Metabolic complications in lung transplantation for cystic fibrosis - A case control study
Bibliographic record
Abstract
Background: Metabolic complications post-lung transplant are poorly understood and little is known about how these complications differ between patients with or without cystic fibrosis (pwCF and pwoCF). This study compared post-lung transplant outcomes between pwCF and pwoCF relating to survival and incidence of diabetes, dyslipidaemia, hypertension, and renal impairment. Methods: A retrospective (2004-2017) case-control study involving 90 pwCF and 90 pwoCF (age, sex and year of transplant matched) was conducted. Demographic variables, pre/post-transplant metabolic diseases, blood investigations and medications were extracted. Descriptive statistics were used to describe the cohort. Mann-Whitney U and Chi-squared tests were used to analyse morbidity and mortality data. Regression analyses were used to identity independent variables that impacted clinical outcomes. Kaplan Meier analysis with log-rank testing was used to compare survival. Results: PwCF were younger, had lower BMIs, and were less likely to have pre-transplant extracorporeal membrane oxygenation (ECMO) use. A total of 37 pwCF and 41 pwoCF died (p = 0.65) during the period of observation with no differences in survival. Adjusting for covariates of age, sex and BMI via multiple logistic regression, CF status was associated with a dramatic increased risk of new-onset diabetes post-transplant (adjusted odds ratio 28.7; 95 % CI, 28.76 to 108.7). No other differences in adjusted risk were found. Conclusions: As pwCF had a greater adjusted risk of developing new post-transplant diabetes and experienced metabolic complications at similar rates as pwoCF, the findings highlight the need for rigorous monitoring of pwCF for possible metabolic complications post-transplant.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".