Interventions to Improve Clinical Outcomes in Indigenous or Remote Patients With Chronic Kidney Disease: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease (CKD) associates with a significant health care burden with a disproportionate impact on indigenous persons or people living in remote areas. Although screening programs have expanded in these communities, there remains a paucity of evidence-based interventions to enhance clinical renal outcomes in these populations. OBJECTIVE: The objective of this study was to identify evidence-based interventions to enhance renal outcomes in these populations. DESIGN: A scoping review was conducted for studies in the Cochrane, MEDLINE, and Embase databases and from major nephrology meetings. SETTING: Chronic kidney disease, including those on dialysis. PATIENTS: Remote or indigenous populations. MEASUREMENTS: Studies that performed an intervention that was followed by measurement of renal outcomes or patient-centered outcomes (ie, quality of life) were included. METHODS: All studies were described by study type, intervention, and clinical outcome, and trends were identified by both authors. Meta-analysis was not conducted due to study heterogeneity. RESULTS: Thirty-two studies met inclusion criteria, only 2 (6.3%) of which were randomized controlled trials. Intervention types included multidisciplinary (34.4%), satellite (32.3%), telehealth (25.0%), or other (9.4%). All multidisciplinary interventions were performed in the CKD (non-dialysis) setting and reported improved patient travel time, waiting time, quality of life, kidney function, proteinuria, and blood pressure. Telehealth interventions improved program cost, patient attendance, hospitalization, and quality of life. Satellite interventions were performed in the hemodialysis setting, with 1 study evaluating acute hemodialysis. Satellite interventions improved patient travel time, dialysis clearance, quality of life, and survival, but increased program costs. LIMITATIONS: The study was restricted to interventional trials assessing clinical outcomes and to studies in developed countries, which likely excluded some research contributing to this field. CONCLUSIONS: There is significant heterogeneity among studies of interventions for patients with CKD who are indigenous or live remotely. Interventions were more likely to be successful when the remote or indigenous community was included in program development, with a culturally safe approach. More large, high-quality studies are needed to identify effective interventions to enhance clinical renal outcomes in indigenous or remote populations. TRIAL REGISTRATION: This trial is registered under PROSPERO, Registration Number 128453.
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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 | 0.013 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".