Conservative management and health-related quality of life in end-stage renal disease: a systematic review
Bibliographic record
Abstract
PURPOSE: Few studies have addressed health-related quality of life (QoL) in patients who chose conservative management over dialysis. This systematic review aims to better define the role of conservative management in improving health-related QoL in patients with end-stage renal disease (ESRD). METHODS: Medline, Cochrane and EMBASE were searched for prospective or retrospective studies published until June 30, 2016, that examined QoL of ESRD patients. The primary outcome was health-related QoL. RESULTS: Four studies were included (405 patients received dialysis and 332 received conservative management). Two studies that used the Short Form-36 Survey (SF-36) showed that the dialysis group had higher physical component scores, but the conservative management group had similar, or better, mental component scores at the end of intervention. Another study using the SF-36 showed that the physical and mental component scores of the dialysis group did not significantly change after intervention. In the conservative management group, the physical component scores did not change, but the mental component scores increased significantly over time (0.12 ± 0.32, p < 0.05). One study, which used the Kidney Disease Quality of Life-Short Form (KD QoL-SF), found no change after intervention in either physical or mental component scores in the dialysis group; however, the physical component score declined (p = 0.047) and the mental component score increased (p = 0.033) in the conservative management group. CONCLUSION: Although there are only a limited number of published articles, ESRD patients who receive conservative management may have improved mental health-related QoL when compared with those who receive dialysis.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".