ReviewClinical kidney journal2021
The utility of remote patient management in peritoneal dialysis.
Review in Clinical kidney journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 29 citations in OpenAlex.
- Evaluation of a Remote Therapeutic Monitoring Device and Integrated Care Platform in Outpatient Parenteral Antimicrobial Therapy.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026Trial
- Preserving residual kidney function in peritoneal dialysis: from conventional approaches to contemporary practice.Clinical kidney journal · 2026Review
- Management of Hypertension in Patients Undergoing Peritoneal Dialysis: A Narrative Review.Cureus · 2026Review
- Artificial intelligence in kidney transplantation: a 30-year bibliometric analysis of research trends, innovations, and future directions.Renal failure · 2025Review
- Article
- Co-Producing Peritoneal Dialysis Nursing Sensitive Indicators for Quality Care: A Multinational Consensus Building Design.Journal of renal care · 2025Article
- Article
- Effect of a Management Algorithm for Wet Contamination of Peritoneal Dialysis System on the Prevention of Peritonitis: A Prospective Observational Study.Kidney diseases (Basel, Switzerland) · 2024Article
- Impact of Remote Monitoring on Standardized Outcomes in Nephrology-Peritoneal Dialysis.Kidney international reports · 2024Article
- Scheduling of Remote Monitoring for Peritoneal Dialysis Patients.Journal of clinical medicine · 2024Article
- Patient experience in automated peritoneal dialysis with telemedicine monitoring during the COVID-19 pandemic in Mexico: Qualitative study.Nursing open · 2023Article
- Factors Influencing the Choice of Automated Peritoneal Dialysis Treatment by Patients Receiving Home Peritoneal Dialysis.Patient preference and adherence · 2023Article
- Remote Patient Monitoring in Home Dialysis Patients: Enhancing Care for Home Hemodialysis and Peritoneal Dialysis.Seminars in dialysisReview
- Living is very dangerous: dialysis in the pandemic.Jornal brasileiro de nefrologiaArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Remote patient management (RPM) programs are one of the most crucial innovations in the peritoneal dialysis (PD) field that have been developed in the last decade. RPM programs are associated with favourable clinical outcomes by increasing the adherence of the patients to PD prescription. The literature supports that RPM is associated with increased blood pressure control and technique survival, and decreased hospitalization rate, length of hospital stay and health costs. RPM programs also facilitate patient follow-up during the coronavirus disease 2019 pandemic, increase treatment adherence and lead to better clinical outcomes. However, published data remain scarce and mainly consist of observational or retrospective studies with relatively low numbers of patients. Therefore, randomized controlled trial results will be more informative to demonstrate the effect of RPM programs on clinical outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.