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Background A reduction in overall acute coronary syndrome (ACS) cases, increases in the severity of ACS presentation, and increased rates of out-of-hospital cardiac arrest (OHCA) have been reported from multiple countries during the COVID-19 pandemic. The attributed factors include COVID-19 infection, fear of COVID-19 and resultant avoidance of health care facilities, and restrictions on mobility. Pakistan, a country with a high burden of cardiovascular disease (CVD) and challenges related to health care access, will be expected to demonstrate these same findings. Therefore, we compared ACS hospitalization, ACS severity, and patients who have already died (dead on arrival, or DOA) due to presumed OHCA at a tertiary cardiac hospital during pre-pandemic and intra-pandemic periods in Pakistan. Methods Standardized data elements were extracted from the charts of patients with ACS, and telephonic verbal autopsies (VA) using a validated tool were conducted for patients who were arrived DOA. As a comparison, cases during the same months prior to the COVID-19 were analyzed for respective waves. Events were counted, and proportions and frequencies are reported for each time period. Results A total of 4,480 ACS cases were reviewed; 1,216 cases during March-July 2019, 804 cases in the same months of 2020 (33.8% decrease); 1,304 cases in August 2019-January 2020 and 1,157 in the corresponding months of 2020 and 2021 (11.2% decrease). There was no observed change in the baseline characteristics of patients with ACS or their symptom-to-door time, and in-hospital mortality was unchanged across all time periods. There were 218 DOA cases in pre-pandemic months and 360 cases during the pandemic. The pre-pandemic rate of DOA was 12/1000 emergency patients (95% CI 10–13) compared to 22/1000 (95% CI 22–27) during the pandemic (30/1000in the 1st wave and 17/1000 during 2nd wave). On VA, CVD was found to be the major cause of death during both time periods. Conclusion At a cardiac hospital in Pakistan, the COVID-19 pandemic was associated with a reduction in ACS hospitalization and an increased DOA rate.

BACKGROUND: Postoperative hypotension is associated with adverse outcomes, but intraoperative prediction of postanaesthesia care unit (PACU) hypotension is not routine in anaesthesiology workflow. Although machine learning models may support clinician prediction of PACU hypotension, clinician acceptance of prediction models is poorly understood. METHODS: We developed a clinically informed gradient boosting machine learning model using preoperative and intraoperative data from 88 446 surgical patients from 2015 to 2019. Nine anaesthesiologists each made 192 predictions of PACU hypotension using a web-based visualisation tool with and without input from the machine learning model. Questionnaires and interviews were analysed using thematic content analysis for model acceptance by anaesthesiologists. RESULTS: The model predicted PACU hypotension in 17 029 patients (area under the receiver operating characteristic [AUROC] 0.82 [95% confidence interval {CI}: 0.81–0.83] and average precision 0.40 [95% CI: 0.38–0.42]). On a random representative subset of 192 cases, anaesthesiologist performance improved from AUROC 0.67 (95% CI: 0.60–0.73) to AUROC 0.74 (95% CI: 0.68–0.79) with model predictions and information on risk factors. Anaesthesiologists perceived more value and expressed trust in the prediction model for prospective planning, informing PACU handoffs, and drawing attention to unexpected cases of PACU hypotension, but they doubted the model when predictions and associated features were not aligned with clinical judgement. Anaesthesiologists expressed interest in patient-specific thresholds for defining and treating postoperative hypotension. CONCLUSIONS: The ability of anaesthesiologists to predict PACU hypotension was improved by exposure to machine learning model predictions. Clinicians acknowledged value and trust in machine learning technology. Increasing familiarity with clinical use of model predictions is needed for effective integration into perioperative workflows.

