{"id":16416,"date":"2023-06-22T16:10:00","date_gmt":"2023-06-22T20:10:00","guid":{"rendered":"https:\/\/www.ices.on.ca\/?post_type=journal_article&#038;p=16416"},"modified":"2023-07-24T16:13:44","modified_gmt":"2023-07-24T20:13:44","slug":"development-and-validation-of-a-predictive-risk-algorithm-for-bleeding-in-individuals-on-long-term-hemodialysis","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/development-and-validation-of-a-predictive-risk-algorithm-for-bleeding-in-individuals-on-long-term-hemodialysis\/","title":{"rendered":"Development and validation of a predictive risk algorithm for bleeding in individuals on long-term hemodialysis: an international prospective cohort study (BLEED-HD)"},"content":{"rendered":"<p><strong>Background<\/strong> \u2014 Individuals with kidney disease are at a high risk of bleeding and as such tools that identify those at highest risk may aid mitigation strategies.<\/p>\n<p><strong>Objective<\/strong> \u2014 We set out to develop and validate a prediction equation (BLEED-HD) to identify patients on maintenance hemodialysis at high risk of bleeding.<\/p>\n<p><strong>Design<\/strong> \u2014 International prospective cohort study (development); retrospective cohort study (validation).<\/p>\n<p><strong>Settings<\/strong> \u2014 Development: 15 countries (Dialysis Outcomes and Practice Patterns Study [DOPPS] phase 2-6 from 2002 to 2018); Validation: Ontario, Canada.<\/p>\n<p><strong>Patients<\/strong> \u2014 Development: 53\u2009147 patients; Validation: 19\u2009318 patients.<\/p>\n<p><strong>Measurements <\/strong>\u2014 Hospitalization for a bleeding event.<\/p>\n<p><strong>Methods<\/strong> \u2014 Cox proportional hazards models.<\/p>\n<p><strong>Results<\/strong> \u2014 Among the DOPPS cohort (mean age, 63.7 years; female, 39.7%), a bleeding event occurred in 2773 patients (5.2%, event rate 32 per 1000 person-years), with a median follow-up of 1.6 (interquartile range [IQR], 0.9-2.1) years. BLEED-HD included 6 variables: age, sex, country, previous gastrointestinal bleeding, prosthetic heart valve, and vitamin K antagonist use. The observed 3-year probability of bleeding by deciles of risk ranged from 2.2% to 10.8%. Model discrimination was low to moderate (c-statistic = 0.65) with excellent calibration (Brier score range = 0.036-0.095). Discrimination and calibration of BLEED-HD were similar in an external validation of 19\u2009318 patients from Ontario, Canada. Compared to existing bleeding scores, BLEED-HD demonstrated better discrimination and calibration (c-statistic: HEMORRHAGE = 0.59, HAS-BLED = 0.59, and ATRIA = 0.57, c-stat difference, net reclassification index [NRI], and integrated discrimination index [IDI] all <em>P<\/em> value &lt;.0001).<\/p>\n<p><strong>Limitations<\/strong> \u2014 Dialysis procedure anticoagulation was not available; validation cohort was considerably older than the development cohort.<\/p>\n<p><strong>Conclusion<\/strong> \u2014 In patients on maintenance hemodialysis, BLEED-HD is a simple risk equation that may be more applicable than existing risk tools in predicting the risk of bleeding in this high-risk population.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Background \u2014 Individuals with kidney disease are at a high risk of bleeding and as such tools that identify those at highest risk may aid mitigation strategies. Objective \u2014 We set out to develop and validate a prediction equation (BLEED-HD) to identify patients on maintenance hemodialysis at high risk of bleeding. Design \u2014 International prospective [&hellip;]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[49,66],"migration-helper-qa-sample-set":[],"class_list":["post-16416","journal_article","type-journal_article","status-publish","hentry","topic-kidney-disease","topic-trials"],"acf":{"citation":"Madken M, Mallick R, Rhodes E, Mahdavi R, Bader Eddeen A, Hundemer GL, Kelly DM, Karaboyas A, Robinson B, Bieber B, Molnar AO, Badve SV, Tanuseputro P, Knoll G, Sood MM. <em>Can J Kidney Health Dis<\/em>. 2023; 10:20543581231169610. Epub 2023 Jun 22.","source_url":"https:\/\/doi.org\/10.1177\/20543581231169610","ices_scientist":[1316,1107,1144],"site":[6734],"research_program":[6743],"news_release":"","journal_article":"","atlas":"","research_report":"","infographic":"","video":"","downloads":null,"links":null,"sitecore_item_id":"","sitecore_item_name":"","sitecore_field_values":"","previous_url":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ICES | Development and validation of a predictive risk algorithm for bleeding in individuals on long-term hemodialysis: an international prospective cohort study (BLEED-HD)<\/title>\n<meta name=\"description\" content=\"Background \u2014 Individuals with kidney disease are at a high risk of bleeding and as such tools that identify those at highest risk may aid mitigation\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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