Lost in translation: Unveiling medical students' untold errors of medical history documentation.

OBJECTIVE: The accurate documentation of a medical history interview is an important goal in medical education. As students' documentation of medical history interviews is mostly decentralised on the wards, a systematic assessment of documentation quality is missing. We therefore evaluated the extent of details missed in students' medical history reports in a standardised setting. METHODS: In this prospective, observational study, 123 of 380 students (32.4%) participated in an Objective Structured Clinical Examination (OSCE) regarding history taking and documentation. Based on the interviews and nine deductively selected main categories, a categorical system was established using a summarising qualitative content analysis. The items in the transcripts (defined as ground truth) and in students' reports were labelled and assigned to the correct subcategory. The ground truth and students' reports were compared to quantify students' documentation completeness. RESULTS: Next to the nine deductively selected main categories, 61 subcategories were defined. A total of 8943 items were labelled in the 123 interview transcripts (ground truth), compared with 5870 items labelled in students' reports (65.6% completeness of students' reports compared with ground truth). The main category personal details overlapped with 94.2% between students' report and ground truth in contrast to the main category with the highest discrepancy, allergy, with 41.1% overlap. Pertinent negative items and non-numerical quantifications were often missed. CONCLUSIONS: Medical students show incomplete documentation of medical history interviews. Therefore, accurate documentation should be taught as an important goal in medical education.

Guideline-Based Cardiovascular Risk Assessment Delivered by an mHealth App: Development Study.

BACKGROUND: Identifying high-risk individuals is crucial for preventing cardiovascular diseases (CVDs). Currently, risk assessment is mostly performed by physicians. Mobile health apps could help decouple the determination of risk from medical resources by allowing unrestricted self-assessment. The respective test results need to be interpretable for laypersons. OBJECTIVE: Together with a patient organization, we aimed to design a digital risk calculator that allows people to individually assess and optimize their CVD risk. The risk calculator was integrated into the mobile health app HerzFit, which provides the respective background information. METHODS: To cover a broad spectrum of individuals for both primary and secondary prevention, we integrated the respective scores (Framingham 10-year CVD, Systematic Coronary Risk Evaluation 2, Systematic Coronary Risk Evaluation 2 in Older Persons, and Secondary Manifestations Of Arterial Disease) into a single risk calculator that was recalibrated for the German population. In primary prevention, an individual's heart age is estimated, which gives the user an easy-to-understand metric for assessing cardiac health. For secondary prevention, the risk of recurrence was assessed. In addition, a comparison of expected to mean and optimal risk levels was determined. The risk calculator is available free of charge. Data safety is ensured by processing the data locally on the users' smartphones. RESULTS: Offering a risk calculator to the general population requires the use of multiple instruments, as each provides only a limited spectrum in terms of age and risk distribution. The integration of 4 internationally recommended scores allows risk calculation in individuals aged 30 to 90 years with and without CVD. Such integration requires recalibration and harmonization to provide consistent and plausible estimates. In the first 14 months after the launch, the HerzFit calculator was downloaded more than 96,000 times, indicating great demand. Public information campaigns proved effective in publicizing the risk calculator and contributed significantly to download numbers. CONCLUSIONS: The HerzFit calculator provides CVD risk assessment for the general population. The public demonstrated great demand for such a risk calculator as it was downloaded up to 10,000 times per month, depending on campaigns creating awareness for the instrument.

Characteristics and quality assessment of online mentoring profile texts in academic medical mentoring.

BACKGROUND: Mentoring is important for a successful career in academic medicine. In online matching processes, profile texts are decisive for the mentor-selection. We aimed to qualitatively characterize mentoring-profile-texts, identify differences in form and content and thus elements that promote selection. METHODS: In a mixed method study first, quality of texts in 150 selected mentoring profiles was evaluated (10-point Likert scale; 1 = insufficient to 10 = very good). Second, based on a thematic and content analysis approach of profile texts, categories and subcategories were defined. We compared the presence of the assigned categories between the 25% highest ranked profiles with the 25% lowest ranked ones. Finally, additional predefined categories (hot topics) were labelled on the selected texts and their impact on student evaluation was statistically examined. RESULTS: Students rated the quality of texts with a mean of 5.89 ± 1.45. 5 main thematic categories, 21 categories and a total of 74 subcategories were identified. Ten subcategories were significantly associated with high- and four with low-rated profiles. The presence of three or more hot topics in texts significantly correlated with a positive evaluation. CONCLUSION: The introduced classification system helps to understand how mentoring profile texts are composed and which aspects are important for choosing a suited mentor.

