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ABO-Incompatible Transplantation without Conventional Induction Immunosuppression (IL-2RB or Depleting agents)

2018· article· en· W2884697260 on OpenAlexaff
Feroz Aziz, Benil Hafeeq, Ismail A Naduvileparambil, Sajith Narayanan, Jyotish Chalil Gopinathan, Julie Jose

Bibliographic record

VenueTransplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsASTER
Fundersnot available
KeywordsThymoglobulinMedicineImmunosuppressionRituximabTransplantationBasiliximabTacrolimusRegimenSurgeryInternal medicineImmunologyAntibody

Abstract

fetched live from OpenAlex

Background Transplantation across ABO blood group ( ABOI-Tx) has facilitated to increase donor pool for living donor kidney transplantation. Increased risk of rejection despite augmented immunosuppression has been the concern for many transplant programs in initiating a ABOI-TX program. The benefits on long term graft surivial with induction immunosuppression in immunologically low risk individuals is still not clear. ABOI-Tx recipients are subjcted to increased immunosuppression prior to transplant which could provide and an opportunity to transplant without induction with IL2-R blockers or Lymphocyte depleting agents. Aim Aim of our study is to analyze the outcome of our series of 25 consecutive ABOI-Tx patients who underwent transplantation without routine Thymoglobulin or IL2R-blocker induction. Methods Our study is a prospective observational study for first 25 consecutive patients who had undergone ABOI-Tx from two tertiary care centers in Kerala, India having the same IS protocol. Anti-A and anti-B titers ≤ 1:512 by Gel-method(Biorad) were accepted for desensitization. All patients underwent CDC-crossmatch, Flow-crossmatch and Luminex-anti-HLA-antibody-screen. Desensitization regimen included- Rituximab 200mg on Day -21, Triple IS- Prednisolone 10mg, MMF 1000mg and Tacrolimus 0.05mg/bodywt from Day -14 and Plasma-exchange(PLEX) 3-4 sessions from day -7 to attain titer of 1:8 prior to transplantation. Transplantation was done without induction IS. Results Twenty five patients underwent ABOI-Tx from both centers. Twenty recipients were male. Average age was 34±8 yrs with follow-up of 431±298 days. Eight donors were spouse, 13 were parents and 3 siblings. Average age of donor was 46.3± 10.5years. Twenty-two patients have normal functioning transplant with creatinine 1.23± 0.2 mg/dL. Kaplan-Meier analysis showed patient survival of 91.2% and death censored graft survival of 95.6% at 32 months (Figure 1). Two patients were lost; one on post-op day(POD)3 due to ACS and second on POD-22 due to fungal sepsis. One graft loss occurred due to post-transplant HUS with no evidence of rejection. Of the functioning 22 allograft-recipients one had cellular rejection which resolved with pulse steroids; one developed HUS due to CNI which recovered with PLEX and switch to non-CNI based IS. One patient developed AMR on POD-4 which was completely reversed with PLEX and augmentation of IS. Three patients had CMV viremia and one 3 had BKV viremia ; all resolved with treatment and tailoring of IS. Conclusion Achieving acceptable anti A/B titers prior to transplantation is the most critical step in ABOI-Tx. Avoidance of induction IS can decrease the cost and infectious complications. Our data shows the there is no increased incidence of rejections in the first post transpalnt year for immunologically low risk individuals from histocompatibility standpoint undergoing ABOI-Tx without induction immunosuppression. Figure 1 Sreesan A Sreedharan. Ranjith Narayanan.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.044
GPT teacher head0.339
Teacher spread0.296 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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