Structural equation modelling of the role of cognition in functional interference and treatment nonadherence among haemodialysis patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Cognitive impairment is common in haemodialysis patients and associated with adverse health outcomes. This may be due to cognitive impairments interfering with daily functioning and self-care, but evidence is limited. This cross-sectional study aims to explore the interrelationships between cognition and functional outcomes in haemodialysis patients. METHODS: Haemodialysis patients completed measures of objective cognitive function (Montreal Cognitive Assessment), everyday problem-solving skills (scenario-based task), and subjective cognitive complaints (self-report). Participants also self-reported sociodemographic information, functional interference, treatment nonadherence, and mood and fatigue symptoms. Patients' clinical data including comorbidities and lab results were extracted from medical record. Structural equation modelling was performed. RESULTS: A total of 268 haemodialysis patients (mean age = 59.87 years; 42.5% female) participated. The final model showed satisfactory fit: CFI = 0.916, TLI = 0.905, RMSEA = 0.033 (90% confidence interval 0.024 to 0.041), SRMR = 0.066, χ2(493) = 618.573 (p < .001). There was a negative association between objective cognitive function and subjective cognitive complaints. Cognitive complaints were positively associated with both functional interference and treatment nonadherence, whereas objective performance was not. Everyday problem-solving skills emerged as a distinct aspect of cognition not associated with objective performance or subjective complaints, but had additive utility in predicting functional interference. CONCLUSIONS: Subjective cognitive complaints and everyday problem-solving skills appear to be stronger predictors of functional variables compared to objective performance based on traditional tests. Routine screening of everyday cognitive difficulties may allow for early identification of dialysis patients at risk of cognitive impairment, functional interference, treatment nonadherence, and poor clinical outcomes.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".