Background Modern medical education requires frequent competency assessment. The Accreditation Council for Graduate Medical Education (ACGME) provides a descriptive framework of competencies and milestones but does not provide standardized instruments to assess and track trainee competency over time. Entrustable professional activities (EPAs) represent a workplace-based method to assess the achievement of competency milestones at the point-of-care that can be applied to anesthesiology training in the United States. Methods Experts in education and competency assessment were recruited to participate in a 6-step process using a modified Delphi method with iterative rounds to reach consensus on an entrustment scale, a list of EPAs and procedural skills, detailed definitions for each EPA, a mapping of the EPAs to the ACGME milestones, and a target level of entrustment for graduating US anesthesiology residents for each EPA and procedural skill. The defined EPAs and procedural skills were implemented using a website and mobile app. The assessment system was piloted at 7 anesthesiology residency programs. After 2 months, faculty were surveyed on their attitudes on usability and utility of the assessment system. The number of evaluations submitted per month was collected for 1 year. Results Participants in EPA development included 18 education experts from 11 different programs. The Delphi rounds produced a final list of 20 EPAs, each differentiated as simple or complex, a defined entrustment scale, mapping of the EPAs to milestones, and graduation entrustment targets. A list of 159 procedural skills was similarly developed. Results of the faculty survey demonstrated favorable ratings on all questions regarding app usability as well as the utility of the app and EPA assessments. Over the 2-month pilot period, 1636 EPA and 1427 procedure assessments were submitted. All programs continued to use the app for the remainder of the academic year resulting in 12,641 submitted assessments. Conclusions A list of 20 anesthesiology EPAs and 159 procedural skills assessments were developed using a rigorous methodology to reach consensus among education experts. The assessments were pilot tested at 7 US anesthesiology residency programs demonstrating the feasibility of implementation using a mobile app and the ability to collect assessment data. Adoption at the pilot sites was variable; however, the use of the system was not mandatory for faculty or trainees at any site.

Key Points Question Based on the current understanding of the associations between school disruption and decreased educational attainment and between decreased educational attainment and lower life expectancy, is it possible to estimate the association between school closure during the coronavirus disease 2019 pandemic and decreased life expectancy of publicly educated primary school–aged children in the United States? Findings This decision analytical model found that missed instruction during 2020 could be associated with an estimated 5.53 million years of life lost. This loss in life expectancy was likely to be greater than would have been observed if leaving primary schools open had led to an expansion of the first wave of the pandemic. Meaning These findings suggest that the decision to close US public primary schools in the early months of 2020 may be associated with a decrease in life expectancy for US children., This decision analytical model estimates the potential years of life lost among US primary school–aged children associated with school closures during the coronavirus disease 2019 pandemic., Importance United States primary school closures during the 2020 coronavirus disease 2019 (COVID-19) pandemic affected millions of children, with little understanding of the potential health outcomes associated with educational disruption. Objective To estimate the potential years of life lost (YLL) associated with the COVID-19 pandemic conditioned on primary schools being closed or remaining open. Design, Setting, and Participants This decision analytical model estimated the association between school closures and reduced educational attainment and the association between reduced educational attainment and life expectancy using publicly available data sources, including data for 2020 from the US Centers for Disease Control and Prevention, the US Social Security Administration, and the US Census Bureau. Direct COVID-19 mortality and potential increases in mortality that might have resulted if school opening led to increased transmission of COVID-19 were also estimated. Main Outcomes and Measures Years of life lost. Results A total of 24.2 million children aged 5 to 11 years attended public schools that were closed during the 2020 pandemic, losing a median of 54 (interquartile range, 48-62.5) days of instruction. Missed instruction was associated with a mean loss of 0.31 (95% credible interval [CI], 0.10-0.65) years of final educational attainment for boys and 0.21 (95% CI, 0.06-0.46) years for girls. Summed across the population, an estimated 5.53 million (95% CI, 1.88-10.80) YLL may be associated with school closures. The Centers for Disease Control and Prevention reported a total of 88 241 US deaths from COVID-19 through the end of May 2020, with an estimated 1.50 million (95% CI, 1.23-1.85 million) YLL as a result. Had schools remained open, 1.47 million (95% credible interval, 0.45-2.59) additional YLL could have been expected as a result, based on results of studies associating school closure with decreased pandemic spread. Comparing the full distributions of estimated YLL under both “schools open” and “schools closed” conditions, the analysis observed a 98.1% probability that school opening would have been associated with a lower total YLL than school closure. Conclusions and Relevance In this decision analytical model of years of life potentially lost under differing conditions of school closure, the analysis favored schools remaining open. Future decisions regarding school closures during the pandemic should consider the association between educational disruption and decreased expected lifespan and give greater weight to the potential outcomes of school closure on children’s health.

