Evidence map›Paper›PMID 40640791›Full record

ArticleBMC pulmonary medicine2025

Determination of the frequency of sarcopenia in patients admitted with COPD diagnosis with the SARC-F survey.

Çagri Besnek, Burcu Akkok, Hatice Sahin, Murat Sahin, Nurhan Atilla, Hasan Kahraman

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Article in BMC pulmonary medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Çagri BesnekDepartment of Pulmonology, Faculty of Medicine, Sutcu Imam University, Kahramanmaras, Türkiye.ORCID http://orcid.org/0009-0002-1001-5022
Burcu AkkokDepartment of Pulmonology, Faculty of Medicine, Sutcu Imam University, Kahramanmaras, Türkiye. bkaraokur@hotmail.com.ORCID http://orcid.org/0000-0001-7664-2657
Hatice SahinDepartment of Pulmonology, Faculty of Medicine, Sutcu Imam University, Kahramanmaras, Türkiye.ORCID http://orcid.org/0000-0002-3317-3640
Murat SahinDepartment of Endocrinology, Faculty of Medicine, Sutcu Imam University, Kahramanmaras, Türkiye.ORCID http://orcid.org/0000-0001-7969-9157
Nurhan AtillaDepartment of Pulmonology, Faculty of Medicine, Sutcu Imam University, Kahramanmaras, Türkiye.ORCID http://orcid.org/0000-0003-4127-4924
Hasan KahramanDepartment of Pulmonology, Faculty of Medicine, Sutcu Imam University, Kahramanmaras, Türkiye.ORCID http://orcid.org/0000-0002-6196-1521

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSarcopenia is recognized as a consequence of hormones, immune system changes, and chronic inflammatory diseases that occur with aging. For the diagnosis of sarcopenia, the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria are used. Furthermore, the fat-free mass index (FFMI), a marker of sarcopenia, is used to predict sarcopenic patients. In patients with chronic obstructive pulmonary disease (COPD), systemic inflammation, advanced age, sedentary lifestyle, and poor nutrition may lead to sarcopenia. This study aimed to investigate the contribution of the SARC-F questionnaire, a simple questionnaire to rapidly diagnose sarcopenia, in the prediction of sarcopenic patients secondary to COPD.

methodOur study included patients aged 50 years and older who were diagnosed with COPD and who signed an informed consent form. Demographic data, symptoms, anthropometric measurements, pulmonary function tests, a 6-minute walk test, and blood parameters were evaluated. The SARC-F questionnaire was administered to the participants. In our study, the correlation of sarcopenic patients according to FFMI with the SARC-F questionnaire was analyzed. The significance value was accepted as p < 0.05 in the statistical analysis of the study's data.

resultsThe data from 130 participants were analyzed in the study. Of the patients, 99 (76.2%) were male, 31 (23.8%) were female, and the mean age was 68.0 ± 9.6 years. According to the SARC-F results, the number of patients with < 4 points was 103 and the number of patients with ≥ 4 points was 27. According to the FFMI, the number of patients without sarcopenia was 96 and the number of patients with sarcopenia was 34. A statistically significant correlation was found between the FFMI and the sarcopenia indicators assessed by the SARC-F (p < 0.001).

conclusionPatients' adaptation to a sedentary lifestyle, COPD exacerbations causing systemic inflammation, and advanced age increase the likelihood of sarcopenia. The advanced age of patients diagnosed with COPD normalizes the loss of muscle strength, which delays the early diagnosis and treatment of sarcopenia. This study emphasizes the importance and practical usefulness of the SARC-F questionnaire in achieving the goals of early diagnosis and treatment of sarcopenia in all COPD patients.

Indexed as

Pulmonary Disease, Chronic ObstructiveSarcopeniaAgedFemaleHumansMaleMiddle AgedSurveys and QuestionnairesBIACOPDFFM indexSARC-FSarcopenia

Identifiers

PMID40640791
PMCPMC12243166

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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.