Evidence map›Paper›PMID 39610547›Full record

ArticleJournal of diabetes and metabolic disorders2024

Evaluating the prevalence and risk factors of sarcopenia in elderly patients with type 2 diabetes mellitus in a Chinese hospital setting.

Shiyue Zou, Tingying Xiao, Mengyao Liu, Li Zhong, Ximin Mou, Jing Lai

Abstract read
In one paragraph

Article in Journal of diabetes and metabolic disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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

7 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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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

6 authors.

Shiyue ZouEndocrinology Department, The First People's Hospital of Longquanyi District, Chengdu, China.
Tingying XiaoEndocrinology Department, The First People's Hospital of Longquanyi District, Chengdu, China.
Mengyao LiuEndocrinology Department, The First People's Hospital of Longquanyi District, Chengdu, China.
Li ZhongEndocrinology Department, The First People's Hospital of Longquanyi District, Chengdu, China.
Ximin MouEndocrinology Department, The First People's Hospital of Longquanyi District, Chengdu, China.
Jing LaiNursing Department, The First People's Hospital of Longquanyi District, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to assess the prevalence and risk factors associated with sarcopenia among hospitalized elderly Chinese patients with Type 2 Diabetes Mellitus (T2DM) to inform more effective management and prevention strategies. Methods: We conducted a cross-sectional analysis of 263 elderly T2DM patients in a hospital in Chengdu, China. Sarcopenia was diagnosed using the 2019 criteria from the Asian Working Group for Sarcopenia (AWGS). Multifactorial logistic regression analysis was employed to explore the determinants of sarcopenia among these patients. Results: The study revealed a sarcopenia prevalence of 42.2% among hospitalized elderly patients with T2DM, with men at 49.44% and women at 38.51%. Patients with sarcopenia were older (72.21 ± 6.841 years vs. 68.55 ± 5.585 years) and had lower Short Physical Performance Battery scores(SPPB), grip strength, and appendicular skeletal muscle mass index(ASMI) compared to non-sarcopenic patients ( Conclusions: Key strategies to manage sarcopenia in elderly T2DM patients include maintaining an optimal BMI, strengthening grip, regular body composition assessments, and controlling waist circumference. These measures improve muscle strength, reduce risks from visceral fat, and enhance patient outcomes and quality of life.

Indexed as

ElderlyPhysical functionRisk factorsSarcopeniaType 2 diabetes mellitus

Identifiers

PMID39610547
PMCPMC11599695

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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.