MétaCan
Menu
Back to cohort
Record W3046247864 · doi:10.1002/jcsm.12604

Sarcopenia and low muscle radiodensity associate with impaired FEV<sub>1</sub> in allogeneic haematopoietic stem cell transplant recipients

2020· article· en· W3046247864 on OpenAlexafffund
Asmita Mishra, Kevin Bigam, Martine Extermann, Rawan Faramand, Kerry Thomas, Joseph A. Pidala, Vickie E. Baracos

Bibliographic record

VenueJournal of Cachexia Sarcopenia and Muscle · 2020
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
FundersNational Cancer InstituteAlberta Cancer FoundationCanadian Institutes of Health ResearchMoffitt Cancer Center
KeywordsMedicineSarcopeniaSpirometryInternal medicineConfidence intervalTransplantationLung cancerGastroenterologySurgeryAsthma

Abstract

fetched live from OpenAlex

Abstract Background Quantification of skeletal muscle using computed tomography (CT) is accessible using cancer patients' standard oncologic images. Reduced muscle mass may be related to reduced respiratory muscle strength; however, the impact of this on lung functional parameters is not characterized in adult allogeneic haematopoietic stem cell transplant (alloHCT) recipients. Methods A consecutive retrospective series (n = 296) of patients who had alloHCT at a comprehensive cancer centre between March 2005 and April 2015 were included. Pre‐transplant CT scans were used to quantify skeletal muscle and adipose tissue at the fourth thoracic (T4) and/or third lumbar (L3) level. Tumour and patient characteristics were recorded, including forced expiratory volume in 1 second (FEV1) by spirometry. Regression models were created to characterize predictive relationships. Results A total of 296 patients (♂n = 161; ♀n = 135) were included, all of whom had chest CT as part of standard care; a subset of these (n = 215, 72.6%) also had abdominal CT. Diagnoses were non‐Hodgkins lymphoma (n = 165), acute myeloid leukaemia (n = 66), Hodgkin's disease (n = 14), acute lymphocytic leukaemia (n = 14), myelodysplastic syndromes (n = 18), and other (n = 19). In multivariable linear regression adjusted for sex (P < 0.0001), age (P < 0.0001), haematopoietic cell transplantation‐specific co‐morbidity index (P = 0.010), and parameters of pulmonary function testing (defined by spirometry, P < 0.0001), both T4 muscle index [β 0.127 (95% confidence interval 0.019; 0.252), P < 0.0001] and T4 muscle radiodensity [β 0.132 (95% confidence interval 0.087; 0.505), P = 0.006] were independently associated with FEV1; disease risk index (P = 0.877) and Karnofsky performance status (P = 0.548) were not associated with FEV1. Similar conclusions were obtained when L3 muscle index and radiodensity were considered. Unlike T4, L3 muscle index values can be compared with published cut‐off values for sarcopenia. Overall rates of sarcopenia were uniformly higher in the HCT population than in age‐matched and sex‐matched patients with solid tumours [alloHCT ♂64.7% vs. solid tumour ♂56.6% (P < 0.001); alloHCT ♀57.6% vs. solid tumour ♀36.0% (P < 0.001)]. Significant but moderate correlations (P < 0.001) were found for muscle area and radiodensity between L3 and T4, for both men and women; adipose tissue quantity also correlated significantly (P < 0.001) between L3 and T4 for both men and women. Conclusions Lumbar or thoracic CT images are useful for body composition assessment in this population and reveal high rates of sarcopenia, similar to those reported in very elderly patients. Reduced muscle mass and radiodensity associate with impaired FEV1 even after adjustment for clinical covariables including co‐morbidities, performance status, disease risk, and mild intrinsic pulmonary disease (chronic obstructive pulmonary disease) defined by spirometry.

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 score0.007

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.245
Teacher spread0.222 · 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".

Quick stats

Citations34
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Cachexia Sarcopenia and MuscleSame topicNutrition and Health in AgingFrench-language works237,207