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Antithymocyte Globulin Induction Allows a Prolonged Delay in the Initiation of Cyclosporine in Heart Transplant Patients with Postoperative Renal Dysfunction

2004· article· en· W2015878807 on OpenAlexaff
Marcelo Cantarovich, Nadia Giannetti, Jeffrey Barkun, Renzo Cecere

Bibliographic record

VenueTransplantation · 2004
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsMcGill UniversityRoyal Victoria HospitalRoyal Victoria Regional Health CentreMcGill University Health Centre
Fundersnot available
KeywordsMedicineRenal transplantGlobulinInduction therapyHeart transplantationInternal medicineUrologyKidneyCardiologyTransplantationChemotherapy

Abstract

fetched live from OpenAlex

The authors evaluated the efficacy of antithymocyte globulin (ATG) induction and delayed initiation of cyclosporine (CsA) in heart transplant (HTx) patients with postoperative renal dysfunction (RD). The authors compared 15 adult HTx patients with postoperative RD (serum creatinine [SCr] > or =150 microM) to 17 controls without postoperative RD. ATG was given daily (1.5 mg/kg/day for 5 days) in controls and every 2 to 5 days in RD patients (total lymphocyte count <200/mm). All patients received corticosteroids and mycophenolate mofetil. The initiation of CsA was delayed in RD patients until SCr had decreased to less than 150 microM (day 12 +/- 8 vs. 2 +/- 1, P<0.0001). One-year patient survival and acute rejection rates were 87% and 27% in RD patients and 88% and 59% in controls, respectively (P=not significant). SCr improved in RD patients and did not differ from controls after the first month. The authors' results suggest that marked prolongation of the period of ATG induction permits a safe delay in the initiation of CsA in HTx patients with postoperative RD.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.013
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations51
Published2004
Admission routes1
Has abstractyes

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