Evidence map›Paper›PMID 38256540›Full record

ArticleJournal of clinical medicine2024

Scheduling of Remote Monitoring for Peritoneal Dialysis Patients.

Grazia Maria Virzì, Niccolò Morisi, Sabrina Milan Manani, Ilaria Tantillo, José David Gonzàlez Barajas, Bladimir Diaz Villavicencio, Claudia Castiglione, Gaetano Alfano, Gabriele Donati, Monica Zanella

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.8field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Remote monitoring of automated peritoneal dialysis reduces mortality, adverse events and hospitalizations: a cluster-randomized controlled trial.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025
    Trial
  2. Article
  3. Review
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Grazia Maria VirzìDepartment of Nephrology, Dialysis and Transplantation, San Bortolo Hospital, 36100 Vicenza, Italy.ORCID 0000-0001-7934-9800
Niccolò MorisiIRRIV-International Renal Research Institute Vicenza Foundation, 36100 Vicenza, Italy.ORCID 0009-0000-0753-3326
Sabrina Milan MananiDepartment of Nephrology, Dialysis and Transplantation, San Bortolo Hospital, 36100 Vicenza, Italy.
Ilaria TantilloDepartment of Nephrology, Dialysis and Transplantation, San Bortolo Hospital, 36100 Vicenza, Italy.
José David Gonzàlez BarajasIRRIV-International Renal Research Institute Vicenza Foundation, 36100 Vicenza, Italy.ORCID 0000-0002-1977-5960
Bladimir Diaz VillavicencioIRRIV-International Renal Research Institute Vicenza Foundation, 36100 Vicenza, Italy.ORCID 0000-0002-0736-876X
Claudia CastiglioneDepartment of Medicine, Section of Nephrology, University of Verona, 37129 Verona, Italy.
Gaetano AlfanoSurgical, Medical and Dental Department of Morphological Sciences, Section of Nephrology, University of Modena and Reggio Emilia, 41121 Modena, Italy.ORCID 0000-0003-0591-8622
Gabriele DonatiSurgical, Medical and Dental Department of Morphological Sciences, Section of Nephrology, University of Modena and Reggio Emilia, 41121 Modena, Italy.ORCID 0000-0001-8549-1221
Monica ZanellaDepartment of Nephrology, Dialysis and Transplantation, San Bortolo Hospital, 36100 Vicenza, Italy.
Ospedale San Bortolo · ITUniversity of Modena and Reggio Emilia · ITUniversidad de Guadalajara · MXUniversity of Verona · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peritoneal dialysis (PD) is performed as a home-based treatment and in this context, telemedicine has been proven helpful for improving clinicians' surveillance and maintaining PD patients in their home setting. The new e-health devices make remote patient monitoring (RPM) for automated peritoneal dialysis (APD) treatment possible, evaluating the data at the end of every treatment and adapting the prescription at distance if necessary. This paper aims to share a method for improving clinical surveillance and enabling PD patients to receive their treatment at home. In the present case series, we delineate the clinical protocol of the Vicenza PD Center regarding patient characteristics, timing, and the purpose of the APD-RPM. We present the Vicenza PD Center's experience, illustrating its application through three case reports as exemplars. Telemedicine helps to carefully allocate healthcare resources while removing the barriers to accessing care. However, there is a risk of data overload, as some data might not be analyzed because of an increased workload for healthcare professionals. A proactive physician's attitude towards the e-health system has to be supported by clinical instructions and legislative rules. International and national guidelines may suggest which patients should be candidates for RPM, which parameters should be monitored, and with what timing. According to our experience, we suggest that the care team should define a workflow that helps in formulating a correct approach to RPM, adequately utilizing resources. The workflow has to consider the different needs of patients, in order to assure frequent remote control for incident or unstable patients, while prevalent and stable patients can perform their home treatment more independently, helped by periodic and deferred clinical supervision.

Indexed as

automated peritoneal dialysis (APD)peritoneal dialysisremote patient monitoring (RPM)workflow

Identifiers

PMID38256540
PMCPMC10816117
OpenAlexW4390750793

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.