[Introduction] Despite the unmet need for management of chronic kidney disease (CKD), the prevalence of CKD among patients visiting a university hospital general medicine department (UHGMD) is unknown. Thus, we performed a study to evaluate the prevalence of CKD in UHGMD patients. [Methods] The participants were patients who visited the Department of General Medicine and Emergency Care at the Toho University Omori Medical Center from 2018 to 2021 as a surrogate of the “UHGMD population” and public data of health checkups in the Metropolitan Southern Region as a surrogate of the “community population.” We also compared our data and previously reported data. [Results] The data of 8,545 and 117,971 participants were evaluated as UHGMD and community populations, respectively. The comparison between UHGMD and the community population revealed that the prevalence of CKD in UHGMD patients (15.2%) was 1.4 times that in the community population (10.6%). The prevalence of CKD in UHGMD patients in this study was intermediate between the prevalence in patients managed by nephrologists (20.6%) and in the community population (4.2-16.2%). [Conclusions] The prevalence of CKD in UHGMD patients may reflect the hospital population before nephrologists are involved.

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Although many predictive models of falls have been developed, there are no firmly established and widely used predictive models of falls for health care settings in Japan. In this review, we elucidate the features of existing fall predictive models and compare them with our independently developed in-hospital fall predictive model, which includes Bedriddenness ranks (Saga Fall Risk Model 2, SFRM2). We conducted a narrative review after searching PubMed to identify studies on the development and/or validation of fall predictive models. We describe the outcomes, study participants, related factors, and development methods in those studies. A comparison was made with our developed SFRM2 and its features were analyzed. The reported fall predictive models exhibit considerable diversity in the number of items, evaluation methods, and model area under the receiving operator characteristic curve, with no consistent trends. Compared with previously developed fall prediction models, the SFRM2 only comprises eight items, allowing for simplified assessment through questionnaire-based inquiry without additional in-depth assessment upon admission.

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