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Record W3011134465 · doi:10.2215/cjn.11951019

A Systematic Review and Jurisdictional Scan of the Evidence Characterizing and Evaluating Assisted Peritoneal Dialysis Models

2020· review· en· W3011134465 on OpenAlexafffund
Mark Hofmeister, Scott Klarenbach, Lesley Soril, Nairne Scott‐Douglas, Fiona Clement

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2020
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of AlbertaUniversity of Calgary
FundersAlberta Health
KeywordsMedicinePeritoneal dialysisCINAHLPsychosocialDialysisIntensive care medicineMEDLINEPsycINFOSystematic reviewHemodialysisInternal medicineNursingPsychological interventionPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Compared with hemodialysis, home peritoneal dialysis alleviates the burden of travel, facilitates independence, and is less costly. Physical, cognitive, or psychosocial factors may preclude peritoneal dialysis in otherwise eligible patients. Assisted peritoneal dialysis, where trained personnel assist with home peritoneal dialysis, may be an option, but the optimal model is unknown. The objective of this work is to characterize existing assisted peritoneal dialysis models and synthesize clinical outcomes. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A systematic review of MEDLINE, Cochrane Central Register of Controlled Trails, Cochrane Database of Systematic Reviews, Embase, PsycINFO, and CINAHL was conducted (search dates: January 1995-September 2018). A focused gray literature search was also completed, limited to developed nations. Included studies focused on home-based assisted peritoneal dialysis; studies with the assist provided exclusively by unpaid family caregivers were excluded. All outcomes were narratively synthesized; quantitative outcomes were graphically depicted. RESULTS: We included 34 studies, totaling 46,597 patients, with assisted peritoneal dialysis programs identified in 20 jurisdictions. Two categories emerged for models of assisted peritoneal dialysis on the basis of type of assistance: health care and non-health care professional assistance. Reported outcomes were heterogeneous, ranging from patient-level outcomes of survival, to resource use and transfer to hemodialysis; however, the comparative effect of assisted peritoneal dialysis was unclear. In two qualitative studies examining the patient experience, the maintenance of independence was identified as an important theme. CONCLUSIONS: Reported outcomes and quality were heterogeneous, and relative efficacy of assisted peritoneal dialysis could not be determined from included studies. Although the patient voice was under-represented, suggestions to improve assisted peritoneal dialysis included using a person-centered model of care, ensuring continuity of nurses providing the peritoneal dialysis assist, and measures to support patient independence. Although attractive elements of assisted peritoneal dialysis are identified, further evidence is needed to connect assisted peritoneal dialysis outcomes with programmatic features and their associated funding models.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.046
metaresearch head score (Gemma)0.199
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.046
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.199
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0240.024
Science and technology studies0.0010.002
Scholarly communication0.0070.006
Open science0.0040.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.152
GPT teacher head0.442
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations26
Published2020
Admission routes2
Has abstractyes

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