Citations

Introduction Medical students experience higher rates of distress and burnout compared with their age-similar peers overall. Coaching has been proposed as one means of combating distress and burnout within the medical profession. The purpose of this systematic review is to synthesise the current evidence on the effects of coaching interventions on medical student well-being, including engagement, resilience, quality of life, professional fulfilment and meaning in work and distress, including burnout, anxiety and depressive symptoms. Methods and analysis We will conduct a systematic review of interventional and observational comparative studies that assess the effects of coaching interventions on well-being, including engagement, resilience, quality of life, professional fulfilment and meaning in work and distress, including burnout, anxiety and depressive symptoms among undergraduate medical students internationally. We will search PubMed (MEDLINE), Embase (OVID), PsycINFO (OVID), Scopus, ERIC, Cochrane Database of Systematic Reviews (OVID) and Cochrane Central Register of Controlled Trials (OVID) from their respective inception dates using the following search terms: (medical students OR medical student OR undergraduate medical education) AND (coach OR coaching OR coaches). Studies in any language will be eligible. Studies that report one or more outcomes of distress or well-being among medical students who receive a coaching intervention will be included. Data on participant and intervention characteristics, outcomes and instruments used will be collected as well as quality/risk of bias assessments. Two reviewers will screen studies against the inclusion criteria and perform data extraction. We will conduct a narrative synthesis, with meta-analysis if evidence permits quantitative pooling of results. Heterogeneity of results across studies according to study design, learner level and study risk of bias will be evaluated, as well as publication bias. Ethics and dissemination Ethical approval is not required for this review. Results will be disseminated by publication in a scientific journal. PROSPERO registration number CRD42022322503.

Abstract Background: A multitude of factors are considered in an infectious diseases (ID) training program’s meticulous selection process of ID fellows but their correlation to pre and in-fellowship academic success as well as post-fellowship academic success and short-term outcomes is poorly understood. Our goal was to investigate factors associated with subsequent academic success in fellowship as well as post-fellowship short-term outcomes. Methods: In 2022, we retrospectively analyzed deidentified academic records from 39 graduates of the Mayo Clinic Rochester ID Fellowship Program (July 1, 2013- June 30, 2022). Data abstracted included demographics, degrees, honor society membership, visa/citizenship status, medical school, residency training program, United States Medical Licensure Exam (USMLE) scores, letters of recommendation, in-training examination (ITE) scores, fellowship track, academic rank, career choice, number of honors, awards, and abstracts/publications prior to fellowship, during training, and within 2 years of graduation. Results: Younger fellows had higher USMLE step 1 scores, pre and in-fellowship scholarly productivity, and higher ITE performance. Female fellows had significantly higher USMLE step 3 scores. Prior research experience translated to greater in-fellowship scholarly productivity. Higher USMLE scores were associated with higher ID ITE performance during multiple years of fellowship, but USMLE step 2 clinical knowledge and 3 scores were associated with higher pre and in-fellowship scholarly productivity and receiving an award during fellowship. USMLE step 1 score did not correlate with fellowship performance beyond year 1 and 2 ITE scores. Conclusions: Multiple aspects of a prospective fellow’s application must be considered as part of a holistic reviewprocess for fellowship selection. USMLE step 2 CK and 3 scores may predict fellowship performance across multiple domains.

Background Nonalcoholic fatty liver disease (NAFLD) and heart failure with preserved ejection fraction (HFpEF) share common risk factors, including obesity and diabetes. They are also thought to be mechanistically linked. The aim of this study was to define serum metabolites associated with HFpEF in a cohort of patients with biopsy‐proven NAFLD to identify common mechanisms. Methods and Results We performed a retrospective, single‐center study of 89 adult patients with biopsy‐proven NAFLD who had transthoracic echocardiography performed for any indication. Metabolomic analysis was performed on serum using ultrahigh performance liquid and gas chromatography/tandem mass spectrometry. HFpEF was defined as ejection fraction >50% plus at least 1 echocardiographic feature of HFpEF (diastolic dysfunction, abnormal left atrial size) and at least 1 heart failure sign or symptom. We performed generalized linear models to evaluate associations between individual metabolites, NAFLD, and HFpEF. Thirty‐seven out of 89 (41.6%) patients met criteria for HFpEF. A total of 1151 metabolites were detected; 656 were analyzed after exclusion of unnamed metabolites and those with >30% missing values. Fifty‐three metabolites were associated with the presence of HFpEF with unadjusted P value <0.05; none met statistical significance after adjustment for multiple comparisons. The majority (39/53, 73.6%) were lipid metabolites, and levels were generally increased. Two cysteine metabolites (cysteine s‐sulfate and s‐methylcysteine) were present at significantly lower levels in patients with HFpEF. Conclusions We identified serum metabolites associated with HFpEF in patients with biopsy‐proven NAFLD, with increased levels of multiple lipid metabolites. Lipid metabolism could be an important pathway linking HFpEF to NAFLD.

