A team-based learning model using clinical vignettes in an advanced undergraduate pre-health professional physiology course facilitated by medical students.

There is evidence that demonstrates that teaching preclinical and clinical material can have numerous benefits for both students and teachers, with the majority of literature focusing on peer medical student teaching. There is a dearth of literature exploring the benefit of medical students teaching undergraduate, pre-health professional students and using clinical cases in this setting. We explore our implementation of a team-based learning curriculum built around clinical cases to teach advanced physiology and introduce pathology, pharmacology, and interprofessional collaboration for pre-health students. This course was entirely taught by medical students. Course evaluations and future implications are discussed.

Using artificial intelligence to risk stratify COVID-19 patients based on chest X-ray findings.

BACKGROUND: Deep learning-based radiological image analysis could facilitate use of chest x-rays as a triaging tool for COVID-19 diagnosis in resource-limited settings. This study sought to determine whether a modified commercially available deep learning algorithm (M-qXR) could risk stratify patients with suspected COVID-19 infections. METHODS: A dual track clinical validation study was designed to assess the clinical accuracy of M-qXR. The algorithm evaluated all Chest-X-rays (CXRs) performed during the study period for abnormal findings and assigned a COVID-19 risk score. Four independent radiologists served as radiological ground truth. The M-qXR algorithm output was compared against radiological ground truth and summary statistics for prediction accuracy were calculated. In addition, patients who underwent both PCR testing and CXR for suspected COVID-19 infection were included in a co-occurrence matrix to assess the sensitivity and specificity of the M-qXR algorithm. RESULTS: 625 CXRs were included in the clinical validation study. 98% of total interpretations made by M-qXR agreed with ground truth (p = 0.25). M-qXR correctly identified the presence or absence of pulmonary opacities in 94% of CXR interpretations. M-qXR's sensitivity, specificity, PPV, and NPV for detecting pulmonary opacities were 94%, 95%, 99%, and 88% respectively. M-qXR correctly identified the presence or absence of pulmonary consolidation in 88% of CXR interpretations (p = 0.48). M-qXR's sensitivity, specificity, PPV, and NPV for detecting pulmonary consolidation were 91%, 84%, 89%, and 86% respectively. Furthermore, 113 PCR-confirmed COVID-19 cases were used to create a co-occurrence matrix between M-qXR's COVID-19 risk score and COVID-19 PCR test results. The PPV and NPV of a medium to high COVID-19 risk score assigned by M-qXR yielding a positive COVID-19 PCR test result was estimated to be 89.7% and 80.4% respectively. CONCLUSION: M-qXR was found to have comparable accuracy to radiological ground truth in detecting radiographic abnormalities on CXR suggestive of COVID-19.

Structured Reporting: An Intervention to Improve Procedure Documentation in Breast Imaging.

OBJECTIVE: To evaluate intervention of structured reporting after wrong-site surgery that occurred after localization of an incorrect breast biopsy marker. METHODS: An IRB-exempt retrospective database review identified patients who underwent core-needle biopsy of a breast lesion from July 1, 2014 to July 1, 2020. They were divided into three cohorts: 2014 pre-intervention/pre-sentinel, 2017 pre-intervention/post-sentinel, and 2019 post-intervention of structured reports. One hundred reports per cohort were reviewed for documentation of marker and shape. Statistical analysis was performed with mixed-effects logistic regression model and chi-squared test with P < 0.05 considered significant. RESULTS: The 2014 cohort consisted of 100 patients with 122 biopsies. Twenty-seven (22.1%) were excluded: 5/122 (4.1%) lesion resolution, 22/122 (18.0%) no documentation whether marker was/was not placed. Of the 95 biopsies remaining, 4/95 (4.2%) had no marker placed, 62/95 (65.3%) reported marker only, and 29/95 (30.5%) reported marker and shape. In the 2017 cohort, 100 patients underwent 108 biopsies. Four/108 (3.7%) were excluded: lesion resolution. Of the 104, 10/104 (9.6%) had no marker placed, 22/104 (21.2%) reported marker only, and 72/104 (69.2%) reported marker and shape. In the 2019 cohort, 100 patients underwent 114 biopsies. Two/114 (1.8%) were excluded: lesion resolution. Of the 112, 3/112 (2.7%) had no marker placed, 3/112 (2.7%) reported marker only, and 106/112 (94.6%) reported marker and shape. The predicted probability of both marker placement and shape described were statistically greater for 2019 compared to the other cohorts (P < 0.05). CONCLUSION: Using structured reports facilitates and improves documentation of breast biopsy markers and may potentially reduce the risk of medical errors.

Necrobiotic Xanthogranuloma on 18F-FDG PET/CT.

We report the case of a 57-year-old man who presented with a 6-year history of yellowish plaques on his left buttock and right medial knee, as well as ulcerating subcutaneous nodules on his forearms bilaterally. Skin biopsy, bone biopsy, and serum protein electrophoresis confirmed the diagnosis of necrobiotic xanthogranuloma with associated monoclonal gammopathy. Necrobiotic xanthogranuloma is a rare form of non-Langerhans histiocytosis characterized by development of chronic cutaneous nodules that enlarge over time to form plaques. The author discusses necrobiotic xanthogranuloma's presentation and the utility of F-FDG PET/CT in disease staging, localizing optimal biopsy sites, and assessing treatment response.

Laryngeal tuberculosis mimicking malignancy: A case report.

Laryngeal involvement in tuberculosis is rare and may mimic malignancy. We report the case of a 26-year-old female who presented with sore throat for several months. CT revealed an infiltrative laryngeal mass and upper lobe pulmonary opacities. Laryngoscopic biopsy confirmed necrotizing granulomatous inflammation with positive culture for Mycobacterium tuberculosis.