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Impact of Gender-Dependent Body Composition Disparity Evaluated by Computed Tomography on Mortality Risk in Cirrhotic Patients

2017· article· en· W2914680781 on OpenAlexaff
Aldo J. Montaño‐Loza, Maryam Ebadi, Puneeta Tandon, Vera C. Mazurak

Bibliographic record

VenueThe American Journal of Gastroenterology · 2017
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineAdipose tissueInternal medicineHazard ratioProportional hazards modelBody mass indexGastroenterologyUnivariate analysisMultivariate analysisConfidence interval

Abstract

fetched live from OpenAlex

Introduction: Prognostic significance of adipose tissue in cirrhotic patients is not clear. We determined the impact of two major body compartments, muscle and adipose tissue, on mortality in 677 cirrhotic patients evaluated for liver transplant (LT). Methods: CT images taken at the 3rd lumbar vertebra were applied to determine 3 body composition variables, each normalized to height to calculate indices (cm2/m2): visceral adipose tissue index (VATI), subcutaneous adipose tissue index (SATI), and skeletal muscle index (SMI). Cox proportional hazard models were conducted to assess associations between mortality and body composition. Results: The majority of patients were male (67%) with a mean age of 57±8 years, MELD score of 14±7 and BMI of 27±6 kg/m2. Patients were followed (21.4 ± 30.2 months) until death (n=258), LT (n=248) or last visit (n=171). Despite similar BMI between genders, men had greater SMI (53±12 vs. 45±9) and VATI (39 ±30 vs. 31±22) whereas SATI (67±52 vs. 48±37) was higher in females [p < 0.001 for each]. Patients who died had lower SMI (49±12 vs. 51±11), and SATI (47±41 vs. 59±44) [p < 0.001 for each], but similar BMI and VATI. By univariate Cox analysis, SATI (HR 0.99; 95% CI 0.99-1.00; p=0.001), MELD (HR 1.05; 95% CI 1.03-1.07; p< 0.001), age (HR 0.98; 95% CI 0.97-1.00; p=0.05), and SMI (HR 0.98; 95% CI 0.96-0.99; p< 0.001) were predictors of mortality. SATI independently associated with mortality (HR 0.99; 95% CI 0.99-1.00; p=0.03), after adjusting for MELD score, SMI and age. In a subanalysis by gender, SATI was lower (52±43 vs. 77±55; p< 0.001) in female patients who died whereas SMI (51±12 vs. 54±12; p=0.04) was lower in deceased male patients. In gender stratified multivariate analyses, MELD (HR 1.07; 95% CI 1.03-1.10; p < 0.001) and SATI (HR 0.99; 95% CI 0.98-1.00; p=0.005) were independent predictors of mortality in females whereas in males, MELD (HR 1.04; 95% CI 1.02-1.07; p < 0.001) and SMI (HR 0.97; 95% CI 0.95-0.99; p=0.002) were significant predictors.Figure: Female patients with the same BMI, A) with low SATI and B) normal SATI.Figure: Male patients with the same BMI, A) with low SMI and B) with normal SMI.Conclusion: A lower amount of subcutaneous adipose tissue associates with higher mortality in female patients. On the other hand, depletion of skeletal muscle predicts mortality in male patients. This emphasizes the necessity for studies to investigate potential interactions between muscle mass and subcutaneous adiposity on mortality in patients with cirrhosis.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.019
GPT teacher head0.322
Teacher spread0.303 · 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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Citations0
Published2017
Admission routes1
Has abstractyes

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