Bibliographic record
Abstract
Background: The relationship between mild cognitive impairment (MCI) and pinch strength in patients with cardiovascular disease is unclear.The purpose of the present study was to examine the associations among MCI and pinch strength and to determine a pinch strength cut-off value for use in the assessment of MCI.Methods: We conducted a cross-sectional study of 135 patients with cardiovascular disease but without probable dementia.MCI was estimated with the Japanese version of the Montreal Cognitive Assessment.We classified patients into the normal cognitive group and MCI group and compared their clinical characteristics, handgrip strength, and pinch strength.The relation between MCI and pinch strength was clarified with logistic regression analysis, and the cut-off value for three-fingered pinch strength was determined by receiver operating characteristic curve analysis.Results: The incidence of MCI was 37.0%.Significant differences between the two groups were identified for age, body mass index, hemoglobin, estimated glomerular filtration rate, albumin, dyslipidemia, use of nitrates, educational background, handgrip strength, and pinch strength.After multivariate analysis, three-fingered pinch strength was significantly associated with MCI (odds ratio 0.77, p = 0.02).The cut-off value of three-fingered pinch strength for predicting MCI was 6.75 kgf (area under the curve = 0.71; p < 0.001).Conclusions: Pinch strength was one independent factor significantly associated with MCI in patients with cardiovascular disease.The determination of a cut-off value for three-fingered pinch strength that can predict MCI may be one important factor in the early screening for MCI in the daily clinical setting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".