{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T14:07:44Z","timestamp":1793714864236,"version":"4.6.1"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T00:00:00Z","timestamp":1740614400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>As the global population ages, cardiovascular diseases, particularly heart failure (HF), have become leading causes of mortality and disability among elderly patients. Diabetes and hypertension are major risk factors for cardiovascular diseases, making this group especially vulnerable to HF. Current clinical tools for predicting HF risk are often complex, requiring extensive clinical parameters and laboratory tests, which limit their practical application. Therefore, a need exists for a predictive model that is both simple and effective in assessing HF risk in elderly patients with diabetes and hypertension.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>This study utilized data from the National Health and Nutrition Examination Survey, spanning seven cycles from 2003 to 2016, including 71 058 subjects. The study focused on elderly patients (aged 65 and above) diagnosed with both diabetes and hypertension, ultimately including 1445 participants. We examined seven novel composite indices: a body shape index (ABSI), atherogenic index of plasma (AIP), BARD score, body fat percentage (BFP), body roundness index (BRI), fatty liver index (FLI), and prognostic nutritional index (PNI). These indices were selected for their simplicity and ease of calculation from routine clinical assessments. The primary outcome was HF status, and data pre-processing included imputation for missing values using random forest algorithms. Various machine learning models were applied, including random forest, logistic regression, XGBoost, and others, with model performance assessed through metrics like accuracy, precision, recall, F1 score, and receiver operating characteristic-area under the curve (ROC AUC). The best-performing model was further analysed using SHAP (SHapley Additive exPlanations) values to determine feature importance. The study found that the XGBoost model demonstrated superior performance across all evaluation metrics, with an area under the curve (AUC) value of 0.96. Significant predictors of HF included BRI and PNI, which had the highest SHAP values, indicating their substantial influence on model predictions. The study also highlighted the robust predictive capabilities of AIP, particularly in assessing cardiovascular events in elderly patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The study demonstrates that novel composite indices like ABSI, AIP, BARD score, BFP, BRI, FLI, and PNI have significant potential in predicting HF risk among elderly diabetic and hypertensive patients. These indices offer clinicians new tools for cardiovascular risk assessment that are simpler and potentially more effective in clinical practice. Future research should focus on validating these findings in different populations and exploring their longitudinal predictive power.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Lay summary<\/jats:title>\n                    <jats:p>This study explores simple and effective ways to predict heart failure risk in elderly patients with diabetes and hypertension by using novel, easy-to-calculate indices.Indices like ABSI, AIP, BARD score, BFP, BRI, FLI, and PNI are highly effective in predicting heart failure risk in elderly diabetic and hypertensive patients.The XGBoost machine learning model, which uses these indices, demonstrated strong predictive power with an AUC of 0.96, highlighting its clinical applicability.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/eurjpc\/zwaf081","type":"journal-article","created":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T15:23:15Z","timestamp":1739892195000},"page":"53-63","source":"Crossref","is-referenced-by-count":34,"title":["Advanced prediction of heart failure risk in elderly diabetic and hypertensive patients using nine machine learning models and novel composite indices: insights from NHANES 2003\u20132016"],"prefix":"10.1093","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-6135-8950","authenticated-orcid":false,"given":"Qiyuan","family":"Bai","sequence":"first","affiliation":[{"name":"The First Clinical Medical College, Lanzhou University , 222 Tianshui South Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Chen","sequence":"additional","affiliation":[{"name":"The First Clinical Medical College, Lanzhou University , 222 Tianshui South Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Beijing Anzhen Hospital, Capital Medical University , 100029 Beijing ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University , 100029 Beijing ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shidong","family":"Liu","sequence":"additional","affiliation":[{"name":"The First Clinical Medical College, Lanzhou University , 222 Tianshui South Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]},{"name":"Department of Cardiovascular Surgery, First Hospital of Lanzhou