Association of repeated high serum osmolarity with cognitive function in older Japanese adults in a KOBE study subanalysis
Bibliographic record
Abstract
The relationship between serum osmolarity and cognitive function has not been fully characterized. This study aimed to examine the cross-sectional association between repeated high serum osmolarity and cognitive performance among elderly community residents. We performed a subanalysis of the Kobe Orthopedic and Biomedical Epidemiological Study, including residents aged ≥ 75 years who completed the Japanese Montreal Cognitive Assessment (MoCA-J) in 2016-2017 (n = 127), 2018-2019 (n = 71), and 2020 (n = 16). Serum osmolarity was obtained from the data in the 2012-2013 survey and in the 2016-2017 survey. MoCA-J scores were dichotomized at ≤ 22 versus > 22. Multivariate logistic regression adjusted for demographic, lifestyle including daily non-alcohol drink intake, seasonal, and clinical covariates to assess associations between osmolarity status and cognitive group. Among 214 participants (mean age 76.2 ± 1.3 years; 56% female), high osmolarity (≥ 300 mOsm/L) in 2012-2013 was associated with MoCA-J ≤ 22 (OR 2.67, 95% CI 1.29-5.53, p = 0.008). A similar association emerged for 2016-2017 measurements (OR 6.12, 95% CI 1.46-25.61, p = 0.013). Participants with high serum osmolarity at both time points showed a stronger cross-sectional association with lower MoCA-J scores (OR 17.64, 95% CI = 1.8-184.83, p = 0.017). No significant association was observed between daily non-alcoholic drink (NAD) intake and either MoCA-J scores or serum osmotic pressure. Repeated high serum osmolarity was cross-sectionally associated with lower cognitive performance in Japanese community-dwelling older adults. While NAD intake showed no significant association, further research is needed to explore the potential role of serum osmolarity in cognitive health. These findings warrant confirmation in larger prospective studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".