Online medical history taking course: Opportunities and limitations in comparison to traditional bedside teaching.

Objective: Obtaining a systematic medical history (MH) from a patient is a core competency in medical education and plays a vital role in the diagnosis of diseases. At the Faculty of Medicine at LMU Munich, students have their first course in MH taking during their second year. Due to the COVID-19 pandemic, the traditional bedside MH taking course had to be transformed into an online course (OC). Our objectives were to implement an online MH taking course, to evaluate its feasibility and to compare the evaluation results to a historic cohort that had undertaken the traditional bedside teaching course (BTC). Methods: 874 second-year students participated in the OC (BTC=827). After teaching the theoretical background via asynchronous online lectures, students participated in a practical exercise with fellow students using the video communication platform Zoom where they were able to practice taking a MH on the basis of fictitious, text-based patient cases. Students were then asked to evaluate the course through a standardized online survey with 31 questions on teaching quality and self-perceived learning success, which had also been used in previous years. The survey results were compared to the results of the historic cohort using the Mann-Whitney U test. Results: A total of n=162 students (18.5%) evaluated the OC. In the historic cohort, n=252 (30.5%) completed the survey. 85.3% of the OC respondents thought that the atmosphere during the practical exercise was productive and 83.0% greatly appreciated the flexibility in terms of time management. Moreover, they appreciated the online resources as well as having the opportunity to undertake a MH taking course during the COVID-19 pandemic. 27.7% of the respondents thought that traditional BTCs should be supplemented through more online activities in the future. With respect to the ability of independently taking a MH upon completion of the course, the OC was rated significantly lower relative to the BTC (mean OC=2.4, SD=±1.1 vs. mean BTC=1.9, SD=±1.1 (1=strongly agree; 5=strongly disagree); p<0.0001). Conclusion: OCs are a feasible format and seem to convey the theory and practical implementation in a peer-exercise format of MH taking to medical students. The theoretical background can be acquired with great flexibility. Nevertheless, the students' self-appraisal suggested that the traditional teaching format was more effective at teaching MH taking skills. Thus, we propose a blended learning concept, combining elements of both formats. In this context, we suggest prospective, randomized trials to evaluate blended learning approaches.

Only Hyperuricemia with Crystalluria, but not Asymptomatic Hyperuricemia, Drives Progression of Chronic Kidney Disease.

BACKGROUND: The roles of asymptomatic hyperuricemia or uric acid (UA) crystals in CKD progression are unknown. Hypotheses to explain links between UA deposition and progression of CKD include that (1) asymptomatic hyperuricemia does not promote CKD progression unless UA crystallizes in the kidney; (2) UA crystal granulomas may form due to pre-existing CKD; and (3) proinflammatory granuloma-related M1-like macrophages may drive UA crystal-induced CKD progression. METHODS: MALDI-FTICR mass spectrometry, immunohistochemistry, 3D confocal microscopy, and flow cytometry were used to characterize a novel mouse model of hyperuricemia and chronic UA crystal nephropathy with granulomatous nephritis. Interventional studies probed the role of crystal-induced inflammation and macrophages in the pathology of progressive CKD. RESULTS: Asymptomatic hyperuricemia alone did not cause CKD or drive the progression of aristolochic acid I-induced CKD. Only hyperuricemia with UA crystalluria due to urinary acidification caused tubular obstruction, inflammation, and interstitial fibrosis. UA crystal granulomas surrounded by proinflammatory M1-like macrophages developed late in this process of chronic UA crystal nephropathy and contributed to the progression of pre-existing CKD. Suppressing M1-like macrophages with adenosine attenuated granulomatous nephritis and the progressive decline in GFR. In contrast, inhibiting the JAK/STAT inflammatory pathway with tofacitinib was not renoprotective. CONCLUSIONS: Asymptomatic hyperuricemia does not affect CKD progression unless UA crystallizes in the kidney. UA crystal granulomas develop late in chronic UA crystal nephropathy and contribute to CKD progression because UA crystals trigger M1-like macrophage-related interstitial inflammation and fibrosis. Targeting proinflammatory macrophages, but not JAK/STAT signaling, can attenuate granulomatous interstitial nephritis.