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Record W4322617058 · doi:10.1111/ctr.14949

Current opinions on DGF management practices: A survey of the United States and Canada

2023· article· en· W4322617058 on OpenAlexaffabout
Caroline C. Jadlowiec, Benjamin Hippen, John S. Gill, Raymond L. Heilman, Darren Stewart, Kunam S. Reddy, Sumit Mohan, Alexander C. Wiseman, Matthew Cooper

Bibliographic record

VenueClinical Transplantation · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWorkgroupMedicineMachine perfusionTransplantationDialysisKidney transplantationFamily medicineIntensive care medicineEmergency medicineSurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: Significant center-to-center variation in attitudes and management of delayed graft function (DGF) remains common. METHODS: A survey to describe current DGF practices was developed by workgroup members sponsored by the National Kidney Foundation (NKF) and was distributed to both the NKF DGF workgroup members, kidney transplant program directors and the transplant community within the United States and Canada. Seventy-one percent of NKF workgroup members completed the survey along with 70 unique the United States and three Canadian kidney transplant programs. All Organ Procurement and Transplantation Network (OPTN) regions were represented. RESULTS: DGF was reported to occur at rate of 20%-40% for most centers with 3.9% indicating their incidence to be >60%. Most centers reported longer hospital lengths of stay and more frequent outpatient visits. Despite the commonality of DGF, only half of centers reported having an established protocol to manage DGF. Kidney allograft biopsies were the only consistent DGF management strategy observed, although use of machine perfusion was also heavily favored. Other DGF management strategies voiced by a minority included having established outpatient practices to care for DGF patients and administering outpatient community-based hemodialysis. CONCLUSION: Although approximately a third of survey responders indicated that risk of DGF played a role in their willingness to accept organs, most did not feel that increased cost or clinical impact on outcomes was a deterrent. Future strategies, including broader sharing of best practices, redefining terminology specific to DGF, the establishment of DGF dialysis guidelines and improving access to machine perfusion across OPOs may help reduce discard and improve utilization of kidneys at risk for DGF.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.165
GPT teacher head0.442
Teacher spread0.277 · 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 teacher head, 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

Citations13
Published2023
Admission routes2
Has abstractyes

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