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Based on their MNA-SF scale scores, the patients were classified into two groups: the malnutrition group (107 patients) and the non-malnutrition group (21 patients). Univariate and multivariate logistic regression analyses were performed to identify risk factors for malnutrition in CHF patients, which facilitated the development of a nomogram. Correlation analysis was also conducted to explore the relationships between GHRL, MSTN, CRP, and Hs-CRP.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Logistic regression analysis identified age, right upper limb diameter, simplified anorexia scale score, and MSTN as significant risk factors for malnutrition in CHF patients (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05). The nomogram exhibited strong discriminative power during internal validation, with an AUC of 0.917 (95% CI: 0.8439\u20130.990), a Hosmer\u2013Lemeshow test result of \u03c7<jats:sup>2<\/jats:sup>\u2009=\u20097.966 (<jats:italic>P<\/jats:italic>\u2009=\u20090.336), a maximum Youden index of 0.701, an optimal cutoff value of 2.207, sensitivity of 77.7%, and specificity of 92.3%. Calibration curve analysis showed that the nomogram's predictions closely matched the ideal outcomes. Decision curve analysis (DCA) demonstrated that when the threshold probability exceeded 0.1, the nomogram's clinical net benefit surpassed those of the \"full intervention\" and \"no intervention\" strategies, highlighting its strong clinical applicability. Additionally, MSTN was positively correlated with CRP and Hs-CRP, while GHRL was negatively correlated with MSTN, CRP, and Hs-CRP. Significant differences were observed between MSTN, GHRL, and CRP (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>This study supports the hypothesis that age, right upper limb diameter, simplified anorexia scale score, and MSTN are significant risk factors for malnutrition in CHF patients. The nomogram developed in this study demonstrated robust predictive value for identifying malnutrition in this population. Furthermore, the proposed inflammation-GHRL\/MSTN-appetite improvement\/muscle growth-CHF improvement pathway offers a potential regulatory mechanism,which represents a promising direction for research into the mechanisms of malnutrition and muscle loss disorders in patients with CHF.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/s12872-025-04985-1","type":"journal-article","created":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T04:01:38Z","timestamp":1755144098000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A nomogram for predicting malnutrition risk in patients with chronic heart failure and correlation study between GHRL, MSTN, CRP, Hs-CRP"],"prefix":"10.1186","volume":"25","author":[{"given":"Yuling","family":"Zha","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengshuai","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7367-7837","authenticated-orcid":false,"given":"Yuping","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miao","family":"Kong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinlei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Jing","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hailati","family":"Gulimila","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,14]]},"reference":[{"issue":"12","key":"4985_CR1","first-page":"1207","volume":"38","author":"J Zhang","year":"2023","unstructured":"Zhang J, Zhang Y, Zhang L. 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