Impact of chronic kidney disease on health-related quality of life in adults: a systematic review and meta-analysis protocol
Bibliographic record
Abstract
Introduction: Chronic Kidney Disease (CKD) significantly impacts patients' health-related quality of life (HRQoL), yet comprehensive evidence synthesis remains limited, particularly from African contexts. This systematic review aims to evaluate how CKD affects HRQoL in adult patients and identify the most impacted domains across disease stages, providing evidence to guide patient-centered care and health policy. Methods: Following PRISMA-P 2020 guidelines, we will systematically search PubMed, Embase, Scopus, Web of Science, Cochrane Library, and grey literature for observational studies and clinical trials evaluating HRQoL in adults (≥18 years) with CKD using validated instruments (SF-36, KDQOL, EQ-5D). Two independent reviewers will conduct study selection, data extraction, and quality assessment using the Newcastle-Ottawa Scale and Cochrane Risk of Bias Tool. Meta-analysis will be performed where feasible, with subgroup analyses by CKD stage, treatment modality, and geographic region. Expected outcomes: This review will provide nurses and clinicians with comprehensive evidence on HRQoL impairments across CKD stages, inform development of targeted psychosocial interventions, and guide resource allocation for holistic patient care. Findings will support healthcare providers in addressing not only physiological parameters but also patients' subjective wellbeing and quality of life. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420251036629.
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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 | 0.066 | 0.082 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.022 | 0.026 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.067 | 0.008 |
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".