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Record W2893179068 · doi:10.1002/jcsm.12349

Poor performance of psoas muscle index for identification of patients with higher waitlist mortality risk in cirrhosis

2018· article· en· W2893179068 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Cachexia Sarcopenia and Muscle · 2018
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital Edmonton
FundersNational Institute of General Medical SciencesNational Institute on Alcohol Abuse and Alcoholism
KeywordsSarcopeniaMedicineCirrhosisHazard ratioModel for End-Stage Liver DiseaseLiver diseaseBody mass indexInternal medicineSkeletal muscleMortality ratePsoas MusclesGastroenterologySurgeryLiver transplantationConfidence intervalTransplantation

Abstract

fetched live from OpenAlex

Abstract Background Sarcopenia, characterized by low muscle mass, associates with mortality in patients with cirrhosis. Skeletal muscle area in a single computed tomography image at the level of the third lumbar vertebrate (L3) is a valid representative of whole body muscle mass. Controversy remains regarding applicability of psoas muscle to identify patients at greater risk of mortality. We aimed to determine psoas muscle index (PMI) association with skeletal muscle index (SMI) and to evaluate the capacity of PMI to predict liver transplant waitlist mortality. Methods We evaluated listed adult patients with cirrhosis from 2012 to 2013 at four North American liver transplant centres. From L3 computed tomography images within 3 months of listing, we determined SMI and PMI expressed by cm 2 /m 2 . Low SMI was defined as SMI <39 cm 2 /m 2 in women and <50 cm 2 /m 2 in men as published by us earlier. Cut‐offs for PMI to predict mortality were established using a receiver‐operating characteristic analysis. Mortality predictors were determined using competing‐risk analysis with reported results as subdistribution hazard ratios (sHRs). Results Of 353 waitlist candidates, 68% were men, mean age 56 ± 9 years, and Model for End‐stage Liver Disease of 16 ± 8 points. Low SMI was present more frequently in men than women (51 vs. 36%, P = 0.02). Moderately strong correlation between SMI and PMI was observed ( r > 0.7, P < 0.001). Low PMI (males < 5.1 cm 2 /m 2 ; females < 4.3 cm 2 /m 2 ) yielded poor and moderate concordance with low SMI in men and women, respectively (Kappa coefficient 0.31 and 0.63). SMI (39 ± 9 vs. 43 ± 7 cm 2 /m 2 ; P = 0.009) and PMI (4.4 ± 1.3 vs. 5.2 ± 1.1 cm 2 /m 2 ; P = 0.001) were lower in women who died and/or were delisted (compared with non‐deceased patients) whereas men who died and/or were delisted had only lower SMI (47 ± 7 vs. 51 ± 9 cm 2 /m 2 ; P = 0.003), but not PMI compared with non‐deceased patients. In women, both SMI (sHR 0.94, P = 0.048) and PMI (sHR 0.58, P = 0.002) were predictors of mortality, while in men, SMI was significant (sHR 0.95, P = 0.001) and PMI showed a trend to be (sHR 0.85, P = 0.09) associated with mortality. Overall, 104 patients (29%) were misclassified between SMI and PMI categories. Using PMI cut‐offs, 66% and 28% of low SMI men and women, who have a higher risk of mortality, were incorrectly classified as low risk. Conclusions Skeletal muscle index is a more complete and robust measurement than PMI, especially in men with cirrhosis. Low PMI identifies an incomplete subset of patients at increased risk of mortality indicated by low SMI. Given the poor performance of PMI, SMI should not be substituted by PMI.

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.

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)0.001
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 score0.012
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.309
Teacher spread0.284 · 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