Association between TMSE/MoCA and MIS/NAF in ESKD patients undergoing hemodialysis: a cross-sectional study
Bibliographic record
Abstract
Both cognitive impairment and malnutrition are common in hemodialysis (HD) patients and are associated with increased hospitalization rates, infection, poor clinical outcomes, and mortality. The study investigated the association between cognitive and nutrition status among end-stage kidney disease (ESKD) patients undergoing hemodialysis. In this cross-sectional study, we enrolled 115 patients with ESKD who underwent regular hemodialysis (HD). Data collection included the use of screening tools for mild cognitive impairment (MCI), specifically Thai Mental State Examination (TMSE) and Montreal Cognitive Assessment (MoCA). In addition, we collected data using nutritional screening tools including Malnutrition Inflammation Score (MIS) and Nutrition Alert Form (NAF). Our primary outcome was to demonstrate whether there was a relationship between TMSE/MoCA and MIS/NAF scores in this population. Secondary outcomes were a prevalence of MCI and malnutrition status in ESKD patients, an association between TMSE and MoCA with other surrogate nutritional markers, and factors affecting MCI in such patients. A total of 109 patients undergoing HD completed our protocol. Their mean age was 63.42 (± 15.82) years, and 51.38% were male. Mean TMSE and MoCA were 23.98 (± 5.06) points and 18.3 (± 6.40) points, respectively. The prevalence of TMSE ≤ 23 and MoCA ≤ 24 were 39.45% and 83.49%, respectively. TMSE had a statistically significant negative correlation with MIS (R 2 = 0.16, p < 0.001) and NAF. MoCA also negatively correlated with MIS and NAF. The age, total educational year, the status of whether having a caregiver, serum albumin, serum phosphorus level, handgrip strength, and lean mass tissue were correlated with TMSE. Nutritional parameters, including MIS score, NAF score, serum albumin, lean tissue mass, and lean tissue index, significantly correlate with TMSE and MoCA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".