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.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.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.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.Déterminer si les données provenant d'applications mobiles de calcul dédiées à l'anesthésie et munies d'une fonction de géolocalisation peuvent servir de substitut en vue d'évaluer le nombre d'interventions chirurgicales dans le monde et, par conséquent, de mesurer l'impact de la pandémie de maladie à coronavirus 2019 (COVID-19) sur ces interventions.Nous avons récolté les données fournies par les utilisateurs de l'application mobile «Anesthesiologist» entre le 1Au total, 100 099 utilisateurs originaires de 214 pays et régions nous ont communiqué leurs données. Nous avons observé une diminution dans l'utilisation de l'application durant les vacances, les week-ends et la nuit, ce qui correspond aux fluctuations prévues en matière de volume d'interventions. Nous avons également constaté que l'apparition de la pandémie avait entraîné une baisse considérable de l'utilisation de l'application. Nous avons noté une importante corrélation croisée entre le nombre de cas de COVID-19 et cette baisse d'utilisation dans les pays à faible et moyen revenu, mais pas dans les pays à haut revenu. Sur les 112 pays et régions affichant une utilisation non nulle de l'application pendant la période de référence et pendant la pandémie, nous avons calculé une réduction médiane de 73,6%.Les données provenant de l'application fournissent des informations indirectes qui servent à déterminer le nombre d'interventions chirurgicales, et peuvent donc être employées pour suivre en temps réel l'impact de la COVID-19 sur la capacité chirurgicale. Nous avons créé un tableau de bord pour visualiser ces données en continu, ce qui permet aux législateurs d'attribuer des ressources aux secteurs qui en ont le plus besoin.Determinar si los datos de las aplicaciones móviles para calcular la anestesia asociada a la localización pueden servir como un sustituto cualitativo para evaluar la cantidad de intervenciones quirúrgicas a nivel mundial y, por lo tanto, para medir el impacto de la pandemia de la enfermedad del coronavirus 2019 (COVID-19) en esas intervenciones.Se recopilaron los datos que suministraron los usuarios de la aplicación móvil «Anestesiólogo» durante el periodo comprendido entre el 1.Un total de 100 099 usuarios de la aplicación en 214 países y territorios suministraron datos. Se observó que el uso de la aplicación se redujo durante los días festivos, los fines de semana y por las noches, en correlación con las fluctuaciones previstas de la cantidad de intervenciones quirúrgicas. Se observó que el inicio de la pandemia generó reducciones sustanciales en el uso de la aplicación. Se registró una fuerte correlación cruzada entre el recuento de los casos de la COVID-19 y las reducciones en el uso de la aplicación en los países de ingresos bajos y medios, pero no en los países de ingresos altos. De los 112 países y territorios que no usaron la aplicación durante el momento basal y durante la pandemia, se calculó una reducción mediana en el uso de la aplicación hasta el 73,6 % del valor basal.Los datos de la aplicación representan indicadores de la cantidad de intervenciones quirúrgicas y, por lo tanto, se pueden usar para medir en tiempo real el impacto de la COVID-19 en la capacidad quirúrgica. Se ha elaborado un tablero para visualizar estos datos de forma continua, lo que permite a los responsables de formular las políticas asignar recursos a las áreas de mayor necesidad.