Background and Purpose Recent introduction of photon counting detector (PCD) computed tomography (CT) scanners into clinical practice further improve CT angiography (CTA) depiction of orbital arterial vasculature compared to conventional energy integrating detector (EID) CT scanners. PCD-CTA of the orbit can provide a detailed arterial roadmap of the orbit which can de diagnostic on its own or serve as a helpful planning adjunct for both diagnostic and therapeutic catheter-based angiography of the orbit. Methods For this review, EID and PCD-CT imaging was obtained in 28 volunteers. The volume CT dose index was closely matched. A dual-energy scanning protocol was used on EID-CT. An ultra-high-resolution (UHR) scan mode was used on PCD-CT. Images were reconstructed at 0.6 mm slice thickness using a closely matched medium-sharp standard resolution (SR) kernel. High-resolution (HR) images with the sharpest quantitative kernel were also reconstructed on PCD-CT at the thinnest slice thickness of 0.2 mm. A denoising algorithm was applied to the HR image series. Results The imaging description of the orbital vascular anatomy presented in this work was derived from these patients’ PCD-CTA images in combination with review of the literature. We found that orbital arterial anatomy is much better depicted with PCD-CTA, and this work can serve primarily as an imaging atlas of the normal orbital vascular anatomy. Conclusion With recent advances in technology, arterial anatomy of the orbit is much better depicted with PCD-CTA as opposed to EID-CTA. Current orbital PCD-CTA technology approaches the necessary resolution threshold for reliable evaluation of central retinal artery occlusion.

Objective: The purpose of this study was to use the RE-AIM framework to evaluate the implementation of a mental health app designed for undergraduate and medical students during the COVID-19 pandemic. Participants: Medical (n = 270) and undergraduate students (n = 1386) from five universities in the Appalachian region in the United States participated in this study. Methods: Universities from the United States were recruited to deploy the Sharpen app for medical and undergraduate students. The Sharpen app provided psychoeducational modules in mental health literacy, social-emotional learning, mindfulness-based stress reduction, and suicide prevention to promote protective factors for students. The utilization of the Sharpen app was analyzed using the RE-AIM framework using a retrospective, cross-sectional design. Results: Reach: A total of 12.72% of medical students and 6.00% of undergraduate students participated in the study. Efficacy: Medical students viewed significantly more pages, had a significantly higher unique page view average, and a statistically significant exit percentage when compared to undergraduate students. Adoption: A total of 100% of the universities that were recruited participated in the study. Implementation: Five out of six implementation criteria were included, indicating high implementation. Maintenance: All of the universities continued using the Sharpen app following the end of data collection, resulting in a 100% maintenance rate. Conclusions: The RE-AIM framework indicated usability and maintenance by medical and undergraduate students. Future research needs to implement a more rigorous design to determine the impact of the Sharpen app on mental health outcomes in medical and undergraduate students.

Objective Noise quantification is fundamental to computed tomography (CT) image quality assessment and protocol optimization. This study proposes a deep learning–based framework, Single-scan Image Local Variance EstimatoR (SILVER), for estimating the local noise level within each region of a CT image. The local noise level will be referred to as a pixel-wise noise map. Methods The SILVER architecture resembled a U-Net convolutional neural network with mean-square-error loss. To generate training data, 100 replicate scans were acquired of 3 anthropomorphic phantoms (chest, head, and pelvis) using a sequential scan mode; 120,000 phantom images were allocated into training, validation, and testing data sets. Pixel-wise noise maps were calculated for the phantom data by taking the per-pixel SD from the 100 replicate scans. For training, the convolutional neural network inputs consisted of phantom CT image patches, and the training targets consisted of the corresponding calculated pixel-wise noise maps. Following training, SILVER noise maps were evaluated using phantom and patient images. For evaluation on patient images, SILVER noise maps were compared with manual noise measurements at the heart, aorta, liver, spleen, and fat. Results When tested on phantom images, the SILVER noise map prediction closely matched the calculated noise map target (root mean square error <8 Hounsfield units). Within 10 patient examinations, SILVER noise map had an average percent error of 5% relative to manual region-of-interest measurements. Conclusion The SILVER framework enabled accurate pixel-wise noise level estimation directly from patient images. This method is widely accessible because it operates in the image domain and requires only phantom data for training.

Abstract The receptor tyrosine kinase AXL is a member of the TYRO3, AXL, and proto-oncogene tyrosine-protein kinase MER family and plays pleiotropic roles in cancer progression. AXL is expressed in immunosuppressive cells, which contributes to decreased efficacy of immunotherapy. Therefore, we hypothesized that AXL inhibition could serve as a strategy to overcome resistance to chimeric antigen receptor T (CAR T)–cell therapy. To test this, we determined the impact of AXL inhibition on CD19-targeted CAR T (CART19)–cell functions. Our results demonstrate that T cells and CAR T cells express high levels of AXL. Specifically, higher levels of AXL on activated Th2 CAR T cells and M2-polarized macrophages were observed. AXL inhibition with small molecules or via genetic disruption in T cells demonstrated selective inhibition of Th2 CAR T cells, reduction of Th2 cytokines, reversal of CAR T-cell inhibition, and promotion of CAR T-cell effector functions. AXL inhibition is a novel strategy to enhance CAR T-cell functions through two independent, but complementary, mechanisms: targeting Th2 cells and reversing myeloid-induced CAR T-cell inhibition through selective targeting of M2-polarized macrophages.

Abstract The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1x10− 4 values, including HAS3, CNTNAP5 and NFIB. Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3β. We also found various genes associated with BP’s age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4, XKR4, NRXN1, NRG1/3 and GRK5. Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.