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Clinical Implications of Metabolic Risk Factors in Lung Transplant Recipients

2021· article· en· W4254403977 on OpenAlexaffabout
Jason Park, Karan Chohan, Jussi Tikkanen, Sahar Nourouzpour, Mamatha Bhat, Daniel Santa Mina, L.G. Singer, Tereza Martinu, Shaf Keshavjee, Dmitry Rozenberg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMedicineInternal medicineDiabetes mellitusHyperlipidemiaRetrospective cohort studyObesityLungRisk factorLung transplantationMetabolic syndromeGastroenterologyEndocrinology

Abstract

fetched live from OpenAlex

RATIONALE: Metabolic risk factors (RF) have been associated with cardiovascular morbidity and poor graft survival in kidney and liver transplant recipients but have not been wellstudied in lung transplantation (LTx). We aimed to evaluate the prevalence of metabolic RF pre-and post-LTx, and test our hypothesis that pre-transplant metabolic RF are associated with an increased risk of chronic lung allograft dysfunction (CLAD) with detrimental effects on exercise capacity and post-LTx survival. METHODS: Single center, retrospective cohort study of LTx recipients listed 2014-2015 in the Toronto Lung Transplant Program. Clinical characteristics and pre-and post-LTx metabolic RF (hypertension, hyperlipidemia, diabetes, and obesity with BMI 30 kg/m 2 ) were abstracted from medical records. Subjects were categorized by number of pre-LTx metabolic RF present: 0; 1-2; and 3-4. Post-LTx six-minute walk distance (6MWD), CLAD and mortality within three-years post-transplant were compared across groups using one-way ANOVA and multivariable regression adjusting for age, sex, and diagnosis. RESULTS: 227 LTx recipients [median age 58 years, 60% males, BMI: 24.9 5.1 kg/m 2 , and 54% with interstitial lung disease (ILD)] were studied. Pre-LTx RF prevalence was: hypertension in 63 patients (28%), hyperlipidemia in 79 (35%), diabetes in 40 (18%) and obesity in 44 (19%). 43% of LTx recipients had no RF, 46% had 1-2 and 11% had 3-4 at time of transplant. The prevalence of 3-4 RF post-LTx was 26% at one and 34% at three-years, with obesity rates increasing to 31% by three-years. LTx recipients with 3-4 RF were more likely to have ILD (69%) as primary diagnosis compared to the other two RF groups (ILD 52%, p=0.01), but no differences were observed with respect to age, sex or pre-LTx 6MWD (cohort 304 m 108). Based on pre-LTx risk groups, there were significant differences in 6MWD improvement across groups in the first two-years post-transplant (Figure), which remained significant after adjustment for age, sex, and diagnosis. By three-years post-LTx, incidence of CLAD was 55/227 (24%) and all-cause mortality was 64/227 (28%), but no independent differences were observed between risk groups with respect to CLAD [3-4 vs. 1-2 RF; HR: 1.67 95% CI (0.8 -3.7), p=0.13] or all-cause mortality [HR: 1.74 95% (0.9 -3.4), p=0.14]. CONCLUSION: Metabolic RF were prevalent pre-and post-LTx, and were associated with lower exercise capacity post-LTx, but not CLAD or survival. Future studies exploring lifestyle interventions aimed at improving pre-and post-LTx metabolic RF and functional capacity are needed.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.423
Teacher spread0.354 · 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 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".

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Citations2
Published2021
Admission routes2
Has abstractyes

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