الغرض تحديد ما إذا كانت بيانات تطبيق الهاتف المحمول (التطبيق) للآلة الحاسبة للتخدير، والمرتبطة بالموقع، يمكنها أن تكون بمثابة مؤشر نوعي لأحجام الحالات الجراحية العالمية، وبالتالي مراقبة تأثير الإصابة بفيروس كورونا 2019 (كوفيد 19). الطريقة قمنا بجمع البيانات التي قدمها مستخدمو تطبيق الهاتف المحمول Anesthesiologist (طبيب التخدير) خلال الفترة من 1 أكتوبر/تشرين أول 2018 إلى 30 يونيو/حزيران 2020. كما قمنا بتحليل هذه البيانات باستخدام RStudio، وقمنا بإنشاء مخططات لاستخدام توضح متوسط ​​الحركة لمدة 7 أيام. قم باحتساب حالات الانخفاض في استخدام التطبيق على مستوى البلد كنسبة مئوية من خط الأساس. حصلنا على بيانات عن عدد حالات الإصابة بمرض كوفيد -19 من المركز الأوروبي للوقاية من الأمراض ومكافحتها. قمنا بتخطيط التغيير في استخدام التطبيق وأعداد حالات كوفيد-19 للعديد من البلدان والمناطق. النتائج إجمالي 100099 من مستخدمي التطبيق في 214 بلدًا وإقليمًا، قاموا بتقديم البيانات. لاحظنا أن استخدام التطبيق قد انخفض خلال الإجازات وعطلات نهاية الأسبوع وأثناء الليل، وهو ما يرتبط بالتقلبات المتوقعة في حجم العمليات الجراحية. لاحظنا أن تفشي الوباء أدى إلى حالات انخفاض ملموسة في استخدام التطبيق. لاحظنا وجود علاقة متبادلة قوية بين عدد حالات الإصابة بكوفيد 19، والانخفاضات في استخدام التطبيق في البلدان منخفضة ومتوسطة الدخل، ولكن ليس في البلدان مرتفعة الدخل. من بين 112 بلدًا وإقليمًا ينعدم فيها استخدام التطبيق أثناء خط الأساس وأثناء الوباء، قمنا باحتساب متوسط ​​الانخفاض في استخدام التطبيق بنسبة 73.6% من خط الأساس. الاستنتاج توفر بيانات تطبيق الاستنتاج مؤشرًا لأحجام الحالات الجراحية، وبالتالي يمكن استخدامها كمراقب في الوقت الفعلي لتأثير كوفيد 19 على القدرة الجراحية. لقد أنشأنا لوحة تحكم للتصور المستمر لهذه البيانات، مما يسمح لواضعي السياسات بتوجيه الموارد إلى المناطق الأكثر احتياجًا.确定定位麻醉学计算器移动应用程序（以下简称应用）数据是否可以作为全球外科手术量的定性替代指标，从而监测 2019 年全球流行病冠状病毒 (COVID-19) 产生的影响。.我们收集了 2018 年 10 月 1 日至 2020 年 6 月 30 日期间，移动应用程序麻醉师 (Anesthesiologist) 用户的使用数据。我们利用 Rstudio 分析这些数据，并绘制出 7 天内使用应用的移动平均曲线图。我们计算出国家或地区应用使用人数削减数量占基准值的百分比。我们从欧洲疾病预防控制中心了解到新型冠状病毒肺炎病例数。我们绘制了一些国家和地区应用使用人数和新型冠状病毒肺炎病例数量变化图。.214 个国家和地区共有 100,099 名应用用户提供了数据。我们发现，应用使用人数在节假日、周末和晚间有所减少，这与外科手术量的预期波动有关，我们还观察到，全球性流行病爆发导致应用使用人数大幅度下降。我们也注意到，在中低收入国家，新型冠状病毒肺炎病例与应用使用人数减少存在很强的互相关性，而在高收入国家则不存在。基准线和全球性流行病爆发期间，应用使用人数非零的 112 个国家和地区中，我们得出其中位数下降到基准线的 73.6%。.应用数据可以作为外科手术台次的替代指标，因此可用来实时监测新型冠状病毒肺炎对外科手术量的影响。我们设计了一个仪表盘，以便不间断地提供可视化数据，从而决策者可将资源集中于最需要的地区。.Определить, могут ли данные мобильного приложения калькулятора анестезиологии с привязкой к местоположению служить качественным показателем глобальных объемов хирургических операций и, следовательно, отслеживать влияние пандемии коронавирусного заболевания 2019 г. (COVID-19).Авторы собрали данные, предоставленные пользователями мобильного приложения «Анестезиолог» в период с 1 октября 2018 г. по 30 июня 2020 г. Эти данные были проанализированы с помощью программы RStudio, и по ним были построены графики использования приложения для скользящих средних показаний за 7 дней. Сокращение использования приложения на уровне страны было рассчитано в виде процентов от исходного уровня. Данные о количестве случаев COVID-19 авторы получили из Европейского центра по контролю и профилактике заболеваний. Авторы составили график изменения использования приложения в зависимости от количества случаев COVID-19 для нескольких стран и регионов.Данные были получены от 100 099 пользователей приложения из 214 стран и территорий. Было отмечено, что использование приложения сокращалось в праздничные дни, выходные дни и ночью, что соотносится с ожидаемыми колебаниями объема хирургических операций. Также было отмечено, что начало пандемии привело к значительному сокращению использования приложения. Авторы наблюдали сильную взаимную корреляцию между количеством случаев COVID-19 и сокращением использования приложения в странах с низким и средним уровнем дохода, но не в странах с высоким уровнем дохода. По данным для 112 стран и территорий с ненулевым использованием приложения во время исходного уровня и во время пандемии медианное сокращение использования приложения составило до 73,6% от исходного уровня.Данные приложения служат косвенной оценкой количества проводимых хирургических операций и, следовательно, могут использоваться в качестве средства мониторинга воздействия COVID-19 на хирургический потенциал в режиме реального времени. Авторы создали панель индикаторов для непрерывной визуализации этих данных, которая позволяет лицам, формирующим политику, направлять ресурсы в области, где потребности являются наиболее острыми.

