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Record W3111117811 · doi:10.1177/2054358120975305

Technique Survival and Determinants of Technique Failure in In-Center Nocturnal Hemodialysis: A Retrospective Observational Study

2020· article· en· W3111117811 on OpenAlexafffundabout
Michael Schächter, Marc J. Saunders, Ayub Akbari, Julia M. Caryk, Ann Bugeja, Edward G. Clark, Karthik Tennankore, Dan Martinusen

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2020
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsOttawa HospitalDalhousie UniversityUniversity of OttawaUniversity of CalgaryIsland Health
FundersBC Renal AgencyUniversity of Calgary
KeywordsMedicineDiscontinuationHemodialysisDialysisRetrospective cohort studyHazard ratioPopulationObservational studyProportional hazards modelInternal medicineEmergency medicinePediatricsConfidence interval

Abstract

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BACKGROUND: Long-duration (7-8 hours) hemodialysis provides benefits compared with conventional thrice-weekly, 4-hour sessions. Nurse-administered, in-center nocturnal hemodialysis (INHD) may expand the population to whom an intensive dialysis schedule can be offered. OBJECTIVE: The primary objective of this study was to determine predictors of INHD technique failure, disruptions, and technique survival. DESIGN: This study used retrospective chart and database review methodology. SETTING: This study was conducted at a single Canadian INHD program operating in Victoria, British Columbia, within a tertiary care hospital. Our program serves a catchment population of approximately 450 000 people. PATIENTS/SAMPLE/PARTICIPANTS: Forty-three consecutive incident INHD patients took part in the INHD program of whom 42 provided informed consent to participate in this study. METHODS: We conducted a retrospective observational study including incident INHD patients from 2015 to 2017. The primary outcome was technique failure ≤6 months (TF ≤6). Secondary outcomes included technique survival and reasons for/predictors of INHD discontinuation or temporary disruption. Predictors of each outcome included demographics, comorbidities, and Clinical Frailty Scale (CFS) scoring. RESULTS: Among 42 patients, mean (SD) age, dialysis vintage, CFS score, and follow-up were 63 (16) years, 46 (55) months, 4 (1), and 11 (9) months, respectively. 52% were aged ≥65 years. TF ≤6 occurred in 12 (29%) patients. One-year technique survival censored for transplants and home dialysis transitions was 60%. Discontinuation related to insomnia (32%), medical status change (27%), and vascular access (23%). In unadjusted Cox survival analysis, 1-point increases in CFS score associated with a higher risk of technique failure (hazard ratio: 2.04, 95% confidence interval [CI]: 1.26-3.31). In an adjusted analysis, higher frailty severity also associated with temporary INHD disruptions (incidence rate ratio: 2.64, 95% CI: 1.55-4.50, comparing CFS of ≥4 to 1-3). LIMITATIONS: The retrospective, observational design of this study resulted in limited ability to control for confounding factors. In addition, the relatively small number of events observed owing to a small sample size diminished statistical power to inform study conclusions. Use of a single physician to determine the clinical frailty score is another limitation. Finally, the use of a single center for this study limits generalizability to other programs and clinic settings. CONCLUSIONS: INHD is a sustainable modality, even among older patients. Higher frailty associates with INHD technique failure and greater missed treatments. Inclusion of a CFS threshold of ≤4 into INHD inclusion criteria may help to identify individuals most likely to realize the long-term benefits of INHD. TRIAL REGISTRATION: Due to the retrospective and observational design of this study, trial registration was not necessary.

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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.305
Teacher spread0.267 · 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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Citations4
Published2020
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Kidney Health and DiseaseSame topicDialysis and Renal Disease ManagementFrench-language works237,207