YUPENG HE

Background Research on the influence of heart failure on mortality after Alzheimer's disease diagnosis is limited. Objective To evaluate the association between comorbid heart failure and mortality following Alzheimer's disease diagnosis, particularly considering sex differences. Methods We analyzed administrative claims data from Japan, involving 32,363 individuals (11,064 men and 21,299 women) aged 75 or older newly diagnosed with Alzheimer's disease, with 7% having comorbid heart failure. Cox proportional hazard models and population attributable fractions (PAFs) were used to evaluate the association between comorbid heart failure and mortality within one year following Alzheimer's disease diagnosis. Results Individuals with Alzheimer's disease and heart failure had a multivariate-adjusted hazard ratio of 1.51 (95% confidence interval [CI], 1.32–1.73) for mortality during the one-year follow-up period compared to those with Alzheimer's disease and without heart failure. Subgroup analysis by sex revealed a higher mortality hazard ratio in women of 1.63 (95% CI, 1.36–1.95) than that in men of 1.39 (95% CI, 1.13–1.71). Further age and sex subgroup analysis indicated that women across all age brackets—75–79, 80–84, and ≥ 85 years—had higher mortality hazard ratios. The PAF for heart failure increased with age in both sexes, with women having higher PAFs than men, and the sex difference in PAF being most pronounced in the 75–79 age category (men: 1.4%, women: 4.0%). Conclusions Hazard ratios and PAFs for mortality associated with comorbid heart failure in newly diagnosed Alzheimer's disease are higher in women than in men, which persists across all age subgroups.

Objectives We evaluated the number of hospitalizations among public assistance recipients for each major classification according to the International Classification of Diseases 10th Revision (ICD-10), adjusting for sex and age differences in the general Japanese population. This study aimed to provide a comprehensive assessment of hospitalization patterns among public assistance recipients by disease category.Methods We used indirect methods to adjust for sex and age, with public assistance recipients and the entire Japanese population as the observation and reference groups, respectively. We calculated the standardized hospitalization ratios (SHRs) for each major classification based on the ICD-10. We only used publicly available government statistics, including data from the 2020 Patient Survey, for hospitalization rates according to sex, age, and major classification. Additionally, we used data from the 2020 National Survey on Public Assistance Recipients conducted for the number of public assistance recipients by sex and age groups and data from the 2020 Survey on the Actual Status of Medical Assistance conducted for the number of hospitalizations by major classification.Results After adjusting for age, the overall SHR was 1.49. The major classifications with the high SHRs for men and women were "V. Mental and behavioural disorders" (SHR for men; 4.06, women; 3.45) and "IV. Endocrine, nutritional, and metabolic diseases" (SHR for men; 2.40, women; 1.47). Conversely, the major classifications with low SHRs were "XVI. Certain conditions originating in the perinatal period" (SHR; 0.43) and "VII. Diseases of the eye and adnexa" (SHR; 0.44) for men. For women, these were "XV. Pregnancy, childbirth, and the puerperium" (SHR; 0.17) and "VII. Diseases of the eye and adnexa" (SHR; 0.27).Conclusion After adjusting for age, hospitalization status among public assistance recipients was higher overall than in the general Japanese population. However, if divided based on major classifications, higher and lower rates were observed compared with the general population. In assessing the status of medical assistance for public assistance recipients, research should be conducted by disease classification, considering the significant differences in age composition between public assistance recipients and the general Japanese population.

BACKGROUND: Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from hospitals and self-reported physician diagnoses or typical schizophrenia symptoms. These approaches are likely to underestimate the true prevalence owing to stigma, poor insight, or lack of access to health care among respondents. To address these issues, we previously developed an artificial neural network (ANN)-based schizophrenia classification model (SZ classifier) using data from a large-scale Japanese web-based survey to enhance the comprehensiveness of schizophrenia case identification in the general population. In addition, we also plan to introduce a population-based survey to collect general information and sample participants matching the population's demographic structure, thereby achieving a precise estimate of the prevalence of schizophrenia in Japan. OBJECTIVE: This study aimed to estimate the prevalence of schizophrenia by applying the SZ classifier to random samples from the Japanese population. METHODS: We randomly selected a sample of 750 participants where the age, sex, and regional distributions were similar to Japan's demographic structure from a large-scale Japanese web-based survey. Demographic data, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities were collected and applied to the SZ classifier, as this information was also used for developing the SZ classifier. The crude prevalence of schizophrenia was calculated through the proportion of positive cases detected by the SZ classifier. The crude estimate was further refined by excluding false-positive cases and including false-negative cases to determine the actual prevalence of schizophrenia. RESULTS: Out of 750 participants, 62 were classified as schizophrenia cases by the SZ classifier, resulting in a crude prevalence of schizophrenia in the general population of Japan of 8.3% (95% CI 6.6%-10.1%). Among these 62 cases, 53 were presumed to be false positives, and 3 were presumed to be false negatives. After adjustment, the actual prevalence of schizophrenia in the general population was estimated to be 1.6% (95% CI 0.7%-2.5%). CONCLUSIONS: This estimated prevalence was slightly higher than that reported in previous studies, possibly due to a more comprehensive disease classification methodology or, conversely, model limitations. This study demonstrates the capability of an ANN-based model to improve the estimation of schizophrenia prevalence in the general population, offering a novel approach to public health analysis.

Aim Japan faces a public health challenge of dementia, further complicated by the increasing complications from diabetes within its rapidly aging population. This study assesses the impact of diabetes on mortality and hospitalization among individuals aged ≥75 years with new dementia diagnoses. Methods We analyzed administrative claims data in Japan from 73 324 individuals aged ≥75 years with dementia, of whom 17% had comorbid diabetes. Dementia and diabetes were identified from the International Classification of Diseases, Tenth Revision codes. We used Kaplan–Meier survival analysis, Cox proportional hazards analysis, and population attributable fractions (PAFs) to evaluate the impact on mortality and hospitalization after dementia diagnosis. Results One‐year mortality and 1‐year hospitalization probabilities in individuals with dementia and diabetes (10.3% and 31.7%, respectively) were higher than those without diabetes (8.3% and 25.4%, respectively). The adjusted hazard ratios for individuals with diabetes, as compared to those without, were 1.126 (95% confidence interval [CI], 1.040–1.220) for mortality and 1.191 (95% CI, 1.140–1.245) for hospitalization. The PAFs from the comorbidity of dementia and diabetes were 2.2% for mortality and 3.1% for hospitalization. Subgroup analysis showed that the PAFs were highest in men aged 75–79 years and women aged 80–84 years for mortality and in individuals aged 75–79 for hospitalization. Conclusion During the early postdiagnosis period, comorbid diabetes increases mortality and hospitalization risks in older adults with dementia. The variation in disease burden across age groups underscores the need for age‐specific health care strategies to manage comorbid diabetes in individuals with dementia. Geriatr Gerontol Int 2024; 24: 773–781.