Association between Visceral Fat Content and Obesity-Related Indicators with Cognitive Impairment after Intracerebral Hemorrhage
Bibliographic record
Abstract
BACKGROUND: Intracerebral hemorrhage (ICH) is a major cause of morbidity and mortality, often leading to long-term cognitive impairment that significantly diminishes the quality of life. This study investigated the relationship between visceral fat content, obesity-related indicators, and cognitive dysfunction following ICH. METHODS: A total of 388 subjects with ICH who were admitted to the Neurosurgery Department of the Hospital and met the inclusion and exclusion criteria were included in this study. Obesity-related indicators, including body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR), were measured. L3 level images were obtained by abdominal computerized tomography (CT). The visceral fat content was estimated using IMAGE J software, and adiponectin levels were assessed via enzyme-linked immunosorbent assay (ELISA). The Mini-Mental State Examination (MMSE) was used to evaluate the cognitive level of patients within 2 weeks of onset, and the shortened version of the Montreal Cognitive Assessment (miniMoCA) was used to evaluate the cognitive level of patients 6 months after ICH. Univariate and multivariate analyses were used to analyze the correlations of BMI, WC, WHtR, abdominal fat, and adiponectin with cognitive impairment after ICH. RESULTS: BMI, WC, and WHtR were lower in the cognitive impairment group (p < 0.01). Overweight patients exhibited higher MMSE scores than normal-weight patients (p < 0.05) and higher miniMoCA scores than obese patients (p = 0.014). Abdominal obesity, assessed by WC and WHtR, was associated with higher MMSE scores (p = 0.022 and 0.003, respectively). Multivariate analysis indicated that WHtR was associated with cognitive impairment risk post-ICH (odds ratio (OR) = 0.233, 95% confidence interval (CI) (0.071, 0.762); p = 0.016). Although no overall association was found between adiponectin levels and cognitive impairment, subgroup analysis revealed lower adiponectin levels in overweight patients with cognitive impairment (p = 0.040). CONCLUSION: WHtR is independently and inversely associated with cognitive impairment after ICH. There is no significant correlation between adiponectin with cognitive impairment after ICH, while subgroup analysis indicates that adiponectin levels are lower in overweight patients with cognitive impairment.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".