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Record W2122312105 · doi:10.1148/radiol.2312030563

Bronchiolitis Obliterans Syndrome in Lung Transplant Recipients: Can Thin-Section CT Findings Predict Disease before Its Clinical Appearance?

2004· article· en· W2122312105 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRadiology · 2004
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsBronchiolitis obliteransMedicineBronchiectasisAir trappingLungLung transplantationBronchiolitisNuclear medicinePerfusionRadiologyInternal medicineRespiratory system

Abstract

fetched live from OpenAlex

PURPOSE: To determine whether there are thin-section computed tomographic (CT) features that predict bronchiolitis obliterans syndrome (BOS) in lung transplant recipients before the clinical appearance and during the early stages of the disease. MATERIALS AND METHODS: Two hundred ninety-eight thin-section CT scans obtained in 26 lung transplant recipients who did (study group) and 26 lung transplant recipients who did not (control group) develop BOS were reviewed for the presence of mosaic perfusion, bronchiectasis, bronchial wall thickening, and air trapping. BOS was defined by using the recently revised definition of the International Society for Heart and Lung Transplantation. CT scans obtained in the BOS group were divided into three groups: Group A consisted of the last scans obtained before the clinical appearance of BOS; groups B and C consisted of, respectively, the first and last scans obtained after the clinical appearance of BOS. Scans obtained in the control group were acquired during similar posttransplantation periods and matched to scans in each BOS group. Sensitivity, specificity, and positive and negative predictive values were calculated separately for each subgroup. The optimal threshold for each thin-section CT-depicted abnormality was defined by using receiver operating characteristics analysis. RESULTS: The sensitivities of air trapping for the diagnosis of BOS during the periods in which the scans in groups A, B, and C were obtained were 50%, 44%, and 64%, respectively; specificities were 80%, 100%, and 80% respectively. Sensitivities of mosaic perfusion were 4%, 20%, and 36%, respectively; specificities were 100%, 96%, and 96%, respectively. Sensitivities of bronchiectasis were 25%, 24%, and 32%, respectively; specificities were 80%, 80%, and 96%, respectively. Sensitivities of bronchial wall thickening were 4%, 24%, and 40%, respectively; specificities were 96%, 84%, and 80%, respectively. Air trapping was seen intermittently in nine (43%) of 21 patients with CT scans that depicted this finding at least once. CONCLUSION: The value of the finding of air trapping before the clinical appearance and during the early stages of BOS is lower than has been previously reported. When using the recently revised criteria for BOS, the role of thin-section CT as a screening test to evaluate patients with lung transplants appears to be limited.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.005
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.326
Teacher spread0.305 · 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