Background Cannabis legalization may contribute to an increased frequency of chronic use among patients presenting for surgery. At present, it is unknown whether chronic cannabis use modifies the risk of postoperative nausea and vomiting (PONV). Methods This study was a retrospective cohort study conducted at 2 academic medical centers. Twenty-seven thousand three hundred eighty-eight adult ASA 1–3 patients having general anesthesia for non-obstetric, non-cardiac procedures and receiving postoperative care in the Post Anesthesia Care Unit (PACU) were analyzed in the main dataset, and 16,245 patients in the external validation dataset. The main predictor was patient reported use of cannabis in any form collected during pre-anesthesia evaluation and recorded in the chart. The primary outcome was documented PONV of any severity prior to PACU discharge, including administration of rescue medications in PACU. Relevant clinical covariates (risk factors for PONV, surgical characteristics, administered prophylactic antiemetic drugs) were also recorded. Results 10.0% of patients in the analytic dataset endorsed chronic cannabis use. Using Bayesian Additive Regression Trees (BART), we estimated that the relative risk for PONV associated with daily cannabis use was 1.19 (95 CI% 1.00–1.45). The absolute marginal increase in risk of PONV associated with daily cannabis use was 3.3% (95% CI 0.4–6.4%). We observed a lesser association between current, non-daily use of cannabis (RR 1.07, 95% CI 0.94–1.21). An internal validation analysis conducted using propensity score adjustment and Bayesian logistic modeling indicated a similar size and magnitude of the association between cannabis use and PONV (OR 1.15, 90% CI 0.98–1.33). As an external validation, we used data from another hospital in our care system to create an independent model that demonstrated essentially identical associations between cannabis use and PONV. Conclusions Cannabis use is associated with an increased relative risk and a small increase in the marginal probability of PONV.

ImportanceThe COVID-19 pandemic has disrupted global surgical capacity. The impact of the pandemic in low and middle income countries has the potential to worsen already strained access to surgical care. Timely assessment of surgical volumes in these countries remains challenging.ObjectiveTo determine whether usage data from a globally used anesthesiology calculator mobile application can serve as a proxy for global surgical case volume and contribute to monitoring of the impact of the COVID-19 pandemic, particularly in World Bank low income countries where official data collection is not currently practical.DesignSubset of data from an ongoing observational cohort study of users of the application collected from October 1, 2018 to April 18, 2020.SettingThe mobile application is available from public sources; users download and use the application per their own clinical needs on personal mobile devices.ParticipantsNo user data was excluded from the study.Exposure(s)Events with impacts on surgical case volumes, including weekends, holidays, and the COVID-19 pandemic.Main Outcome(s) and Measure(s)It was previously noted that application usage was decreased on weekends and during winter holidays. We subsequently hypothesized that more detailed analysis would reveal impacts of country-specific or region-specific holidays on the volume of app use.Results4,300,975 data points from 92,878 unique users were analyzed. Physicians and other anesthesia providers comprised 85.8% of the study population. Application use was reduced on holidays and weekends and correlated with fluctuations in surgical volume. The COVID-19 pandemic was associated with substantial reductions in app use globally and regionally. There was strong cross correlation between COVID-19 case count and reductions in app use. By country, there was a median global reduction in app use to 58% of baseline (interquartile range, 46%-75%). Application use in low-income continues to decline but in high-income countries has stabilized.Conclusions and RelevanceApplication usage metadata provides a real-time indicator of surgical volume. This data may be used to identify impacted regions where disruptions to surgical care are disproportionate or prolonged. A dashboard for continuous visualization of these data has been deployed.Key PointsQuestionCan usage data from a globally used anesthesiology calculator mobile application contribute to monitoring of the impacts to global surgical case volume caused by the COVID-19 pandemic, particularly in resource-limited environments such as World Bank low income countries?FindingsIn this ongoing observational cohort study, application usage data from 92,878 unique users in 221 countries was found to serve well as a qualitative proxy for surgical case volume, with clear impacts to app use during weekend, holidays, and during the COVID-19 pandemic.MeaningThis proxy of surgical volume will provide insight into the impact of and recovery from the COVID-19 pandemic where official data collection is not currently practical. A real time dashboard tracking this proxy of global surgical volume is live and under continued development.

