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AbstractBackgroundAs heart transplant guidelines evolve, the clinical indication for 73% of durable left ventricular assist device (LVAD) implants is now destination therapy. Although completely magnetically levitated LVAD devices have demonstrated improved durability relative to previous models, LVAD replacement procedures are still required for a variety of indications. Thus, the population of patients with a replaced LVAD is growing. There is a paucity of data regarding the outcomes and risk factors for those patients receiving first‐time LVAD replacements.MethodsThe study cohort consisted of all consecutive patients between 2006 and 2020 that received a first‐time LVAD replacement at a single institution. Preoperative clinical and laboratory variables were collected retrospectively. The primary endpoint was death or need for an additional LVAD replacement. Data were subjected to Kaplan–Meier, univariate, and multivariate Cox hazard ratio analyses.ResultsIn total, 152 patients were included in the study, of which 101 experienced the primary endpoint. On multivariate analysis, patients receiving HeartMate 3 (HM3) LVADs as the replacement device showed superior outcomes (HR 0.15, 95% CI 0.065–0.35, p < 0.0001). Independent risk factors for death or need for additional replacement included preoperative extracorporeal membrane oxygenation (ECMO) (HR 4.44, 95% CI 1.87–14.45, and p = 0.00042), increased number of sternotomies (HR 5.20, 95% CI 1.87–14.45, and p = 0.0016), and preoperative mechanical ventilation (HR 1.98, 95% CI 1.01–3.86, and p = 0.045).ConclusionsReplacement with HM3 showed superior outcomes compared to all other pump types when controlling for both initial pump type and other independent predictors of death or LVAD replacement. Preoperative ECMO, mechanical ventilation, and multiple sternotomies also increased the odds for death or the need for subsequent replacement.

Abstract Background Early diagnosis and appropriate management of concussion/mild traumatic brain injury (mTBI) is critical for preventing poor outcomes and minimizing health care burden. Current clinical guidelines for concussion management focus mostly on diagnosis and return to cognitive and physical activity but provide limited guidance on the use of specific therapeutic interventions. Objective To systematically review the available evidence on therapeutic interventions for concussion/mTBI and develop an evidence‐based consensus statement on the use of these interventions in clinical practice. Literature Survey A systematic literature search was performed first in 2018 and 2019, and again in 2022, to identify relevant original research on these interventions. A total of 6303 articles were retrieved through the systematic literature search and screened for inclusion. Eighty articles met inclusion criteria and were included in this review and consensus process. Methodology A multispecialty panel was convened to explore management of concussion/mTBI. Interventions evaluated included rest, exercise, rehabilitation, and return to activity (RTA) protocols. Studies were assessed for relevance and methodologic quality and were voted upon to develop an evidence‐based consensus statement on the therapeutic appropriateness of these interventions for concussion/mTBI. A meta‐analysis was not performed. Synthesis There was sufficient evidence to recommend exercise as an appropriate therapy for adolescents with acute concussion/mTBI. In other age groups and for other therapeutic modalities, although some studies demonstrated benefits for some of the interventions, mixed results and study limitations prevented the panel from drawing firm conclusions on the efficacy of those interventions. The panel found evidence of detrimental effects from strict rest and high‐intensity physical activity. Conclusions The panel recommended exercise as an appropriate therapy for acute concussion in adolescents. The evidence on other therapeutic interventions for concussion/mTBI remains limited to small randomized controlled trials and observational studies of moderate to low quality. The panel found no strong evidence to support or recommend against the other evaluated interventions but found most interventions to be safe when used judiciously and in consideration of individual patient needs. High‐quality randomized studies with sufficient power are needed to evaluate the effects of rest, rehabilitation, and RTA protocols for the management of concussion/mTBI.

INTRODUCTION: The coronavirus disease 19 (COVID-19) pandemic disrupted endoscopy practices, creating unprecedented decreases in cancer screening and surveillance services. We aimed to assess the impact of the pandemic on the proportion of patients diagnosed with Barrett's esophagus (BE) and BE-related dysplasia and adherence to established quality indicators. METHODS: Data from all esophagogastroduodenoscopies in the GI Quality Improvement Consortium, a national repository of matched endoscopy and pathology data, were analyzed from January 2018 to December 2022. Four cohorts were created based on procedure date and COVID-19 data: pre-pandemic (January 2018 to February 2020), pandemic-phase I (March 2020 to July 2020), pandemic-phase II (August 2020 to May 2021), and pandemic-phase III (June 2021 to December 2022). Observed and expected number of BE and BE-related dysplasia cases per month and adherence to the Seattle biopsy protocol and recommended surveillance intervals for nondysplastic BE (NDBE) were evaluated. RESULTS: Among 2,446,857 esophagogastroduodenoscopies performed during the study period, 104,124 (4.3%) had pathology-confirmed BE. The histologic distribution was 87.4% NDBE, 1.8% low-grade dysplasia, 2.4% indefinite for dysplasia, and 1.4% high-grade dysplasia. The number of monthly BE (−47.9% pandemic-phase I, −21.5% pandemic-phase II, and −19.0% pandemic-phase III) and BE-related dysplasia (high-grade dysplasia: 41.2%, −27.7%, and −19.0%; low-grade dysplasia: 49.1%, −35.3%, and −26.5%; any dysplasia: 46.7%, −32.3%, and −27.9%) diagnoses were significantly reduced during the pandemic phases compared with pre-pandemic data. Adherence rates to the Seattle protocol and recommended surveillance intervals for NDBE did not decline during the pandemic. DISCUSSION: There was a significant decline in the number of BE and BE-related dysplasia diagnoses during the COVID-19 pandemic, with an approximately 50% reduction in the number of cases of dysplasia diagnosed in the early pandemic. The absence of a compensatory increase in diagnoses in the pandemic-phase II and III periods may result in deleterious downstream effects on esophageal adenocarcinoma morbidity and mortality.

