Home versus in-centre haemodialysis for people with kidney failure
Notice bibliographique
Résumé
BACKGROUND: Home haemodialysis (HHD) may be associated with important clinical, social or economic benefits. However, few randomised controlled trials (RCTs) have evaluated HHD versus in-centre HD (ICHD). The relative benefits and harms of these two HD modalities are uncertain. This is an update of a review first published in 2014. This update includes non-randomised studies of interventions (NRSIs). OBJECTIVES: To evaluate the benefits and harms of HHD versus ICHD in adults with kidney failure. SEARCH METHODS: We contacted the Information Specialist and searched the Cochrane Kidney and Transplant Register of Studies up to 9 October 2022 using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Registry Platform (ICTRP) Search Portal, and ClinicalTrials.gov. We searched MEDLINE (OVID) and EMBASE (OVID) for NRSIs. SELECTION CRITERIA: RCTs and NRSIs evaluating HHD (including community houses and self-care) compared to ICHD in adults with kidney failure were eligible. The outcomes of interest were cardiovascular death, all-cause death, non-fatal myocardial infarction, non-fatal stroke, all-cause hospitalisation, vascular access interventions, central venous catheter insertion/exchange, vascular access infection, parathyroidectomy, wait-listing for a kidney transplant, receipt of a kidney transplant, quality of life (QoL), symptoms related to dialysis therapy, fatigue, recovery time, cost-effectiveness, blood pressure, and left ventricular mass. DATA COLLECTION AND ANALYSIS: Two authors independently assessed if the studies were eligible and then extracted data. The risk of bias was assessed, and relevant outcomes were extracted. Summary estimates of effect were obtained using a random-effects model, and results were expressed as risk ratios (RR) and their 95% confidence intervals (CI) for dichotomous outcomes and mean difference (MD) or standardised mean difference (SMD) and 95% CI for continuous outcomes. Confidence in the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Meta-analysis was performed on outcomes where there was sufficient data. MAIN RESULTS: , 95% CI -29.60 to -5.89; 2 NRSIs, 130 participants; low certainty evidence). There was insufficient data to evaluate the relative association of HHD and ICHD with fatigue or vascular access outcomes. Patient-reported outcome measures were reported using 18 different measures across 11 studies (QoL: 6 measures; mental health: 3 measures; symptoms: 1 measure; impact and view of health: 6 measures; functional ability: 2 measures). Few studies reported the same measures, which limited the ability to perform meta-analysis or compare outcomes. It is uncertain whether HHD is more cost-effective than ICHD, both in the first (SMD -1.25, 95% CI -2.13 to -0.37; 4 NRSIs, 13,809 participants; very low certainty evidence) and second year of dialysis (SMD -1.47, 95% CI -2.72 to -0.21; 4 NRSIs, 13,809 participants; very low certainty evidence). AUTHORS' CONCLUSIONS: Based on low to very low certainty evidence, HHD, compared with ICHD, has uncertain associations or may be associated with decreased cardiovascular and all-cause death, hospitalisation rate, slower post-dialysis recovery time, and decreased SBP and LVMI. HHD has uncertain cost-effectiveness compared with ICHD in the first and second years of treatment. The majority of studies included in this review were observational and subject to potential selection bias and confounding, especially as patients treated with HHD tended to be younger with fewer comorbidities. Variation from study to study in the choice of outcomes and the way in which they were reported limited the ability to perform meta-analyses. Future research should align outcome measures and metrics with other research in the field in order to allow comparison between studies, establish outcome effects with greater certainty, and avoid research waste.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,004 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».