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Record W3171572885 · doi:10.1093/ndt/gfab101.008

MO686THE EFFECT OF A CONTINUOUS TRAINING PROGRAM ON PERITONEAL DIALYSIS PATIENTS' SURVIVAL

2021· article· en· W3171572885 on OpenAlexaboutno aff
Marios Theodoridis, Stamatia Bezirgianidou, Humeyra Serif-Damadoglou, Konstantia Kantartzi, Ploumis Passadakis, Elias Thodis, Stylianos Panagoutsos

Bibliographic record

VenueNephrology Dialysis Transplantation · 2021
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePeritoneal dialysisPeritonitisNephrologyDialysisUremiaRetrospective cohort studyInternal medicineSurgerySurvival analysis

Abstract

fetched live from OpenAlex

Abstract Background and Aims Peritoneal Dialysis (PD) is a well-established method for dialysis of end stage kidney disease patients. Peritoneal membrane alters with time from several causes such as bioincompatible PD solutions, uremia, and the cumulative effect of peritonitis episodes. Each center follows a specific training program to prevent the appearance of peritonitis episodes. The aim of this study was to retrospectively evaluate the influence of proper and continuous training on the mortality of peritoneal dialysis patients. Method This is a single center retrospective study of 133 PD patients conducted for the time period 2009 – 2019 (10 years). The training course was taught one-on-one, nurse-to-patient at the initiation of dialysis and then once every 6 months at their regular visit or sooner if there was a peritonitis episode. The program included a rated questioner based on the Canadian Association of Nephrology Nurses for Nursing Standards and Practice Recommendations published on August 2008. The patients were divided into two groups according to the mean value (34) of their questioner sum (QS). Group A included 69 patients with mean age of 66 ± 15 years (36 M, 33 F) with mean PD duration of 45 ± 30 months and they achieved a score less than 34. Group B included 64 patients with mean age of 61 ± 18 years (42 M, 22 F) with mean PD duration of 62± 32 months and they achieved a score greater than 34. The cumulative all-cause survival of the PD patients was calculated by Kaplan Meier, was compared using Long Rang analysis and was also adjusted for their age, gender, the modality of PD applied, the presence of Diabetes and their level of education. Using Cox Regression, we tried to find independent risk factors such as the score they achieved in the questioner. The two groups were compared also for their overhydration and their frequency appearance of peritonitis or exit site infection. Results The cumulative survival using Kaplan-Meier analysis revealed statistically significant deference between the two groups (Log Rank p<0.001) with Group B (QS>34) achieving better survival. When the survival was adjusted for age, sex, Diabetes, PD modality the result remains the same. Trying to find among the total of our patients the possible risk factors for mortality, using Cox Regression analysis, their QS score (representing their training level for PD) was statistically significant (HR 0,931 {0.892, 0.971}, p=0.001) independent risk factor, as well as age and PD modality, for our patient survival. Additionally, Group B (QS>34) had statistically significant a smaller number of peritonitis episodes (p<0.001) and presence of peripheral edema (p<0.001). Conclusion In our study we concluded that continuous and monitored training of peritoneal dialysis patients has a significant effect on their survival and the frequency of peritonitis appearance.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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