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PD54-11 NOVEL DEVICE FOR RENAL COOLING DURING TRANSPLANTATION

2019· article· en· W2941499473 on OpenAlexaboutno aff
Thomas Skinner, Ali Dergham, Luke Witherspoon

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTransplantationAnastomosisHypothermiaKidney transplantationMachine perfusionViaspanWarm ischemiaSurgeryIschemiaInternal medicineReperfusion injury

Abstract

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You have accessJournal of UrologyTransplantation & Vascular Surgery: Renal Transplantation & Vascular Surgery I (PD54)1 Apr 2019PD54-11 NOVEL DEVICE FOR RENAL COOLING DURING TRANSPLANTATION Thomas Skinner*, Ali Dergham, and Luke Witherspoon Thomas Skinner*Thomas Skinner* More articles by this author , Ali DerghamAli Dergham More articles by this author , and Luke WitherspoonLuke Witherspoon More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000557064.64143.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: In renal transplantation, warm ischemia time (WIT) describes the period of ischemia beginning with removal of the organ from ice and concluding at reperfusion. WIT is associated with delayed graft function, and adverse patient and graft long-term survival. Metabolic activity in cooled kidneys is minimal at 5°C and resumes above 15°C, a temperature reached after only 15 min of WIT. This is of clinical significance because WIT in renal transplantation is often > 40 min. The solution lies not in rushing the anastomosis but maintaining renal hypothermia during the process. Although various devices have been proposed, most suffer from being too bulky, inefficient, expensive, or prone to puncture. We set out to develop a novel, inexpensive device to maintain allograft temperatures ≤ 5°C, thereby limiting ischemic damage. METHODS: 3/16″ aluminum tubing was organized in a serpentine pattern to create a malleable, form-fitting cooling jacket. Coolant comprised 4°C saline solution flowing at 240 mL/min. Adult porcine kidneys (n = 4) (175 g, 13x7x3 cm LxWxH) were used to test the device. Kidneys were placed at 24°C; surface and core temperatures were monitored using implanted thermocouples. Device usability was tested by anastomosing porcine kidney vessels to GORE-TEX® vascular grafts with the cooling jacket in place in a simulated ex-vivo operative field. RESULTS: Our cooling jacket costs less than $3.00 to produce and is mouldable to any size kidney. The device resulted in mean surface and core temperatures at 60 min of (mean ± standard deviation (SD)) 5.8±0.6°C and 5.4±0.5°C respectively, significantly less than those of the control; 16.6±1.4°C and 16.6±1.2°C, respectively (p<0.00001 for both). Moreover, our device mitigated surface temperature increases (2.4±1.3°C vs. 12.9±0.9°C) and core temperature increases (2.8±1.7°C vs. 14.1±1.5°C) at 60 min (p<0.00001). Surface and core temperatures were significantly lower in cooled kidneys compared to controls within 5 minutes of removal from ice (p<0.05). Ex-vivo anastomotic testing was not inhibited or delayed by our device during testing by expert transplant surgeons. CONCLUSIONS: WIT is associated with many adverse outcomes. We developed a novel inexpensive, and easy-to-use aluminum cooling jacket that mitigated temperature increase, and maintained renal temperatures below metabolically-active levels. Source of Funding: None Ottawa, Canada; Kingston, Canada; Ottawa, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e1009-e1009 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Thomas Skinner* More articles by this author Ali Dergham More articles by this author Luke Witherspoon More articles by this author Expand All Advertisement PDF downloadLoading ...

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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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.003

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 head0.016
GPT teacher head0.282
Teacher spread0.266 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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