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Incidence and prevalence of diabetes mellitus in patients with cystic fibrosis undergoing lung transplantation before and after lung transplantation*

2005· article· en· W1499688610 on OpenAlexaffabout
Denis Hadjiliadis, Janet Madill, Cecilia Chaparro, Anna Tsang, Thomas K. Waddell, L.G. Singer, Michael Hutcheon, Shaf Keshavjee, D. Elizabeth Tullis

Bibliographic record

VenueClinical Transplantation · 2005
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineCystic fibrosisTransplantationDiabetes mellitusLung transplantationInterquartile rangeInternal medicineLungPopulationGastroenterologyIncidence (geometry)Pancreatic diseaseSurgeryPancreasEndocrinology

Abstract

fetched live from OpenAlex

Cystic fibrosis (CF) related diabetes mellitus (DM) occurs in 15% of adult pancreatic insufficient CF patients. Lung transplantation is a treatment option for end-stage CF. We hypothesized that the prevalence of DM increases after lung transplantation. The study population included adult patients undergoing lung transplantation from March 1988 to March 2002 for end-stage CF at the University of Toronto. Demographic data, exocrine pancreatic function, presence of DM before and after transplant, as well as timing of its development after transplant were collected. Eighty-six patients met the study criteria; 77 of 86 (89.5%) of patients were pancreatic insufficient and were further analyzed. Median follow-up post-transplant was 3.3 yr (interquartile range: 1.2-7.2). Their mean age was 29.7 +/- 8.1 yr and 46 of 77 (59.7%) were male. The prevalence of DM increased from 22 of 77 (28.6%) before transplant to 38 of 77 (49.4%) after transplant (p = 0.008). The median time of DM development after transplant was 80 d (range: 13-4352). Sixteen of 55 (29.1%) of pancreatic insufficient patients who were non-diabetic prior to transplant, developed DM after transplant. DM is common in CF patients undergoing lung transplantation and the prevalence increases after transplant.

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 score0.011
Threshold uncertainty score0.748

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 communication0.0000.001
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 head0.010
GPT teacher head0.308
Teacher spread0.299 · 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

Citations77
Published2005
Admission routes2
Has abstractyes

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