Lower Functional Status and Perceived Health Status Are Associated With Poorer Quality of Life in Older People With ESKD
Bibliographic record
Abstract
Background: Frailty is under-recognised in end-stage kidney disease (ESKD) including in those eligible for transplantation. Understanding which frailty components are associated with quality of life outcomes (QoL) allows for focused intervention and counselling of older people with ESKD. Methods: The Kidney Transplantation in Older People: impact of frailty on outcomes (KTOP) study explores frailty, cognition, and QoL changes in older people (≥60) whilst waiting for and after a transplant. Frailty was assessed using the Edmonton Frailty Scale which gives total scores and scores for different frailty components. We present QoL scores from 5 measures at recruitment, their variation by frailty status, and their association with frailty components. Results: 210 patients have been recruited; 118(63.4%) were identified as not frail, 38(20.4%) were vulnerable, and 30(16.2%) were frail. Frailty and QoL scores were available for 164-167 patients. Progressively lower QoL scores in all measures were observed in the vulnerable and frail groups (figure 1, p<0.0001). Table 1 shows the association between frailty components and QOL scores (p≤0.05 on adjusted linear regression). Poor functional status and general health status were associated with lower QoL scores across all measures.Figure 1.: Reported Quality of Life Scores by Frailty StatusTable 1.: Frailty Components Associated With Poorer Reported Quality of Life ScoresConclusions: Frailty and vulnerability to frailty is not uncommon in older people considered eligible for transplantation and is associated with worsening reported QoL. Functional dependence and general health status were associated with poorer QoL scores throughout all questionnaires. This is invaluable for giving a holistic depiction of ESKD in older people and allows for more targeted management.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".