Evidence map›Paper›PMID 36280811›Full record

ArticleBMC musculoskeletal disorders2022

Based on CT at the third lumbar spine level, the skeletal muscle index and psoas muscle index can predict osteoporosis.

Cheng-Bin Huang, Duo-Duo Lin, Jian-Qiang Huang, Wei Hu

Open access · goldAbstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 10% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
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

4 authors at 2 institutions in 1 country.

Cheng-Bin HuangDepartment of Orthopaedic Surgery, The Second Affiliated Hospital and Yuying Childrens Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Duo-Duo LinThe Second Affiliated Hospital and Yuying Childrens Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Jian-Qiang HuangThe Second Affiliated Hospital and Yuying Childrens Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Wei HuDepartment of Orthopaedic Surgery, The Second Affiliated Hospital and Yuying Childrens Hospital of Wenzhou Medical University, Wenzhou, 325000, China. max209190@126.com.
Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University · CNWenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the increasing number of studies on osteoporosis and muscle adipose tissue, existing studies have shown that skeletal muscle tissue and adipose tissue are closely related to osteoporosis by dual-energy x-ray absorptiometry (DXA) measurement. However, few studies have explored whether the skeletal muscle and adipose tissue index measured at the lumbar spine 3 (L3) level are closely related to bone mineral density (BMD) and can even predict osteoporosis. Therefore, this study aimed to prove whether skeletal muscle and adipose tissue index measured by computed tomography (CT) images based on a single layer are closely related to BMD.

methodsA total of 180 participants were enrolled in this study to obtain skeletal muscle index (SMI), psoas muscle index (PMI), subcutaneous fat index (SFI), visceral fat index (VFI), and the visceral-to-subcutaneous ratio of the fat area (VSR) at L3 levels and divide them into osteoporotic and normal groups based on the T-score of DXA. Spearman rank correlation was used to analyze the correlation between SMI, PMI, SFI, VFI, VSR, and BMD. Similarly, spearman rank correlation was also used to analyze the correlation between SMI, PMI, SFI, VFI, VSR, and the fracture risk assessment tool (FRAX). Receiver operating characteristic (ROC) was used to analyze the efficacy of SMI, PMI, SFI, VFI, and VSR in predicting osteoporosis.

resultsBMD of L1-4 was closely correlated with SMI, PMI, VFI and VSR (r = 0.199 p = 0.008, r = 0.422 p < 0.001, r = 0.253 p = 0.001, r = 0.310 p < 0.001). BMD of the femoral neck was only correlated with PMI and SFI (r = 0.268 p < 0.001, r = - 0.164 p-0.028). FRAX (major osteoporotic fracture) was only closely related to PMI (r = - 0.397 p < 0.001). FRAX (hip fracture) was closely related to SMI and PMI (r = - 0.183 p = 0.014, r = - 0.353 p < 0.001). Besides, FRAX (major osteoporotic fracture and hip fracture) did not correlate with VFI, SFI, and VSR. SMI and PMI were statistically significant, with the area under the curve (AUC) of 0.400 (95% confidence interval 0.312-0.488 p = 0.024) and 0.327 (95% confidence interval 0.244-0.410 p < 0.001), respectively. VFI, SFI, and VSR were not statistically significant in predicting osteoporosis.

conclusionsThis study demonstrated that L3-based muscle index could assist clinicians in the diagnosis of osteoporosis to a certain extent, and PMI is superior to SMI in the diagnosis of osteoporosis. In addition, VFI, SFI, and VSR do not help clinicians to diagnose osteoporosis well.

Indexed as

Hip FracturesOsteoporosisOsteoporotic FracturesAbsorptiometry, PhotonBone DensityHumansLumbar VertebraePsoas MusclesRisk AssessmentRisk FactorsTomography, X-Ray ComputedBone mineral densityComputed tomographyOsteoporosisPsoas muscle indexSkeletal muscle index

Identifiers

PMID36280811
PMCPMC9590212
OpenAlexW4307129343

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.