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Record W4362587634 · doi:10.3389/ti.2023.11166

Assessment of Acute Rejection in a Lung Transplant Recipient Using a Sentinel Skin Flap

2023· article· en· W4362587634 on OpenAlexaff
Siba Haykal, S. Juvet, An-Wen Chan, Anne O’Neill, Prodipto Pal, Marcelo Cypel, Shaf Keshavjee

Bibliographic record

VenueTransplant International · 2023
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsMuscular Dystrophy CanadaUniversity Health Network
Fundersnot available
KeywordsMedicineGraft rejectionLungIntensive care medicineSurgeryDermatologyInternal medicineGeneral surgeryTransplantation

Abstract

fetched live from OpenAlex

Dear Editors,Lung transplantation remains one of the only therapeutic options for patients suffering from end-stage lung disease (1).The long-term outcome of lung transplantation is limited because of acute rejection and chronic lung allograft dysfunction (CLAD) (1).The management of lung transplant recipients hinges on selecting the appropriate dose of immunosuppression which remains challenging and is currently guided by drug levels, clinical parameters, pulmonary function and surveillance transbronchial lung biopsies (TBBX).AR is graded according to the International Society for Heart and Lung Transplantation (ISHLT) grading system (2) which can be inaccurate, non-diagnostic, and carries risks including pulmonary hemorrhage, pneumothorax and death.Less invasive means for diagnosing AR are needed for management of lung transplant recipients.The monitoring of acute skin rejection within vascularized composite allotransplants (VCA) involves a biopsy of the skin and subcutaneous tissue and interpreted using the Banff 2007 working classification (3).AR in VCA requires multiple biopsies and can lead to aesthetic deformities.Hence, "sentinel flaps" have become a useful tool.Sentinel flaps are composed of skin, subcutaneous tissue and the vessels which supply them.They are procured from the same donor and transplanted into a recipient in an easily accessible site.They serve as secondary monitoring sites for rejection.These flaps can easily be biopsied with minimal risks and no pain.We describe the first clinical use of a sentinel flap in a lung transplant recipient.Research ethics board approval was obtained.A local donor was required to minimize flap ischemia time.Donor criteria was restricted to match recipient skin colour.The sentinel flap was procured by a team of plastic surgeons, composed of 4 cm × 8 cm of skin, subcutaneous tissue, radial artery and veins from the forearm of the donor from which the lungs were retrieved.The flap was flushed with heparinized saline solution and preserved under static cold storage at 4 ° C. The lungs were preserved in low potassium dextran solution for transportation.Sentinel flap transplantation was performed in the same setting as lung transplantation by a team of plastic surgeons.The radial artery and veins within the flap were anastomosed in an end-to-end fashion to the recipient vessels in the left forearm under microscope magnification.The time required to perform this procedure was 1.5 h after induction.The preservation time limitation of the sentinel flap kept the total lung preservation time well within the usual clinical time.The first patient to have undergone a sentinel flap procedure with bilateral lung transplantation is currently 3 years post-surgery.At the time of transplantation, the patient was 62 years old with chronic obstructive pulmonary disease with several severe exacerbations.The patient was right hand dominant with an intact palmar arch in the left hand and no history of trauma or surgeries to left upper extremity.The patient consented to undergo both procedures.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0020.001

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 head0.040
GPT teacher head0.392
Teacher spread0.352 · 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 designCase report
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

Citations4
Published2023
Admission routes1
Has abstractyes

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