{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T12:12:42Z","timestamp":1769775162319,"version":"3.49.0"},"reference-count":27,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2025,4,18]],"date-time":"2025-04-18T00:00:00Z","timestamp":1744934400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,4,18]],"date-time":"2025-04-18T00:00:00Z","timestamp":1744934400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100010353","name":"Hellenic Atherosclerosis Society","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010353","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Eur J Clin Investigation"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Malignant hypertension (MHT) is a rare, yet severe condition with high morbidity and mortality. We aimed to assess the potential of machine learning (ML) algorithms in forecasting prognostic outcomes in MHT patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data from the West Birmingham MHT Registry were used. We evaluated the efficacy of 9 ML algorithms, CatBoost, Decision Tree (DT), Light\u2010Gradient Boosting Machine (LightGBM), K\u2010Nearest Neighbours (KNN), Logistic Regression (LR), Multi\u2010Layer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM) and XGBoost in predicting a composite outcome of all\u2010cause mortality\/dialysis. Evaluation metrics included the area under the receiver operating characteristic curve (AUC) and F1 score. SHapley Additive exPlanations values were employed to quantify the importance of each feature.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The cohort comprised 385 individuals with MHT (mean age 48\u2009\u00b1\u200913\u2009years, 66% male). During a median follow\u2010up of 11 (interquartile range: 3\u201318) years, 282 patients (73%) experienced the composite outcome. Among 24 demographic and clinical variables, 16 were selected into the ML models. The SVM, LR, and MLP models exhibited robust predictive performance, achieving AUCs of .81 (95% CI: .70\u2013.90), .82 (95% CI: .71\u2013.92) and .81 (95% CI: .71\u2013.90), respectively. Furthermore, these models demonstrated high F1 scores (SVM: .75, LR: .80. MLP: .75). Age, smoking, follow\u2010up systolic blood pressure, and baseline creatinine were commonly identified as primary prognostic features in both SVM and LR models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The application of ML algorithms facilitates effective prediction of prognostic outcomes in MHT patients, illustrating their potential utility in clinical decision\u2010making through more targeted risk stratification and individualised patient care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/eci.70052","type":"journal-article","created":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T09:07:13Z","timestamp":1748336833000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction of major outcomes in patients with malignant hypertension using machine learning: A report from the West Birmingham malignant hypertension registry"],"prefix":"10.1111","volume":"55","author":[{"given":"Antonios A.","family":"Argyris","sequence":"first","affiliation":[{"name":"Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital  Liverpool UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hironori","family":"Ishiguchi","sequence":"additional","affiliation":[{"name":"Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital  Liverpool UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2808-6286","authenticated-orcid":false,"given":"Yang","family":"Chen","sequence":"additional","affiliation":[{"name":"Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital  Liverpool UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yalin","family":"Zheng","sequence":"additional","affiliation":[{"name":"Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital  Liverpool UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alena","family":"Shantsila","sequence":"additional","affiliation":[{"name":"Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital  Liverpool UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eduard","family":"Shantsila","sequence":"additional","affiliation":[{"name":"Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital  Liverpool UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D. Gareth","family":"Beevers","sequence":"additional","affiliation":[{"name":"University Department of Medicine City Hospital  Birmingham UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gregory Y. H.","family":"Lip","sequence":"additional","affiliation":[{"name":"Liverpool Centre for Cardiovascular Science University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital  Liverpool UK"},{"name":"Danish Center for Health Services Research, Department of Clinical Medicine Aalborg University  Aalborg Denmark"},{"name":"Medical University of Bialystok  Bialystok Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,4,18]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.121.023397"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1097\/00004872-199411000-00013"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1097\/00004872-199508000-00013"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.hjh.0000249710.21146.38"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/ajh.2009.153"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/jch.12243"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1097\/HJH.0000000000001446"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1093\/ajh\/hpx008"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1097\/HJH.0000000000001913"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41371-019-0267-y"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1097\/HJH.0b013e3283526e47"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1038\/jhh.2015.112"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1097\/HJH.0000000000001974"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12933-022-01672-9"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1055\/a-1467-2993"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ahj.2023.08.006"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpcardiol.2023.101694"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0174944"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-88257-w"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.119.013924"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1093\/ehjqcco\/qcab037"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1055\/a-1754-7551"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1055\/a-1525-7220"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1055\/s-0042-1757403"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1055\/a-1632-1777"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1055\/a-1591-8033"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.1055\/a-1508-7980"}],"container-title":["European Journal of Clinical Investigation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/eci.70052","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/eci.70052","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/eci.70052","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T21:07:06Z","timestamp":1769720826000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/eci.70052"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,18]]},"references-count":27,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["10.1111\/eci.70052"],"URL":"https:\/\/doi.org\/10.1111\/eci.70052","archive":["Portico"],"relation":{},"ISSN":["0014-2972","1365-2362"],"issn-type":[{"value":"0014-2972","type":"print"},{"value":"1365-2362","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,18]]},"assertion":[{"value":"2025-01-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-04-09","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-04-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70052"}}