{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T15:01:12Z","timestamp":1784127672252,"version":"3.55.0"},"reference-count":34,"publisher":"American Diabetes Association","issue":"3","license":[{"start":{"date-parts":[[2018,2,20]],"date-time":"2018-02-20T00:00:00Z","timestamp":1519084800000},"content-version":"vor","delay-in-days":56,"URL":"http:\/\/www.diabetesjournals.org\/content\/license"}],"funder":[{"DOI":"10.13039\/100006545","name":"National Institute on Minority Health and Health Disparities","doi-asserted-by":"publisher","award":["DP2-MD-010478"],"award-info":[{"award-number":["DP2-MD-010478"]}],"id":[{"id":"10.13039\/100006545","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006545","name":"National Institute on Minority Health and Health Disparities","doi-asserted-by":"publisher","award":["U54-MD-010724"],"award-info":[{"award-number":["U54-MD-010724"]}],"id":[{"id":"10.13039\/100006545","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000968","name":"American Heart Association","doi-asserted-by":"publisher","award":["17MCPRP33670728"],"award-info":[{"award-number":["17MCPRP33670728"]}],"id":[{"id":"10.13039\/100000968","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000062","name":"National Institute for Diabetes and Digestive and Kidney Disease","doi-asserted-by":"publisher","award":["U01-DK-098246"],"award-info":[{"award-number":["U01-DK-098246"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000062","name":"National Institute for Diabetes and Digestive and Kidney Disease","doi-asserted-by":"publisher","award":["R18-DK-10273"],"award-info":[{"award-number":["R18-DK-10273"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000062","name":"National Institute for Diabetes and Digestive and Kidney Disease","doi-asserted-by":"publisher","award":["K23-DK-109200"],"award-info":[{"award-number":["K23-DK-109200"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["diabetesjournals.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,3,1]]},"abstract":"<jats:sec>\n                    <jats:title>OBJECTIVE<\/jats:title>\n                    <jats:p>Identifying patients who may experience decreased or increased mortality risk from intensive glycemic therapy for type 2 diabetes remains an important clinical challenge. We sought to identify characteristics of patients at high cardiovascular risk with decreased or increased mortality risk from glycemic therapy for type 2 diabetes using new methods to identify complex combinations of treatment effect modifiers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESEARCH DESIGN AND METHODS<\/jats:title>\n                    <jats:p>The machine learning method of gradient forest analysis was applied to understand the variation in all-cause mortality within the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 10,251), whose participants were 40\u201379 years old with type 2 diabetes, hemoglobin A1c (HbA1c) \u22657.5% (58 mmol\/mol), cardiovascular disease (CVD) or multiple CVD risk factors, and randomized to target HbA1c &amp;lt;6.0% (42 mmol\/mol; intensive) or 7.0\u20137.9% (53\u201363 mmol\/mol; standard). Covariates included demographics, BMI, hemoglobin glycosylation index (HGI; observed minus expected HbA1c derived from prerandomization fasting plasma glucose), other biomarkers, history, and medications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>The analysis identified four groups defined by age, BMI, and HGI with varied risk for mortality under intensive glycemic therapy. The lowest risk group (HGI &amp;lt;0.44, BMI &amp;lt;30 kg\/m2, age &amp;lt;61 years) had an absolute mortality risk decrease of 2.3% attributable to intensive therapy (95% CI 0.2 to 4.5, P = 0.038; number needed to treat: 43), whereas the highest risk group (HGI \u22650.44) had an absolute mortality risk increase of 3.7% attributable to intensive therapy (95% CI 1.5 to 6.0; P &amp;lt; 0.001; number needed to harm: 27).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>Age, BMI, and HGI may help individualize prediction of the benefit and harm from intensive glycemic therapy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2337\/dc17-2252","type":"journal-article","created":{"date-parts":[[2017,12,26]],"date-time":"2017-12-26T20:10:33Z","timestamp":1514319033000},"page":"604-612","update-policy":"https:\/\/doi.org\/10.2337\/ada-journal-policies","source":"Crossref","is-referenced-by-count":63,"title":["Characteristics Associated With Decreased or Increased Mortality Risk From Glycemic Therapy Among Patients With Type 2 Diabetes and High Cardiovascular Risk: Machine Learning Analysis of the ACCORD Trial"],"prefix":"10.2337","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0599-6332","authenticated-orcid":false,"given":"Sanjay","family":"Basu","sequence":"first","affiliation":[{"name":"1Center for Primary Care and Outcomes Research, Center for Population Health Sciences, Departments of Medicine and Health Research and Policy, Stanford University, Palo Alto, CA"},{"name":"2Harvard Medical School, Boston, MA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0643-4873","authenticated-orcid":false,"given":"Sridharan","family":"Raghavan","sequence":"additional","affiliation":[{"name":"3Department of Veterans Affairs Eastern Colorado Healthcare System, Denver, CO"},{"name":"4Division of General Internal Medicine, Department of Medicine, University of Colorado School of Medicine, Denver, CO"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deborah J.","family":"Wexler","sequence":"additional","affiliation":[{"name":"2Harvard Medical School, Boston, MA"},{"name":"5Diabetes Unit, Massachusetts General Hospital, Boston, MA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seth A.","family":"Berkowitz","sequence":"additional","affiliation":[{"name":"2Harvard Medical School, Boston, MA"},{"name":"5Diabetes Unit, Massachusetts General Hospital, Boston, MA"},{"name":"6Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1167","published-online":{"date-parts":[[2017,12,26]]},"reference":[{"key":"2026041420352760800_B1","doi-asserted-by":"crossref","first-page":"S48","DOI":"10.2337\/dc17-S009","article-title":"Glycemic targets. 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