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Record W3005523777 · doi:10.1177/2054358119887988

Major Outcomes With Personalized Dialysate TEMPerature (MyTEMP): Rationale and Design of a Pragmatic, Registry-Based, Cluster Randomized Controlled Trial

2020· article· en· W3005523777 on OpenAlexafffundabout
Ahmed A. Al‐Jaishi, Christopher W. McIntyre, Jessica M. Sontrop, Stephanie N. Dixon, Sierra Anderson, Amit Bagga, Derek Benjamin, David P Berry, Peter G. Blake, Laura C. Chambers, Patricia C.K. Chan, Nicole Delbrouck, P.J. Devereaux, Luis Felipe Ferreira-Divino, Richard Goluch, Laura Gregor, Jeremy Grimshaw, Garth A. Hanson, Eduard A. Iliescu, Arsh K. Jain, Charmaine E. Lok, Reem A. Mustafa, Bharat Nathoo, Gihad Nesrallah, Matthew J. Oliver, Sanjay Pandeya, Malvinder S. Parmar, David Perkins, Justin Presseau, E. Z. Rabin, Joanna Sasal, Tanya Shulman, Manish M. Sood, Andrew Steele, Paul Tam, Daniel J. Tascona, Davinder Wadehra, Ron Wald, Michael Walsh, Paul Watson, Walter P. Wodchis, Phillip Zager, Merrick Zwarenstein, Amit X. Garg

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2020
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsSt. Joseph’s Healthcare HamiltonSt. Michael's HospitalWilliam Osler Health SystemLakeridge HealthThunder Bay Regional Health Sciences CentreThe Scarborough HospitalSt Joseph's Health CentreHumber River Regional HospitalNiagara Health SystemLondon Health Sciences CentreGrand River HospitalHealth Sciences NorthHalTechSault Area HospitalUniversity of TorontoWestern UniversityTrillium Health CentreToronto East General HospitalYork Central HospitalVictoria HospitalKingston Health Sciences CentreUniversity of OttawaSunnybrook Health Science CentreRoyal Victoria Regional Health CentreHealth Sciences CentreUniversity Health NetworkOttawa HospitalWindsor Regional HospitalMcMaster University
FundersCanadian Institutes of Health ResearchDialysis ClinicsLawson Health Research InstituteHeart and Stroke Foundation of Canada
KeywordsMedicineRandomized controlled trialCluster (spacecraft)Internal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Small randomized trials demonstrated that a lower compared with higher dialysate temperature reduced the average drop in intradialytic blood pressure. Some observational studies demonstrated that a lower compared with higher dialysate temperature was associated with a lower risk of all-cause mortality and cardiovascular mortality. There is now the need for a large randomized trial that compares the effect of a low vs high dialysate temperature on major cardiovascular outcomes. OBJECTIVE: The purpose of this study is to test the effect of outpatient hemodialysis centers randomized to (1) a personalized temperature-reduced dialysate protocol or (2) a standard-temperature dialysate protocol for 4 years on cardiovascular-related death and hospitalizations. DESIGN: The design of the study is a pragmatic, registry-based, open-label, cluster randomized controlled trial. SETTING: Hemodialysis centers in Ontario, Canada, were randomized on February 1, 2017, for a trial start date of April 3, 2017, and end date of March 31, 2021. PARTICIPANTS: In total, 84 hemodialysis centers will care for approximately 15 500 patients and provide over 4 million dialysis sessions over a 4-year follow-up. INTERVENTION: Hemodialysis centers were randomized (1:1) to provide (1) a personalized temperature-reduced dialysate protocol or (2) a standard-temperature dialysate protocol of 36.5°C. For the personalized protocol, nurses set the dialysate temperature between 0.5°C and 0.9°C below the patient's predialysis body temperature for each dialysis session, to a minimum dialysate temperature of 35.5°C. PRIMARY OUTCOME: A composite of cardiovascular-related death or major cardiovascular-related hospitalization (a hospital admission with myocardial infarction, congestive heart failure, or ischemic stroke) captured in Ontario health care administrative databases. PLANNED PRIMARY ANALYSIS: The primary analysis will follow an intent-to-treat approach. The hazard ratio of time-to-first event will be estimated from a Cox model. Within-center correlation will be considered using a robust sandwich estimator. Observation time will be censored on the trial end date or when patients die from a noncardiovascular event. TRIAL REGISTRATION: www.clinicaltrials.gov; identifier: NCT02628366.

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)0.218
metaresearch head score (Gemma)0.189
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.218
Threshold uncertainty score0.964

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2180.189
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0120.007
Bibliometrics0.0030.003
Science and technology studies0.0030.006
Scholarly communication0.0050.006
Open science0.0040.004
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.014
GPT teacher head0.254
Teacher spread0.241 · 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.

Study designRandomized trial
Domainnot available
GenreProtocol

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

Citations31
Published2020
Admission routes3
Has abstractyes

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