Cognitive Impairment and its Correlates in Chronic Kidney Disease Patients Undergoing Haemodialysis
Bibliographic record
Abstract
Cognitive Impairment (CI) has been found to be quite common amongst patients with Chronic Kidney Disease (CKD) undergoing haemodialysis (HD).The presence of these deficits could affect patient's adherence to diet regimens, treatment and also reduce their Quality of Life.The presence of depression in such patients can further lead to CI.We wanted to assess the prevalence of CI in CKD patients undergoing haemodialysis, socio-demographic and patient related variables affecting CI, and also the relationship between depression and cognition. METHODSFifty patients undergoing haemodialysis from two dialysis units were assessed.The Montreal Cognitive Assessment (MoCA) scale and Patient Health Questionnaire-9 (PHQ-9) were administered to patients.Descriptive analysis was done for the sociodemographic and clinical variables.Chi square test was used to find the association between the categorical data.Kruskal-Wallis test was used to determine the association between categorical and quantitative variables. RESULTSMean age of patient was 50.32 (±12.4)years.Mean duration of dialysis was 18.8 (±15.11)months.The prevalence of depression in the patients was 42%.Cognitive impairment was present in 44% of the patients.There was a significant relationship between education level and recall (χ²=31.7,df=12, p=.002) as well as orientation (χ²=29.78,df=8, p=.000) domains of cognition.Also, there was a significant relationship between socio-economic status and global cognition score (χ²=81.13,df=48, p=.002).There was a negative correlation between duration of dialysis and cognition.Significant relationships were found between depression and various cognitive domains. CONCLUSIONSThe prevalence of CI in haemodialysis patients is high.It is also affected by factors such as education level, socio-economic status, duration of dialysis and presence of depression.Insight into CI is essential for its early identification during the course of illness, so that patient precise treatment decisions can be made.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".