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Record W4403047526 · doi:10.1093/ndt/gfae218

Early steroid withdrawal and kidney transplant outcomes in first-transplant and retransplant recipients

2024· article· en· W4403047526 on OpenAlexaff
Sunjae Bae, Yusi Chen, Shaifali Sandal, Krista L. Lentine, Mark A. Schnitzler, Dorry L. Segev, Mara McAdams‐DeMarco

Bibliographic record

VenueNephrology Dialysis Transplantation · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsMcGill University Health Centre
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingNational Institute of Allergy and Infectious DiseasesHennepin Healthcare Research InstituteU.S. Department of Health and Human Services
KeywordsMedicineHazard ratioImmunosuppressionInternal medicineProportional hazards modelConfoundingKidney transplantationTransplantationLogistic regressionSurgeryConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Early steroid withdrawal (ESW) is often preferred over conventional steroid maintenance (CSM) therapy for kidney transplant recipients with low immunological risks because it may minimize immunosuppression-related adverse events while achieving similar transplant outcomes. However, the risk-benefit balance of ESW could be less favorable in retransplant recipients given their unique immunological risk profile. We hypothesized that the association of ESW with transplant outcomes would differ between first-transplant and retransplant recipients. METHODS: To assess whether the impact of ESW differs between first and retransplant recipients, we studied 210 086 adult deceased-donor kidney transplant recipients using the Scientific Registry of Transplant Recipients. Recipients who discontinued maintenance steroids before discharge from transplant admission were classified with ESW; all others were classified with CSM. We quantified the association of ESW (vs CSM) with acute rejection, death-censored graft failure and death, addressing retransplant as an effect modifier, using logistic/Cox regression with inverse probability weights to control for confounders. RESULTS: In our cohort, 26 248 (12%) were retransplant recipients. ESW was used in 30% of first-transplant and 20% of retransplant recipients. Among first-transplant recipients, ESW was associated with no significant difference in acute rejection {adjusted odds ratio (aOR) = 1.04 [95% confidence interval (CI) = 1.00-1.09]}, slightly higher hazard of graft failure [hazard ratio (HR) = 1.09 (95% CI = 1.05-1.12)] and slightly lower mortality [HR = 0.93 (95% CI = 0.91-0.95)] compared with CSM. Nonetheless, among retransplant recipients, ESW was associated with notably higher risk of acute rejection [OR = 1.42 (95% CI = 1.29-1.57); interaction P < .001] and graft failure [HR = 1.24 (95% CI = 1.14-1.34); interaction P = .003], and similar mortality [HR = 1.01 (95% CI = 0.94-1.08); interaction P = .04]. CONCLUSIONS: In retransplant recipients, the negative impacts of ESW on transplant outcomes appear to be non-negligible. A more conservatively tailored approach to ESW might be necessary for retransplant recipients.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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 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

Citations8
Published2024
Admission routes1
Has abstractyes

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