Impact of Age Initiation and Duration of Hemodialysis on Impaired Cognitive Function Experienced by Chronic Kidney Disease (CKD) Patients
Bibliographic record
Abstract
The prevalence of people with chronic kidney disease (CKD) in Indonesia increases with age. Various complications to death can occur in CKD patients, one of which is impaired cognitive function. In addition, end-stage CKD treatment options, such as hemodialysis, further increase the risk of complications of cognitive impairment in CKD patients. About 10%-40% of CKD patients experience a decline in cognitive function. This study aims to determine the factors that influence the occurrence of cognitive impairment in hemodialysis patients. This study was conducted at Mohammad Hoesin Hospital Palembang in October-November 2022. Cognitive decline was detected by examination of the Montreal Cognitive Assessment-Indonesian version (MoCA-Ina) while other variables were obtained through interviews. The data were analyzed with Chi-square or Fisher exact tests. Age, education level, and age at hemodialysis initiation affect global cognitive function in CKD patients. In cognitive domain analysis, a significant relationship was found between age and duration of hemodialysis and attentional function, as well as the impact of age, sex, and age at hemodialysis initiation on executive/visuospatial function. Several demographic and hemodialysis characteristics are associated with cognitive decline in hemodialysis patients. Education and periodic cognitive screening are necessary to prevent and detect cognitive decline in these at-risk populations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".