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Record W2019561715 · doi:10.1159/000186007

Low Dose Ciclosporin from the Early Postoperative Period Yields Potent Immunosuppression after Renal Transplantation

2008· article· en· W2019561715 on OpenAlexaff
Hugh R. Brady, Kamel S. Kamel, M Harding, Gerald T. Cook, G A deVeber, Carl J. Cardella

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2008
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineAzathioprinePrednisoneImmunosuppressionCiclosporinTransplantationGastroenterologyInternal medicineSurgeryKidney transplantationCyclosporinsUrology

Abstract

fetched live from OpenAlex

This study sought to determine if low doses of ciclosporin (CS) designed to give fasting serum levels of 50-100 ng/ml achieve effective immunosuppression when used from the early postoperative period after renal transplantation. Ninety-four primary renal transplant recipients were studied. Group 1 patients were treated with CS 100 ng/ml and prednisone (0.15 mg/kg/day). Group 2 patients received CS 50 ng/ml, prednisone (0.15 mg/kg/day) and azathioprine (1 mg/kg/day). These patients were compared to a control group of 26 patients (group 3) maintained on only prednisone and azathioprine. CS-treated patients suffered significantly fewer rejection episodes than control subjects (rejection episodes per patient in first year: group 1: 0.3 +/- SD 0.6; group 2: 0.7 +/- SD 0.7; group 3: 1.3 +/- SD 1.1, p less than 0.005). In addition, a greater number of CS-treated patients were completely free of rejection episodes during the first year posttransplant (group 1: 63%; group 2: 64%; group 3: 19%, p less than 0.005). Patient and graft survival were similar in all groups after 1 year (group 1: 92 and 92% respectively; group 2: 95 and 87% respectively; group 3: 96 and 85% respectively). These data suggest that the dose of CS required for effective immunosuppression in vivo is lower than has been previously thought.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.285
Teacher spread0.260 · 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.

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

Citations3
Published2008
Admission routes1
Has abstractyes

Explore more

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