University , No. 1 Donggang West Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wentao","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Beijing Anzhen Hospital, Capital Medical University , 100029 Beijing ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuhua","family":"Li","sequence":"additional","affiliation":[{"name":"The First Clinical Medical College, Lanzhou University , 222 Tianshui South Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Song","sequence":"additional","affiliation":[{"name":"The First Clinical Medical College, Lanzhou University , 222 Tianshui South Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]},{"name":"Department of Cardiovascular Surgery, First Hospital of Lanzhou University , No. 1 Donggang West Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cuntao","family":"Yu","sequence":"additional","affiliation":[{"name":"The First Clinical Medical College, Lanzhou University , 222 Tianshui South Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]},{"name":"Department of Cardiovascular Surgery, First Hospital of Lanzhou University , No. 1 Donggang West Road, Chengguan District, 730000 Lanzhou, Gansu ,","place":["China"]},{"name":"Department of Cardiovascular Surgery, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College , No. 167 North Lishi Road, Xicheng District, 100029 Beijing ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,2,27]]},"reference":[{"key":"2026010607174397500_zwaf081-B1","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1136\/heartjnl-2020-316793","article-title":"Income level and outcomes in patients with heart failure with universal health coverage","volume":"107","author":"Hung","year":"2021","journal-title":"Heart"},{"key":"2026010607174397500_zwaf081-B2","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1093\/eurjpc\/zwad223","article-title":"Prevalence of heart failure stages in the general population and implications for heart failure prevention: reports from the China Hypertension Survey 2012\u201315","volume":"30","author":"Cai","year":"2023","journal-title":"Eur J Prev Cardiol"},{"key":"2026010607174397500_zwaf081-B3","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1186\/s12933-021-01313-7","article-title":"Incidence of atrial fibrillation, ischaemic heart disease and heart failure in patients with diabetes","volume":"20","author":"Groenewegen","year":"2021","journal-title":"Cardiovasc Diabetol"},{"key":"2026010607174397500_zwaf081-B4","doi-asserted-by":"crossref","first-page":"e554","DOI":"10.1016\/j.amjmed.2020.03.038","article-title":"Association of multimorbidity with cardiovascular endpoints and treatment effectiveness in patients 75 years and older with atrial fibrillation","volume":"133","author":"Claxton","year":"2020","journal-title":"Am J Med"},{"key":"2026010607174397500_zwaf081-B5","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1001\/jamacardio.2019.5850","article-title":"Prognostic models derived in PARADIGM-HF and validated in ATMOSPHERE and the Swedish Heart Failure Registry to predict mortality and morbidity in chronic heart failure","volume":"5","author":"Simpson","year":"2020","journal-title":"JAMA Cardiol"},{"key":"2026010607174397500_zwaf081-B6","doi-asserted-by":"crossref","first-page":"e39504","DOI":"10.1371\/journal.pone.0039504","article-title":"A new body shape index predicts mortality hazard independently of body mass index","volume":"7","author":"Krakauer","year":"2012","journal-title":"PLoS One"},{"key":"2026010607174397500_zwaf081-B7","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1186\/s12944-022-01732-9","article-title":"Evaluating the use of novel atherogenicity indices and insulin resistance surrogate markers in predicting the risk of coronary artery disease: a case\u2013control investigation with comparison to traditional biomarkers","volume":"21","author":"Mahdavi-Roshan","year":"2022","journal-title":"Lipids Health Dis"},{"key":"2026010607174397500_zwaf081-B8","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/s12933-022-01483-y","article-title":"The associations of hepatic steatosis and fibrosis using fatty liver index and BARD score with cardiovascular outcomes and mortality in patients with new-onset type 2 diabetes: a nationwide cohort study","volume":"21","author":"Park","year":"2022","journal-title":"Cardiovasc Diabetol"},{"key":"2026010607174397500_zwaf081-B9","doi-asserted-by":"crossref","first-page":"4433","DOI":"10.1002\/cam4.3076","article-title":"Body surface area, height, and body fat percentage as more sensitive risk factors of cancer and cardiovascular disease","volume":"9","author":"Si","year":"2020","journal-title":"Cancer Med"},{"key":"2026010607174397500_zwaf081-B10","doi-asserted-by":"crossref","first-page":"e70447","DOI":"10.1002\/cam4.70447","article-title":"Body roundness index trajectories and the risk of cancer: a cohort study","volume":"13","author":"Chen","year":"2024","journal-title":"Cancer Med"},{"key":"2026010607174397500_zwaf081-B11","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1007\/s13105-023-00991-z","article-title":"Fatty