ArticleOsteoporosis and sarcopenia2024
Associations between low muscle mass and clinical characteristics of health population in China.
Article in Osteoporosis and sarcopenia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: The primary aim of this study is to discern the association between specific clinical parameters and low muscle mass (LMM). We endeavor to elucidate the determinants of LMM and the predictive potency of individual factors. Methods: In this retrospective cross-sectional study, we encompassed 450 older adult Chinese participants (252 males and 198 females). Muscle mass quantifications were performed using bioelectrical impedance analysis. Comprehensive data encompassing demographic details (age, sex, height, and weight) and laboratory results (complete blood count, thyroid function, liver function, and renal function) were systematically recorded. Logistic regression models, coupled with receiver operating characteristic curve analytics, were employed to ascertain the variables influencing LMM and to evaluate the predictive validity of each parameter on LMM. Results: Upon confounding adjustment for age, gender, body mass index (BMI), and free thyroxine (FT4) persisted as a determinant of LMM. Specifically, individuals with an FT4 exceeding 1.105 ng/dL exhibited a 1.803-fold increased propensity for LMM relative to those with FT4 values below the specified threshold. Incorporating age, gender, BMI, and FT4 in the diagnostic algorithm enhanced the precision of LMM. The results differ between men and women. In the male population, we can still observe that FT4 has a certain value in the diagnosis of LMM, but this phenomenon is not found in the female population. Conclusions: Elevated FT4 concentrations, albeit within clinically accepted limits, are inversely associated with muscle mass. As such, FT4 could be postulated as a potential biomarker for LMM in geriatric individuals, especially in the male group.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.