Purpose of review The purpose of this review is to describe recent developments and current trends in training anesthesiologists in out-of-operating room anesthesia (OORA). Recent findings In the United States, the Accreditation Council for Graduate Medical Education recently updated its training requirements to include a mandatory 2-week rotation in OORA for anesthesiology residents. This likely reflects the continuing expansion of anesthesia services in the out-of-operating room (OOR) environment as well as the increasing complexity of OOR procedures and medical acuity of patients in these settings. In the United Kingdom, the Royal College of Anaesthetists has rigorous and progressively complex requirements for trainees in 'non-theater' anesthesia experience as they move through the four stages of training. A variety of educational strategies and a well-validated six-step process for curriculum development are described in this review. Summary This review will provide useful models for training directors needing to design and implement OOR rotations for their trainees.

Background:: The COVID-19 pandemic has disrupted global surgical capacity. The impact of the pandemic in low and middle income countries (LMIC) has the potential to worsen already strained access to surgical care. However, timely assessment of surgical volumes in LMIC remains challenging. Methods: Data from a globally available anesthesia mobile application were examined to assess utilization as a real-time qualitative proxy for surgical case volume. Users consent to cloud-based data collection for an ongoing app utilization study. These data were analyzed to identify temporal and geographic trends indicative of COVID-19-associated changes in surgical volume. Findings: Between 1 October 2018 and 18 April 2020, data from 92,878 unique users in 221 countries were collected. App use was reduced on major holidays and weekends, strongly correlated with known fluctuations in surgical volume. The COVID-19 pandemic was associated with substantial reductions in app use globally and regionally. In individual countries and regions, there was strong cross correlation between COVID-19 case count and reductions in app use. By country, there was a median global reduction in app use to 54% of baseline (interquartile range, 42%-64%). Overall app use in LMIC continues to decline but in high-income countries has stabilized. Interpretation: The metadata from this app offers an inexpensive real-time indicator of surgical volume. This data may be used to identify impacted regions where disruptions to surgical care are disproportionate or prolonged. A dashboard for continuous visualization of these data will be deployed to ensure access to this proxy for global surgical volumes. Funding Statement: No funding to declare in support of the present work. Declaration of Interests: All authors declare: no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. The Anesthesiologist app was initially released in 2011 by Vikas O'Reilly-Shah with advertising in the free version and a paid companion app to remove the ads. The app intellectual property was transferred to Emory University in 2015 and advertisements were subsequently removed, and the companion app to remove ads made freely available for legacy users not updating to the ad-free version. Following review by the Emory University Research Conflict of Interest Committee, Vikas O'Reilly-Shah was released from any conflict of interest management plan or oversight. Ethics Approval Statement: The study was reviewed and approved by the Emory University Institutional Review Board (study number 00082571), and there is a reliance agreement in place with the University of Washington Institutional Review Board. The approval includes a waiver of written informed consent. Participants anonymously gave electronic consent before participating in any data collection.

Ackroyd and colleagues’ study[1][1] links epidural analgesia with negative postoperative outcomes based on a propensity matching model intended to remove the bias present in observational datasets. We question their approach for several reasons. First, covariates used to create their model are not

Background: Use of an in situ epidural catheter has been suggested to be efficient to provide anesthesia for postpartum tubal ligation (PPTL). Reported epidural reactivation success rates vary from 74% to 92%. Predictors for reactivation failure include poor patient satisfaction with labor analgesia, increased delivery-to-reactivation time and the need for top-ups during labor. Some have suggested that this high failure rate precludes leaving the catheter in situ after delivery for subsequent reactivation attempts. In this study, we sought to evaluate the success rate of neuraxial techniques for PPTL and to determine if predictors of failure can be identified. Methods: After obtaining IRB approval, a retrospective chart review of patients undergoing PPTL after vaginal delivery from July 2010 to July 2016 was conducted using CPT codes, yielding 93 records for analysis. Demographic, obstetric and anesthetic data (labor analgesia administration, length of epidural catheter in epidural space, top-up requirements, time of catheter reactivation, final anesthetic technique and corresponding doses for spinal and epidural anesthesia) were obtained. Results: A total of 70 patients received labor neuraxial analgesia. Reactivation was attempted in 33 with a success rate of 66.7%. Patient height, epidural volume of local anesthetic and administered fentanyl dose were lower in the group that failed reactivation. Overall, spinal anesthesia was performed in 60 patients, with a success rate of 80%. Conclusions: Our observed rate of successful postpartum epidural reactivation for tubal ligation was lower than the range reported in the literature. Our success rates for both spinal anesthesia and epidural reactivation for PPTL were lower than the generally accepted rates of successful epidural and spinal anesthesia for cesarean delivery. This gap may reflect a lower level of motivation on behalf of both the patients and anesthesia providers to tolerate “imperfect” neuraxial anesthesia once fetal considerations are removed.