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Record W1967641319 · doi:10.1517/14712598.2.5.483

New developments in immunosuppressive therapy in renal transplantation

2002· review· en· W1967641319 on OpenAlexaff
Sita Gourishankar, Penny Turner, Philip F. Halloran

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2002
Typereview
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsHeritage Medical Research ClinicUniversity of Alberta
Fundersnot available
KeywordsMedicineCalcineurinAlemtuzumabRituximabTacrolimusAdverse effectTransplantationPharmacologyMonoclonal antibodyBelataceptMonoclonalImmunosuppressionImmunologyInternal medicineKidney transplantationAntibody

Abstract

fetched live from OpenAlex

The introduction of new immunosuppressive agents and protocols has improved outcomes for renal transplant recipients by decreasing the risk of rejection and by increasing the function and lifespan of the allograft. This article reviews the major changes in the combinations of therapies used: calcineurin inhibitors, target of rapamycin inhibitors, mycophenolate mofetil, non-depleting monoclonal versus depleting monoclonal and polyclonal antibodies for induction and increasing emphasis on protocols for reduction or avoidance of steroids and calcineurin inhibitors. The new agents with novel immunological targets such as anti-CD40 ligand, LEA29Y, FTY720, anti-CD20 (rituximab, Rituxan, Mabthera) and anti-CH52 (alemtuzumab, Campath), which are under development but have yet to survive the rigors of clinical trials are also discussed. In the presence of low early rejection rates, immunosuppressive therapy is setting new goals such as better graft function (glomerular filtration rates), reduction in adverse effects such as hypertension, hyperlipidaemia and drug toxicity and, above all, the prevention of late graft deterioration.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.196
GPT teacher head0.416
Teacher spread0.219 · 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 designOther design
Domainnot available
GenreReview

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

Citations30
Published2002
Admission routes1
Has abstractyes

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