Updates in the Role of Checkpoint Inhibitor Immunotherapy in Classical Hodgkin's Lymphoma.

Classical Hodgkin's lymphoma is a highly curable disease, but 10-25% of patients with higher-risk disease relapse. The introduction of checkpoint inhibitors (CPIs) targeting PD-1 have changed the landscape of treatment for patients with relapsed/refractory disease to multiple lines of therapy. The depth of response to CPI as a monotherapy is highest in the first relapse as salvage therapy based on outcomes reported in several phase II studies. With earlier use of CPI and brentuximab vedotin, the optimal sequencing of therapy is evolving. In this review, we will summarize clinical investigation of anti-PD-1 mAb in earlier line settings to provide insights on utilizing these agents as chemotherapy- and radiation-sparing approaches, increasing depth of response, and as part of combination regimens.

An outpatient telehealth elective for displaced clinical learners during the COVID-19 pandemic.

BACKGROUND: In response to the COVID-19 pandemic, medical schools suspended clinical rotations. This displacement of medical students from wards has limited experiential learning. Concurrently, outpatient practices are experiencing reduced volumes of in-person visits and are shifting towards virtual healthcare, a transition that comes with its own logistical challenges. This article describes a workflow that enabled medical students to engage in meaningful clinical education while helping an institution's outpatient practices implement remote telemedicine visits. METHODS: A 4-week virtual elective was designed to allow clinical learners to participate in virtual telemedicine patient encounters. Students were prepared with EMR training and introduced to a novel workflow that supported healthcare providers in the outpatient setting. Patients were consented to telehealth services before encounters with medical students. All collected clinical information was documented in the EMR, after which students transitioned patients to a virtual Doxy.me video appointment. Surveys were used to evaluate clinical and educational outcomes of students' participation. Elective evaluations and student reflections were also collected. RESULTS: Survey results showed students felt well-prepared to initiate patient encounters. They expressed comfort while engaging with patients virtually during telemedicine appointments. Students identified clinical educational value, citing opportunities to develop patient management plans consistent with in-person experiences. A significant healthcare burden was also alleviated by student involvement. Over 1000 total scheduled appointments were serviced by students who transitioned more than 80 % of patients into virtual attending provider waiting rooms. CONCLUSIONS: After piloting this elective with fourth-year students, pre-clerkship students were also recruited to act in a role normally associated with clinical learners (e.g., elicit patient histories, conduct a review of systems, etc.). Furthermore, additional telemedicine electives are being designed so medical students can contribute to patient care without risk of exposure to COVID-19. These efforts will allow students to continue with their clinical education during the pandemic. Medical educators can adopt a similar workflow to suit evolving remote learning needs.

A Simple Scoring Tool to Predict Medical Intensive Care Unit Readmissions Based on Both Patient and Process Factors.

BACKGROUND: Although many predictive models have been developed to risk assess medical intensive care unit (MICU) readmissions, they tend to be cumbersome with complex calculations that are not efficient for a clinician planning a MICU discharge. OBJECTIVE: To develop a simple scoring tool that comprehensively takes into account not only patient factors but also system and process factors in a single model to predict MICU readmissions. DESIGN: Retrospective chart review. PARTICIPANTS: We included all patients admitted to the MICU of Robert Wood Johnson University Hospital, a tertiary care center, between June 2016 and May 2017 except those who were < 18 years of age, pregnant, or planned for hospice care at discharge. MAIN MEASURES: Logistic regression models and a scoring tool for MICU readmissions were developed on a training set of 409 patients, and validated in an independent set of 474 patients. KEY RESULTS: Readmission rate in the training and validation sets were 8.8% and 9.1% respectively. The scoring tool derived from the training dataset included the following variables: MICU admission diagnosis of sepsis, intubation during MICU stay, duration of mechanical ventilation, tracheostomy during MICU stay, non-emergency department admission source to MICU, weekend MICU discharge, and length of stay in the MICU. The area under the curve of the scoring tool on the validation dataset was 0.76 (95% CI, 0.68-0.84), and the model fit the data well (Hosmer-Lemeshow p = 0.644). Readmission rate was 3.95% among cases in the lowest scoring range and 50% in the highest scoring range. CONCLUSION: We developed a simple seven-variable scoring tool that can be used by clinicians at MICU discharge to efficiently assess a patient's risk of MICU readmission. Additionally, this is one of the first studies to show an association between MICU admission diagnosis of sepsis and MICU readmissions.