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Record W1997050054 · doi:10.1097/tp.0b013e3181889979

Perfusion of Renal Allografts With Verapamil Improves Graft Function

2008· article· en· W1997050054 on OpenAlexaff
Chris Nguan, Alp Şener, Vaishali Karnik, Yves Caumartin, Andrew A. House, Vivian C. McAlister, Patrick Luke

Bibliographic record

VenueTransplantation · 2008
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsVerapamilMedicineUrologyRenal functionCreatininePerfusionTransplantationKidneyAntagonistDiltiazemInternal medicineCalciumReceptor

Abstract

fetched live from OpenAlex

The effect of adding a calcium channel antagonist to kidney allograft perfusate solution was assessed. All renal transplants in which both kidneys from the same donor used for transplantation were studied between November, 2003 and August, 2005 (n=46). The first renal allograft was perfused on the backtable with 1 L of histidine-tryptophan-ketoglurate solution and the second with 1 L of histidine-tryptophan-ketoglurate with 5 mg/L of verapamil. Both organs were transplanted in the usual manner. Baseline demographic parameters were similar between first and second kidney recipients other than BMI and cold ischemic time. At 6 and 12 months, renal function was significantly improved in the verapamil versus control cohort (creatinine clearance 73.8+/-23.5 mL/min vs. 55.8+/-17.0 mL/min, P<0.05 and 87.5+/-28.4 mL/min vs. 59.7+/-21.3 mL/min, P<0.05 respectively). Additionally, rates of hypotension during graft reperfusion and other adverse reactions were similar in both groups. In conclusion, verapamil supplemented perfusate significantly improved renal function posttransplantation.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.379

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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 designBench or experimental
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

Citations16
Published2008
Admission routes1
Has abstractyes

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