MSI-H identified by ctDNA: prevalence across 21 advanced cancers and outcomes from >700 patients.

Laser capture microdissection and mass spectrometry (LCM/MS) is a technique that involves dissection of glomeruli from paraffin-embedded biopsy tissue, followed by digestion of the dissected glomerular proteins by trypsin, and subsequently mass spectrometry to identify and semiquantitate the glomerular proteins. LCM/MS has played a crucial role in the identification of novel types of amyloidosis, biomarker discovery in fibrillary GN, and more recently discovery of novel target antigens in membranous nephropathy (MN). In addition, LCM/MS has also confirmed the role for complement proteins in glomerular diseases, including C3 glomerulopathy. LCM/MS is now widely used as a clinical test and considered the gold standard for diagnosis and typing amyloidosis. For the remaining glomerular diseases, LCM/MS has remained a research tool. In this review, we discuss the usefulness of LCM/MS in other glomerular diseases, particularly MN, deposition diseases, and diseases of complement pathways, and advocate more routine use of LCM/MS at the present time in at least certain diseases, such as MN, for target antigen detection. We also discuss the limitations of LCM/MS, particularly the difficulties faced from moving from a research-based technique to a clinical test. Nonetheless, the role of LCM/MS in glomerular diseases is expanding. Currently, LCM/MS may be used to identify the etiology in certain glomerular diseases, but in the future, LCM/MS can play a valuable role in determining pathways of complement activation, inflammation, and fibrosis.

AbstractBackgroundAccurate and efficient dose calculation is essential for on‐line adaptive planning in proton therapy. Deep learning (DL) has shown promising dose prediction results in photon therapy. However, there is a scarcity of DL‐based dose prediction methods specifically designed for proton therapy. Successful dose prediction method for proton therapy should account for more challenging dose prediction problems in pencil beam scanning proton therapy (PBSPT) due to its sensitivity to heterogeneities.PurposeTo develop a DL‐based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on‐line adaptive proton therapy clinical decision and subsequent replanning.MethodsPBSPT plans of 103 prostate cancer patients (93 for training and the other 10 for independent testing) and 83 lung cancer patients (73 for training and the other 10 for independent testing) previously treated at our institution were included in the study, each with computed tomography scans (CTs), structure sets, and plan doses calculated by the in‐house developed Monte‐Carlo dose engine (considered as the ground truth in the model training and testing). For the ablation study, we designed three experiments corresponding to the following three methods: (1) Experiment 1, the conventional region of interest (ROI) (composed of targets and organs‐at‐risk [OARs]) method. (2) Experiment 2, the beam mask (generated by raytracing of proton beams) method to improve proton dose prediction. (3) Experiment 3, the sliding window method for the model to focus on local details to further improve proton dose prediction. A fully connected 3D‐Unet was adopted as the backbone. Dose volume histogram (DVH) indices, 3D Gamma passing rates with a criterion of 3%/3 mm/10%, and dice coefficients for the structures enclosed by the iso‐dose lines between the predicted and the ground truth doses were used as the evaluation metrics. The calculation time for each proton dose prediction was recorded to evaluate the method's efficiency.ResultsCompared to the conventional ROI method, the beam mask method improved the agreement of DVH indices for both targets and OARs and the sliding window method further improved the agreement of the DVH indices (for lung cancer, CTV D98 absolute deviation: 0.74 ± 0.18 vs. 0.57 ± 0.21 vs. 0.54 ± 0.15 Gy[RBE], ROI vs. beam mask vs. sliding window methods, respectively). For the 3D Gamma passing rates in the target, OARs, and BODY (outside target and OARs), the beam mask method improved the passing rates in these regions and the sliding window method further improved them (for prostate cancer, targets: 96.93% ± 0.53% vs. 98.88% ± 0.49% vs. 99.97% ± 0.07%, BODY: 86.88% ± 0.74% vs. 93.21% ± 0.56% vs. 95.17% ± 0.59%). A similar trend was also observed for the dice coefficients. This trend was especially remarkable for relatively low prescription isodose lines (for lung cancer, 10% isodose line dice: 0.871 ± 0.027 vs. 0.911 ± 0.023 vs. 0.927 ± 0.017). The dose predictions for all the testing cases were completed within 0.25 s.ConclusionsAn accurate and efficient deep learning‐augmented proton dose prediction framework has been developed for PBSPT, which can predict accurate dose distributions not only inside but also outside ROI efficiently. The framework can potentially further reduce the initial planning and adaptive replanning workload in PBSPT.