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Record W3164274884 · doi:10.1055/s-0041-1729542

Acute Rejection in the Modern Lung Transplant Era

2021· review· en· W3164274884 on OpenAlexaff
B. Renaud-Picard, Angela Koutsokera, Michael Cabanero, Tereza Martinu

Bibliographic record

VenueSeminars in Respiratory and Critical Care Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineImmunosuppressionIntensive care medicineLung transplantationLungComplicationRefractory (planetary science)Lung functionFirst lineImmunologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Acute cellular rejection (ACR) remains a common complication after lung transplantation. Mortality directly related to ACR is low and most patients respond to first-line immunosuppressive treatment. However, a subset of patients may develop refractory or recurrent ACR leading to an accelerated lung function decline and ultimately chronic lung allograft dysfunction. Infectious complications associated with the intensification of immunosuppression can also negatively impact long-term survival. In this review, we summarize the most recent evidence on the mechanisms, risk factors, diagnosis, treatment, and prognosis of ACR. We specifically focus on novel, promising biomarkers which are under investigation for their potential to improve the diagnostic performance of transbronchial biopsies. Finally, for each topic, we highlight current gaps in knowledge and areas for future research.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.065
GPT teacher head0.434
Teacher spread0.369 · 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 designNot applicable
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

Citations19
Published2021
Admission routes1
Has abstractyes

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