During the COVID-19 pandemic, social interactions were restricted, including community services for disabled older adults. This study aimed to describe the change of use in community services related to long-term care insurance (LTCI) during the pandemic in Japan. A retrospective descriptive study was conducted using data collected via a cloud-based management support platform for older adult care provider “Kaipoke”, by a private-sector company “SMS Co., Ltd.”, in which care-managers of LTCI manage their office work. Data collection occurred from July 2019 to June 2020. Study subjects were LTCI service users aged 65 years and above. Subjects were living at home. We examined changes in the number of users of LTCI services before and after the COVID-19 pandemic began, using an interrupted time-series analysis. Results indicated that the use of outpatient services was reduced; however, home-visit services were maintained. The decrease in use was significant in the seven prefectures where the infection initially spread. There are concerns that older adults or surrounding caregivers can be affected by such changes in LTC service use. It is therefore necessary to implement sustainable measures from a long-term perspective and investigate their influence as part of future studies.
Confounding adjustment is important for observational studies to derive valid effect estimates for inference. Despite the theoretical advancement of confounding selection procedure, it is often challenging to distinguish between confounders and mediators due to the lack of information about the time-ordering and latency of each variable in the data. This is also the case for the studies of perfluoroalkyl substances (PFAS), a group of synthetic chemicals used in industry and consumer products that are persistent and have endocrine-disrupting properties on health outcomes. In this article, we used directed acyclic graphs to describe potential biases introduced by adjusting for or stratifying by the measure of obesity as an intermediate variable in PFAS exposure analyses. We compared results with or without adjusting for body mass index in two cross-sectional data analyses: (1) PFAS levels and maternal thyroid function during early pregnancy using the Danish National Birth Cohort and (2) PFAS levels and cardiovascular disease in adults using the National Health and Nutrition Examination Survey. In these examples, we showed that the potential heterogeneity observed in stratified analyses by overweight or obese status needs to be interpreted cautiously considering collider stratification bias. This article highlights the complexity of seemingly simple adjustment or stratification analyses, and the need for careful consideration of the confounding and/or mediating role of obesity in PFAS studies.
Aim: To find more effective criteria to identify clinically significant urological anomalies after initial urinary tract infection among children. Methods:Children aged 2-24 months with an initial urinary tract infection were consecutively recruited in a Japanese hospital from 2013 to 2019. Voiding cystourethrography, 99mTc dimercaptosuccinic acid scan and ultrasound were intended to perform for all cases. Clinically significant urological anomalies were defined as high-grade vesicoureteral reflux, obstructive and abnormal urinary tract lesions, need for surgical intervention, renal hypoplasia and scarring. Using classification and regression tree analysis, we sought the associated factors. We developed new criteria with these factors, retrospectively applied them to the original data, and calculated the sensitivity and specificity.Results: One hundred sixty-seven patients were eligible, and 39 had clinically significant urological anomalies. Classification and regression tree analysis showed that the associated factors were non-E. coli infections, serum creatinine levels and ultrasound abnormalities. When the gold standards were performed on children with non-E. coli infections or serum creatinine levels ≥0.21 mg/dl, sensitivity and specificity were 0.82 and 0.68, respectively. Conclusion:The criteria including non-E. coli infections and high-normal or higher serum creatinine levels may efficiently predict clinically significant urological anomalies after initial urinary tract infections.
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