Comprehensive geriatric assessment and drug burden in elderly chronic kidney disease patients
Bibliographic record
Abstract
Abstract Objectives Chronic kidney disease (CKD) is a condition characterized by atherosclerosis, cognitive impairment, physical limitations, biochemical abnormalities, and vascular aging. The proportion of those with a diagnosis of CKD in the older is increasing. With comprehensive geriatric assessment, it could be possible to detect the disorders that are related to biological aging. The aim is to evaluate geriatric syndromes like frailty, cognitive dysfunction, malnutrition, and polypharmacy in an aged population with pre-dialytic CKD (stages 3a–5), and to investigate possible relations with biochemical features and anticholinergic drug burden (ADB). Methods One hundred and fifty-six CKD patients aged 60 and older and 164 healthy controls were included in the study. Geriatric parameters that were used for the evaluation of the groups were, Clinical Frailty Index; Charlson Comorbidity Index; Montreal Cognitive Assessment and Mini Nutritional Assessment Short-Form. Besides, biochemical parameters and ADB defined with 3 scales Anticholinergic Burden Classification (ABC), Chew’s scale, and Drug Burden Index were recorded. Results Despite being younger, CKD patients had higher comorbidity and frailty scores than the controls. Patients and controls had similar nutritional status, and cognitive function test results. Frailty was an important predictor for geriatric parameters and eGFR. ABC score was higher in the CKD group in ADB scale. Conclusions Frailty and polypharmacy are more prevalent than expected in older with CKD. In addition, anticholinergic burden and polypharmacy may form causal links with one and other and lead to increased mortality rates especially with frailty. Therefore, geriatric assessment and appropriate ADB evaluation may be recommended in CKD patients.
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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 | 0.002 |
| 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".