Association between mean corpuscular volume and cognitive impairment in an 8‐year cohort study in the community‐dwelling elderly
Bibliographic record
Abstract
Abstract Background Mean corpuscular volume (MCV) is the average volume of red blood cells (RBC). Larger MCV reduces the amount of RBC reaching the brain, while smaller MCV was associated with iron‐deficiency anemia and the subsequent cognitive impairment. Few studies have relating MCV levels to cognitive impairment and their findings were inconsistent. This study aimed to explore this association in community‐dwelling older adults. Method This study is part of an ongoing cohort study Taiwan Initiatives for Geriatric Epidemiological Research (TIGER, 2011‐ present). A total of 605 non‐demented older adults (age 65+) were recruited at baseline (2011‐2013). After exclusion of participants with dementia at baseline, history of stroke, brain tumor, loss of consciousness, missing data of MCV, 319 elderly were included for analysis. Global and domain‐specific cognition (logical memory, attention, verbal fluency, and executive function) were assessed for each participant at baseline, 2‐year, 4‐year, and 6‐year follow‐ups. MCV was assessed at baseline and then tertitled; high MCV indicates the highest tertile (≥92.7 fL); low MCV indicates the lower tertiles (<92.6 fL). The generalized linear mixed models (GLMM) were used to estimate the association between MCV and cognitive impairment adjusted for important covariates. Result At baseline, the mean age of the study participants was 71.6 years old and the mean MCV at baseline was 90.7 fL. For the multivariable analyses, the effect of baseline MCV on global cognition (assessed by Montreal Cognitive Assessment–Taiwanese version, MoCA‐T) increased as age increased [MCV×age interaction: β= ‐0.07, 90% confidence interval (CI)= ‐0.14 to ‐0.004, p‐value= 0.04], which became more evident in women (β= ‐0.15, 95% CI= ‐0.23 to ‐0.06). After stratification by age groups, the increase of baseline MCV was associated with poor global cognition in the older group (age ≥75: β= ‐0.90, 95% CI= ‐1.65 to ‐0.15). No significant findings were observed in cognitive domains or other strata. Conclusion High baseline MCV was associated with an increased risk of cognitive impairment as age increased. MCV may be used an early marker for dementia in the community‐dwelling older adults.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".