liver index (FLI): more than a marker of hepatic steatosis","volume":"80","author":"Kaneva","year":"2024","journal-title":"J Physiol Biochem"},{"key":"2026010607174397500_zwaf081-B12","doi-asserted-by":"crossref","first-page":"3221","DOI":"10.1007\/s00405-019-05595-2","article-title":"Pretreatment low prognostic nutritional index and low albumin-globulin ratio are predictive for overall survival in nasopharyngeal cancer","volume":"276","author":"Gundog","year":"2019","journal-title":"Eur Arch Otorhinolaryngol"},{"key":"2026010607174397500_zwaf081-B13","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1007\/s10741-024-10474-y","article-title":"Machine learning in predicting heart failure survival: a review of current models and future prospects","volume":"30","author":"Kokori","year":"2025","journal-title":"Heart Fail Rev"},{"key":"2026010607174397500_zwaf081-B14","article-title":"Advancements in heart disease prediction: a machine learning approach for early detection and risk assessment","author":"Ingole","year":"2024","journal-title":"arXiv preprint arXiv:2410.14738"},{"key":"2026010607174397500_zwaf081-B15","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.medcli.2024.01.040","article-title":"Classification tree obtained by artificial intelligence for the prediction of heart failure after acute coronary syndromes","volume":"163","author":"Cordero","year":"2024","journal-title":"Med Clin (Barc)"},{"key":"2026010607174397500_zwaf081-B16","author":"Alhamar G.","year":"2023"},{"key":"2026010607174397500_zwaf081-B17","doi-asserted-by":"crossref","first-page":"e35","DOI":"10.1161\/HYP.0000000000000087","article-title":"Measurement of blood pressure in humans: a scientific statement from the American Heart Association","volume":"73","author":"Muntner","year":"2019","journal-title":"Hypertension"},{"key":"2026010607174397500_zwaf081-B18","doi-asserted-by":"crossref","first-page":"5041","DOI":"10.1038\/s41467-022-32415-9","article-title":"Balancing national economic policy outcomes for sustainable development","volume":"13","author":"Basheer","year":"2022","journal-title":"Nat Commun"},{"key":"2026010607174397500_zwaf081-B19","doi-asserted-by":"crossref","first-page":"828454","DOI":"10.3389\/fpls.2022.828454","article-title":"Hyperspectral monitoring of powdery mildew disease severity in wheat based on machine learning","volume":"13","author":"Feng","year":"2022","journal-title":"Front Plant Sci"},{"key":"2026010607174397500_zwaf081-B20","doi-asserted-by":"crossref","first-page":"103092","DOI":"10.1016\/j.jisa.2021.103092","article-title":"AI@nti-Malware: an intelligent framework for defending against malware attacks","volume":"65","author":"Yi-Wei","year":"2022","journal-title":"Journal of Information Security and Applications"},{"key":"2026010607174397500_zwaf081-B21","doi-asserted-by":"crossref","first-page":"749472","DOI":"10.3389\/fphar.2022.749472","article-title":"Novel diagnostic and therapeutic options for KMT2A-rearranged acute leukemias","volume":"13","author":"Lopes","year":"2022","journal-title":"Front Pharmacol"},{"key":"2026010607174397500_zwaf081-B22","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1142\/S0218488523500228","article-title":"Classification of imbalanced data using SMOTE and AutoEncoder based deep convolutional neural network","volume":"31","author":"Suja","year":"2023","journal-title":"Int J Uncertain Fuzziness Knowl Based Syst"},{"key":"2026010607174397500_zwaf081-B23","doi-asserted-by":"crossref","first-page":"109982","DOI":"10.1016\/j.comnet.2023.109982","article-title":"Res-TranBiLSTM: an intelligent approach for intrusion detection in the Internet of Things","volume":"235","author":"Shiyu","year":"2023","journal-title":"Comput Netw"},{"key":"2026010607174397500_zwaf081-B24","doi-asserted-by":"crossref","first-page":"e022543","DOI":"10.1161\/JAHA.121.022543","article-title":"Association between atrial fibrillation and occupational exposure in firefighters based on self-reported survey data","volume":"11","author":"Vanchiere","year":"2022","journal-title":"J Am Heart Assoc"},{"key":"2026010607174397500_zwaf081-B25","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1161\/CIRCULATIONAHA.114.013116","article-title":"Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts","volume":"131","author":"W\u00fcrtz","year":"2015","journal-title":"Circulation"},{"key":"2026010607174397500_zwaf081-B26","doi-asserted-by":"crossref","first-page":"1035675","DOI":"10.3389\/fcvm.2022.1035675","article-title":"Prediction of 30-day mortality in heart failure patients with hypoxic hepatitis: development and external validation of an interpretable machine learning model","volume":"9","author":"Sun","year":"2022","journal-title":"Front Cardiovasc Med"},{"key":"2026010607174397500_zwaf081-B27","doi-asserted-by":"crossref","first-page":"3447","DOI":"10.3390\/cancers14143447","article-title":"Factors predicting surgical effort using explainable artificial intelligence in advanced stage epithelial ovarian cancer","volume":"14","author":"Laios","year":"2022","journal-title":"Cancers (Basel)"},{"key":"2026010607174397500_zwaf081-B28","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1186\/s12933-024-02198-y","article-title":"The association of atherogenic index of plasma with cardiovascular outcomes in patients with coronary artery disease: a systematic review and meta-analysis","volume":"23","author":"Rad","year":"2024","journal-title":"Cardiovasc Diabetol"},{"key":"2026010607174397500_zwaf081-B29","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1186\/s12944-022-01670-6","article-title":"Association between the atherogenic index of plasma and major adverse cardiovascular events among non-diabetic hypertensive older adults","volume":"21","author":"Hang","year":"2022","journal-title":"Lipids Health Dis"},{"key":"2026010607174397500_zwaf081-B30","first-page":"261","article-title":"Athrogenic indexes: useful markers for predicting metabolic syndrome in axial spondyloarthritis","volume":"34","author":"Slouma","year":"2022","journal-title":"Clin Investig Arterioscler"},{"key":"2026010607174397500_zwaf081-B31","doi-asserted-by":"crossref","first-page":"955241","DOI":"10.3389\/fendo.2022.955241","article-title":"The association between a body shape index and elevated urinary albumin-creatinine ratio in Chinese community adults","volume":"13","author":"Zhang","year":"2022","journal-title":"Front Endocrinol (Lausanne)"},{"key":"2026010607174397500_zwaf081-B32","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1186\/s12889-023-15208-7","article-title":"Relationship between novel anthropometric indices and the incidence of hypertension in Chinese individuals: a prospective cohort study based on the CHNS from 1993 to 2015","volume":"23","author":"Zhang","year":"2023","journal-title":"BMC Public Health"},{"key":"2026010607174397500_zwaf081-B33","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1186\/s12872-020-01444-x","article-title":"Higher fatty liver index is associated with increased risk of new onset heart failure in healthy adults: a nationwide population-based study in Korea","volume":"20","author":"Roh","year":"2020","journal-title":"BMC Cardiovasc Disord"},{"key":"2026010607174397500_zwaf081-B34","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.2174\/0118715303274348231130052050","article-title":"Association between body fat percentage and cardiometabolic diseases in general population","volume":"24","author":"Jiayi","year":"2024","journal-title":"Endocr Metab Immune Disord Drug Targets"},{"key":"2026010607174397500_zwaf081-B35","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1186\/s12933-021-01374-8","article-title":"The association of hepatic steatosis and fibrosis with heart failure and mortality","volume":"20","author":"Park","year":"2021","journal-title":"Cardiovasc Diabetol"},{"key":"2026010607174397500_zwaf081-B36","doi-asserted-by":"crossref","first-page":"2503","DOI":"10.2147\/DMSO.S420924","article-title":"Prognostic nutritional index (PNI) as a predictor in patients with metabolic syndrome and heart failure","volume":"16","author":"Zhang","year":"2023","journal-title":"Diabetes Metab Syndr Obes"},{"key":"2026010607174397500_zwaf081-B37","doi-asserted-by":"crossref","first-page":"2479","DOI":"10.1002\/ehf2.12812","article-title":"Prognostic nutritional index in elderly patients hospitalized for acute heart failure","volume":"7","author":"Candeloro","year":"2020","journal-title":"ESC Heart Fail"},{"key":"2026010607174397500_zwaf081-B38","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/s00380-021-01888-x","article-title":"Changes in prognostic nutritional index during hospitalization and outcomes in patients with acute heart failure","volume":"37","author":"Kawata","year":"2022","journal-title":"Heart Vessels"},{"key":"2026010607174397500_zwaf081-B39","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.1093\/jamia\/ocac093","article-title":"The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression","volume":"29","author":"van den Goorbergh","year":"2022","journal-title":"J Am Med Inform Assoc"}],"container-title":["European Journal of Preventive Cardiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/eurjpc\/advance-article-pdf\/doi\/10.1093\/eurjpc\/zwaf081\/62195129\/zwaf081.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/eurjpc\/article-pdf\/33\/1\/53\/62195129\/zwaf081.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/eurjpc\/article-pdf\/33\/1\/53\/62195129\/zwaf081.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T12:17:53Z","timestamp":1767701873000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/eurjpc\/article\/33\/1\/53\/8044984"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,27]]},"references-count":39,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,2,27]]},"published-print":{"date-parts":[[2026,1,6]]}},"URL":"https:\/\/doi.org\/10.1093\/eurjpc\/zwaf081","relation":{},"ISSN":["2047-4873","2047-4881"],"issn-type":[{"value":"2047-4873","type":"print"},{"value":"2047-4881","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,1]]},"published":{"date-parts":[[2025,2,27]]}}}