Evidence map›Paper›PMID 34757481›Full record

ArticleSkeletal radiology2022

Utility of multidetector computed tomography quantitative measurements in identifying sarcopenia: a propensity score matched study.

Yu-Qiang Zuo, Zhi-Hong Gao, Zheng Wang, Qing Liu, Xu Yang, Yu-Ling Yin, Ping-Yong Feng

Abstract read
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In one paragraph

Article in Skeletal radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 33% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Yu-Qiang ZuoDepartment of Physical Examination, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Zhi-Hong GaoDepartment of Physical Examination, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Zheng WangDepartment of Respiration, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Qing LiuDepartment of Radiology, The Second Hospital of Hebei Medical University, Xinhua District, No. 215 Heping West Road, Shijiazhuang, 050000, Hebei, China.
Xu YangDepartment of Physical Examination, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yu-Ling YinDepartment of Physical Examination, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Ping-Yong FengDepartment of Radiology, The Second Hospital of Hebei Medical University, Xinhua District, No. 215 Heping West Road, Shijiazhuang, 050000, Hebei, China. xjfpy@163.com.
Hebei Medical University · CNSecond Hospital of Hebei Medical University · CN

Funding

Medical Science Research Project of Hebei Province No. 20211544
6 · The paper itself

Abstract

objectiveTo evaluate the utility of multidetector computed tomography MDCT quantitative measurements in identifying sarcopenia. MATERIALS AND

methodsThe clinical data and MDCT images of 64 patients of sarcopenia and 184 non-sarcopenic participants between October 2020 and January 2021were retrospectively analyzed. Propensity score matching was used to match the sarcopenic patients with the non-sarcopenic participants. Two radiologists independently measured the cross-sectional area (CSA) of skeletal muscle and intramuscular fat tissue and CT density of skeletal muscle at the middle L3 vertebral level on CT images of all participants. Intra-observer agreement was evaluated via intraclass correlation coefficients (ICC). A receiver operating characteristic (ROC) curve was built for each variable. Correlations between CT parameters and clinical data were assessed via Pearson or Spearman correlation coefficient.

resultsA total of 74 participants (mean age 72 ± 4 years, range 66-85 years; 38 men and 36 women) were included, comprising 37 sarcopenic patients and 37 non-sarcopenic participants. There were no significant intergroup differences regarding age, sex ratio, and body mass index (BMI) (P < 0.05). The CSA and density of skeletal muscle measured by two radiologists were reliable (ICC ≥ 0.75, P < 0.001). Compared with the sarcopenic group, the non-sarcopenic group had a significantly greater CSA and CT density of the total skeletal muscle (TSM) and paraspinal skeletal muscle (PSM) and skeletal muscle index at L3 level (L3 SMI) (P < 0.05). The fat infiltration ratio (FIR) of TSM, PSM, and psoas muscle was significantly higher in the sarcopenic group than that in non-sarcopenic participants (P < 0.05). ROC curve analysis showed the PSM FIR + PSM CT density (PSM D) had the best predictive value for sarcopenia (AUC = 0.836). The PSM FIR and age were moderately positively correlated (r = 0.410, P < 0.001).

conclusionFat infiltration of skeletal muscle had better predictive value than L3 SMI in the diagnosis of sarcopenic. The PSM FIR + PSMD had the best predictive value for sarcopenia, which was moderately positively correlated with age.

Indexed as

SarcopeniaAgedAged, 80 and overFemaleHumansMaleMultidetector Computed TomographyMuscle, SkeletalPropensity ScorePsoas MusclesRetrospective StudiesComputed tomographyCross-sectional areaFatty infiltration ratioParaspinal muscleSarcopeniaSkeletal muscle

Identifiers

PMID34757481
OpenAlexW3214558176

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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.