Usability of the Japanese Late-Stage Elderly Questionnaire for screening major depression.

BACKGROUND: Older adults with major depression are at risk of frailty and long-term care needs. Consequently, screening for major depression is imperative to prevent such risks. In Japan, the Late-Stage Elderly Questionnaire was developed to evaluate older adults' holistic health, including mental well-being. It comprises one specific question to gauge life satisfaction, but the effectiveness of this question to screen for major depression remains unclear. Therefore, we aimed to assess the usability of this question to screen for major depression. METHODS: This retrospective cohort study used a large, commercially available claims database in Japan. Participants were older adults aged ≥75 years who completed the Late-Stage Elderly Questionnaire and were classified with and without new major depression within 1 year. We evaluated the questionnaire's ability to screen for major depression using C-statistics, developing three models to assess the cut-off value based on responses to the life satisfaction question ('Satisfied', 'Somewhat satisfied', 'Somewhat unsatisfied', or 'Unsatisfied'), estimating the sensitivity and specificity of each model. RESULTS: Among 11 117 older adults, 77 newly experienced major depression within 1 year. The C-statistic for screening major depression was 0.587. The model setting the cut-off between 'Somewhat unsatisfied' and 'Unsatisfied' the demonstrated lowest sensitivity and highest specificity, while the model setting the cut-off between 'Satisfied' and 'Somewhat satisfied' demonstrated highest sensitivity and lowest specificity. CONCLUSIONS: Our results suggest that due to its poor screening ability and high rate of false negatives, the question assessing life satisfaction in the Late-Stage Elderly Questionnaire may not be useful for screening major depression in older adults and may require modification.

Association between subjective physical function and occurrence of new fractures in older adults: A retrospective cohort study.

BACKGROUND: The Late-Stage Elderly Questionnaire has been incorporated into health assessments for older adults in Japan, encompassing three self-administered questions on subjective physical function: subjective gait speed decline, recent fall history, and exercise habits. Nevertheless, its efficacy in predicting new fracture occurrences remains uncertain. METHODS: This retrospective cohort study utilized Japan's DeSC database, a large commercially available claims database. Participants were older adults aged ≥75 years and provided complete responses to the Late-Stage Elderly Questionnaire at health check-ups. We performed two Cox regression analyses for new fractures based on the responses to the three questions (Model 1) and on age, sex, and responses to the three questions (Model 2). The predictive abilities of the 1-year occurrence of new fractures were compared between the two models. RESULTS: Of 11 683 eligible older adults, 927 (7.93%) experienced new fractures. Model 1 revealed significant associations between new fractures and subjective gait speed decline (hazard ratio [HR], 1.63; 95% confidence interval [CI], 1.40-1.89), recent fall history (HR, 2.03; 95% CI, 1.77-2.33), and absence of exercise habits (HR, 1.29; 95% CI, 1.13-1.47). Model 2 demonstrated superior predictive ability (area under the curve, 0.677; 95% CI, 0.659-0.695) compared with Model 1 (area under the curve, 0.633; 95% CI, 0.614-0.652), with a net reclassification improvement of 0.383 (95% CI, 0.317-0.449). CONCLUSION: Three subjective physical well-being factors were significantly associated with new fracture development in older adults. These results suggest that the three-question assessment may be a valuable screening tool for identifying new fractures. Geriatr Gerontol Int 2024; 24: 337-343.

Dengue Early Warning System as Outbreak Prediction Tool: A Systematic Review.

Early warning system (EWS) for vector-borne diseases is incredibly complex due to numerous factors originating from human, environmental, vector and the disease itself. Dengue EWS aims to collect data that leads to prompt decision-making processes that trigger disease intervention strategies to minimize the impact on a specific population. Dengue EWS may have a similar structural design, functions, and analytical approaches but different performance and ability to predict outbreaks. Hence, this review aims to summarise and discuss the evidence of different EWSs, their performance, and their ability to predict dengue outbreaks. A systematic literature search was performed of four primary databases: Scopus, Web of Science, Ovid MEDLINE, and EBSCOhost. Eligible articles were evaluated using a checklist for assessing the quality of the studies. A total of 17 studies were included in this systematic review. All EWS models demonstrated reasonably good predictive abilities to predict dengue outbreaks. However, the accuracy of their predictions varied greatly depending on the model used and the data quality. The reported sensitivity ranged from 50 to 100%, while specificity was 74 to 94.7%. A range between 70 to 96.3% was reported for prediction model accuracy and 43 to 86% for PPV. Overall, meteorological alarm indicators (temperatures and rainfall) were the most frequently used and displayed the best performing indicator. Other potential alarm indicators are entomology (female mosquito infection rate), epidemiology, population and socioeconomic factors. EWS is an essential tool to support district health managers and national health planners to mitigate or prevent disease outbreaks. This systematic review highlights the benefits of integrating several epidemiological tools focusing on incorporating climatic, environmental, epidemiological and socioeconomic factors to create an early warning system. The early warning system relies heavily on the country surveillance system. The lack of timely and high-quality data is critical for developing an effective EWS.