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Record W2886658599 · doi:10.1186/s13014-018-1089-8

Stereotactic ablative radiotherapy for early-stage lung cancer following double lung transplantation

2018· article· en· W2886658599 on OpenAlexaff
Hanbo Chen, Jussi Tikkanen, Gabriel Boldt, Alexander V. Louie

Bibliographic record

VenueRadiation Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General HospitalUniversity Health NetworkLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineAblative caseRadiation therapyStage (stratigraphy)Lung cancerLungLung transplantationRadiologyRadiosurgeryTransplantationOncologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Development of primary lung cancer in donor lung post-lung transplantation is very rare, with few described cases. The safety of stereotactic ablative radiotherapy (SABR) for early-stage lung cancer arising from donor lung is unclear. CASE PRESENTATION: Herein, we present a case of a patient with a Stage IB adenocarcinoma arising from donor lung 8 years post-double lung transplantation, which was performed due to advanced emphysema. The patient was ineligible for surgical management due to chronic lung allograft dysfunction, which significantly compromised pulmonary function. Full dose SABR was delivered with curative intent after a discussion with the patient. The patient tolerated the treatment well, with one episode of subacute toxicity that resolved with treatment. There was no evidence of recurrence at 15 months post-treatment and the patient's pulmonary function did not deviate from the pre-SABR baseline. CONCLUSIONS: SABR appears feasible for medically-inoperable early-stage primary lung adenocarcinoma in the setting of previous double-lung transplantation.

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 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)0.000
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 score0.157
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.433
Teacher spread0.399 · 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 teacher head, 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

Citations6
Published2018
Admission routes1
Has abstractyes

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