover adequately the incisional and tube pain associated with MIDCAB. If validated by prospective studies, these findings suggest that SAPB should be considered only for patients who are not candidates for PVB.

Evidence for increased use of the Society of Pediatric Anesthesia Critical Events Checklist in resource-limited environments: A retrospective observational study of app data.

BACKGROUND: Electronic decision support tools in anesthesiology practice have great value, including the potential for mobile applications to simplify delivery of best-practice guidelines. AIMS: We sought to combine demographics with usage information to elucidate important patterns in the rate of use of the Society of Pediatric Anesthesia Critical Events Checklist, as measured by in-app accesses of the checklist via the freely available anesthesia calculator app anesthesiologist. METHODS: We performed a retrospective analytic observational case-control study using analytics and survey data collected from the app. Users of the app were classified on the basis of whether or not they had accessed the checklist. This classification was used to perform logistic regression against a number of independent variables, including frequency of app use, country income level, professional role, rating of app importance, length of time in practice, group size, practice model, community served, and primary practice environment. RESULTS: Individual app users practicing in low- and middle-income countries have a significantly higher rate of Society for Pediatric Anesthesia Critical Events Checklist utilization as compared with high-income countries. Rural practitioners had higher utilization of the checklist. Practice size did not affect the utilization of the checklist. The checklist was used for both provider learning and for just-in-time patient care. CONCLUSION: mHealth apps are invaluable resource in everyday clinical practice. Mobile app analytics and in-app survey data reveal variable penetration and applicability of such technology worldwide. mHealth apps may be particularly impactful in limited-resource areas, such as lower-income environments and rural communities.