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BackgroundIn 2017, the Accreditation Council for Graduate Medical Education (ACGME) revised its Common Program Requirements to support trainees and faculty by mandating programs to provide dedicated wellness resources and education. Emergency medicine may benefit from this change due to high burnout rates within the specialty. However, the current state of wellness interventions in emergency medicine (EM) residency programs has not yet been well described. Understanding current practices is necessary to assess unmet needs and inform the development and evaluation of future interventions that aim to improve trainee wellness.ObjectivesThe goal of this study was to describe currently implemented wellness interventions in EM residency programs.MethodsThis descriptive study surveyed 250 ACGME-accredited EM residency programs between March 1 and June 1, 2020, regarding wellness interventions. The survey included demographic questions; structured multiple-choice questions about cost, frequency, and champions; and free-text response options to briefly describe interventions. Respondents were also asked to classify the interventions according to the seven factors described in the National Academy of Medicine Model of Clinician Well-Being and Resilience.ResultsNinety of 250 (36% response rate) residency programs participated, describing 162 unique wellness interventions. Respondents classified the majority of interventions (n = 136) as targeting personal factors according to the National Academy of Medicine model. Qualitative analysis revealed five major themes describing the interventions: program culture, program factors, environmental and clinical factors, wellness activities and practices, and wellness resources.ConclusionsResults of this survey may help to inform a national needs assessment addressing the current state of wellness interventions in EM residency programs. Our results highlight the need for more interventions targeting external factors impacting resident wellness.

Introduction: Recent research demonstrates burnout prevalence rates as high as 76% in emergency medicine (EM) residents. In 2017 the Accreditation Council for Graduate Medical Education (ACGME) required that all training programs provide dedicated wellness education for their trainees as a requirement for accreditation. We aimed to conduct a systematic review of published wellness interventions conducted in EM residency programs following the implementation of the 2017 ACGME Common Program Requirements change in order to characterized published intervention and evaluate their effectiveness.Methods: We applied a published approach to conducting systematic reviews of the medical education literature. We performed a search of the literature from January 1, 2017–February 1, 2020. Studies were included for final review if they described a specific intervention and reported outcomes with the primary goal of improving EM resident wellness. Outcomes were characterized using the Kirkpatrick training evaluation model.Results: Eight of 35 identified studies met inclusion criteria. Most described small convenience samples of EM residents from single training programs and used the satisfaction rates of participants as primary outcome data. Only quantitative assessment methods were used. Studies addressed only a limited number of factors affecting resident wellness. The majority of interventions focused on personal factors, although a few also included sociocultural factors and the learning and practice environment.Conclusion: There is a relative dearth of literature in the area of research focused on interventions designed to improve EM resident wellness. Furthermore, the studies we identified are narrow in scope, involve relatively few participants, and describe programmatic changes of limited variety.  Future directions include an increase and emphasis on multi-institutional studies, randomized controlled trials, qualitative methodology, and opportunities for funded research.

We report a case of a 17 year old lady who presented with severe abdominal pain for 4 days. Patient developed fulminant hepatitis and disseminated intravascular coagulation during her hospital stay. History of Ratol (3% yellow phosphorus) ingestion was revealed on the second day of admission. She was managed with NAC infusion for 3 days along with supportive treatment and was discharged on the 10th day of admission. Accidental ingestion of Ratol is common in rural India. Early diagnosis and management of yellow phosphorus can improve the outcome of the patient. It is important to identify predictors of outcome of patients with toxin-induced liver injury. [ABSTRACT FROM AUTHOR]

Background: The role of artificial intelligence and radiomics in prediction model development in cancer has been increasing every passing day. Cervical cancer is the 4th most common cancer in women worldwide, contributing to 6.5% of all cancer types. The treatment outcome of cervical cancer patients varies and individualized prediction of disease outcome is of paramount importance. Purpose: The purpose of this study is to develop and validate the digital signature for 5-year overall survival prediction in cervical cancer using robust CT radiomic and clinical features. Materials and Methods: Pretreatment clinical features and CT radiomic features of 68 patients, who were treated with chemoradiation therapy in our hospital, were used in this study. Radiomic features were extracted using an in-house developed python script and pyradiomic package. Clinical features were selected by the recursive feature elimination technique. Whereas radiomic feature selection was performed using a multi-step process i.e., step-1: only robust radiomic features were selected based on our previous study, step-2: a hierarchical clustering was performed to eliminate feature redundancy, and step-3: recursive feature elimination was performed to select the best features for prediction model development. Four machine algorithms i.e., Logistic regression (LR), Random Forest (RF), Support vector classifier (SVC), and Gradient boosting classifier (GBC), were used to develop 24 models (six models using each algorithm) using clinical, radiomic and combined features. Models were compared based on the prediction score in the internal validation. Results: The average prediction accuracy was found to be 0.65 (95% CI: 0.60– 0.70), 0.72 (95% CI: 0.63–0.81), and 0.77 (95% CI: 0.72–0.82) for clinical, radiomic, and combined models developed using four prediction algorithms respectively. The average prediction accuracy was found to be 0.69 (95% CI: 0.62–0.76), 0.79 (95% CI: 0.72–0.86), 0.71 (95% CI: 0.62–0.80), and 0.72 (95% CI: 0.66–0.78) for LR, RF, SVC and GBC models developed on three datasets respectively. Conclusion: Our study shows the promising predictive performance of a robust radiomic signature to predict 5-year overall survival in cervical cancer patients. [ABSTRACT FROM AUTHOR]

Extracranial metastasis from high-grade glial tumors is an extremely rare condition with its reported incidence being <1%. The most common sites reported in the literature are leptomeninges and spinal cord, followed by the liver, lung, and skeletal system. Its low incidence is thought to be related to the intrinsic aggressive biology of the tumor, thus reducing median overall survival in patients. As there is lack of knowledge about the mechanism of extracranial spread of glioma cells, its diagnosis and management remain a major challenge. We report two cases of extracranial metastases from glial tumors to cervical nodes and postoperative site involving preauricular region detected on F18 Fluoro ethyl tyrosine (FET) positron emission tomography-computed tomography and later on confirmed with histopathology Fluoro ethyl tyrosine. [ABSTRACT FROM AUTHOR]