{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T01:47:24Z","timestamp":1791942444151,"version":"4.3.4"},"reference-count":47,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T00:00:00Z","timestamp":1735171200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T00:00:00Z","timestamp":1735171200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["dom-pubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Obesity Metabolism"],"published-print":{"date-parts":[[2025,3]]},"abstract":"Abstract<\/jats:title>\n \n Aim<\/jats:title>\n We aimed to identify the characteristics of patients with diabetes who can derive cognitive benefits from intensive blood pressure (BP) treatment using machine learning methods.<\/jats:p>\n <\/jats:sec>\n \n Materials and Methods<\/jats:title>\n Using data from the Action to Control Cardiovascular Risk in Diabetes Memory in Diabetes (ACCORD\u2010MIND) study, 1349 patients with type 2 diabetes who underwent BP treatment (intensive treatment targeting a systolic BP <120\u2009mmHg vs. standard treatment targeting <140\u2009mmHg) were included in the machine learning analysis. Seventy\u2010nine variables correlated with diabetes and cognitive function were used to build the causal forest and causal tree models for identifying heterogeneous BP treatment effects on cognitive decline.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Our analyses identified four variables including urinary albumin\u2010to\u2010creatinine ratio (UACR, mg\/g), Framingham 10\u2010year cardiovascular risk score (FRS, %), triglycerides (TG, mmol\/L) and diabetes duration, that categorized the participants into five subgroups with different risk benefits for cognitive decline from BP treatments. Subgroup 1 (UACR \u226565\u2009mg\/g) had an absolute risk reduction (ARR) of 15.36% (95% CI, 5.01%\u201325.46%) from intensive versus standard BP treatment (hazard ratio [HR], 0.36; 95% CI, 0.18\u20130.73). Subgroup 2 (UACR <65\u2009mg\/g, FRS \u226526%, TG <2.3\u2009mmol\/L and diabetes duration \u22659\u2009years) had an ARR of 14.74% (95% CI, 4.56%\u201324.59%) from intensive versus standard BP treatment (HR, 0.34; 95% CI, 0.15\u20130.77). No significant benefits were found for other subgroups.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Patients with type 2 diabetes with high UACR, or with low UACR and low TG, but high predicted cardiovascular risk and long diabetes duration were likely to derive cognitive benefits from intensive BP treatment.<\/jats:p>\n <\/jats:sec>","DOI":"10.1111\/dom.16145","type":"journal-article","created":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T04:29:01Z","timestamp":1735187341000},"page":"1432-1443","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Heterogeneous blood pressure treatment effects on cognitive decline in type 2 diabetes: A machine learning analysis of a randomized clinical trial"],"prefix":"10.1111","volume":"27","author":[{"given":"Xuan","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital Shanghai Jiaotong University School of Medicine Shanghai China"},{"name":"National Clinical Research Center for Metabolic Diseases (Shanghai), Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, National Research Center for Translational Medicine, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital Shanghai Jiaotong University School of Medicine Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoli","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital Shanghai Jiaotong University School of Medicine Shanghai China"},{"name":"National Clinical Research Center for Metabolic Diseases (Shanghai), Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR 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