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Record W4403811224 · doi:10.1681/asn.202496736cy0

Exploring Peritoneal Dialysis Exits from a Canadian Cohort

2024· article· en· W4403811224 on OpenAlexaffabout
Jennifer M. MacRae, Tessa A. M. Woodside, Bushra Muzammal, Terry J. Smith, Susan A. Jones, Nikhil Shah

Bibliographic record

VenueJournal of the American Society of Nephrology · 2024
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsAlberta Health ServicesUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsPeritoneal dialysisMedicineCohortIntensive care medicineInternal medicineUrology

Abstract

fetched live from OpenAlex

Background: Growth in a peritoneal dialysis (PD) program is challenging to achieve. In order to increase the number of people receiving PD, the total number of people exiting should be less than the number of new starts. We sought to better understand the PD exits in our program in order to develop interventions to reduce the attrition from PD. Methods: A 14 month retrospective review of the Alberta Kidney Care (AKC) PD program (comprised of a northern (AKCN, 317 pts) and a southern (AKCS, 298 pts) program with a focus on the reasons why people exited PD from November 1, 2022 until Dec 31, 2023. Differences between programs and between sexes were explored using descriptive statistics and Chi Square where appropriate. The primary outcome was the reason for exit from PD. Results: During the study period 615 people received PD; 230 patients exited PD during this time frame. There were no differences in demographics between the 2 programs with the overall mean age of 61 ±16.3 years, comorbidities of DM 43% (123), CVD 91% (210) and heart failure 27% (63) and mean time on PD of 2.2 ± 1.9 years. Overall, 37% (230/615) exited PD, 45% (103) transferred to facility-based hemodialysis (HD), 21.3% (49) were transplanted, 19.1% (44) died and 11% (26) withdrew from dialysis. Patients who transferred to HD received PD for a similar amount of time (2.13 ±2.00) as compared to those who were transplanted (2.01± 1.92) or died (2.53 ± 1.88 years). The main reasons for transfer to HD included medical 43% (44), peritonitis 32% (33), and hernia/leaks 24% (24). Despite similar PD peritonitis rates, AKCN had more exit site (8.6% vs 1%) and tunnel (17.1% vs 3%) infections than AKCS. Catheter complications occurred more frequently in AKCS with more leaks (21% vs 8.6%) and catheter associated pain (10% vs 2.9%) in AKCS vs AKCN respectively. Conclusion: There was a high turnover of people on PD with the majority transferring to HD for reasons of PD related infections and medical etiology. Strategies to reduce PD related infections will be helpful to reduce PD losses in our program. Further research into the differences in catheter complications and PD infections between the two programs is needed.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.025
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
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 head0.035
GPT teacher head0.273
Teacher spread0.238 · 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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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