Evidence map›Paper›PMID 38099314›Full record

ArticlePeerJ2023

Feasibility of using chest computed tomography (CT) imaging at the first lumbar vertebra (L1) level to assess skeletal muscle mass: a retrospective study.

Shaohua Liu, Xia Han, Jianjun Li, Xia Xie, Yunkai Yang, Wangyan Jiang, Li Liu, Zhelong Liu

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 12 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

8 authors at 4 institutions in 1 country.

Shaohua Liu *Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0003-1448-3827
Xia Han *Wuhan Wuchang Hospital, Wuhan, China.
Jianjun LiDepartment of Radiology, Tongji Hospital, Tongji Medical College; Huazhong University of Science and Technology, Wuhan, China.
Xia XieSchool of Computer Science and Technology, Hainan University, Haikou, China.
Yunkai YangEight-year Program of Clinical Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Wangyan JiangDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Li LiuDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhelong LiuDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
National Clinical Research Center for Digestive Diseases · CNTongji Hospital · CNHainan University · CNWuchang University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Skeletal muscle mass is an essential parameter for diagnosing sarcopenia. The gold standard for assessing skeletal muscle mass is using computed tomography (CT) to measure skeletal muscle area at the third lumbar vertebra (L3) level. This study aims to investigate whether skeletal muscle mass could be evaluated at the first lumbar vertebra (L1) level using images obtained from routine chest CT scans. Methods: Skeletal muscle index (SMI, cm Results: A significantly higher SMI at the L1 level was found in males than in females (43.88 ± 6.33 cm Conclusions: Based on a population from central China, the correlated indicators obtained at the L1 level from routine chest CT scans may serve as effective surrogate markers for those at the L3 level in assessing overall skeletal muscle mass.

Indexed as

SarcopeniaFeasibility StudiesFemaleHumansMaleMuscle, SkeletalRetrospective StudiesSpineTomography, X-Ray ComputedComputed tomographySarcopeniaSkeletal muscle massThe first lumbar vertebra

Identifiers

PMID38099314
PMCPMC10720423
OpenAlexW4389566757

What OpenQuestion holds

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Registered trials

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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.