Ayham Alkhachroum, Lili Zhou, Negar Asdaghi, Hannah Gardener, Hao Ying, Carolina M Gutierrez, Brian M Manolovitz, Daniel Samano, Danielle Bass, Dianne Foster, Nicole B Sur, David Z Rose, Angus Jameson, Nina Massad, Mohan Kottapally, Amedeo Merenda, Robert M Starke, Kristine O'Phelan, Jose G Romano, Jan Claassen, Ralph L Sacco, Tatjana Rundek
{"title":"佛罗里达州中风登记处急性中风后撤除维持生命疗法的预测因素和时间趋势。","authors":"Ayham Alkhachroum, Lili Zhou, Negar Asdaghi, Hannah Gardener, Hao Ying, Carolina M Gutierrez, Brian M Manolovitz, Daniel Samano, Danielle Bass, Dianne Foster, Nicole B Sur, David Z Rose, Angus Jameson, Nina Massad, Mohan Kottapally, Amedeo Merenda, Robert M Starke, Kristine O'Phelan, Jose G Romano, Jan Claassen, Ralph L Sacco, Tatjana Rundek","doi":"10.1097/CCE.0000000000000934","DOIUrl":null,"url":null,"abstract":"<p><p>Temporal trends and factors associated with the withdrawal of life-sustaining therapy (WLST) after acute stroke are not well determined.</p><p><strong>Design: </strong>Observational study (2008-2021).</p><p><strong>Setting: </strong>Florida Stroke Registry (152 hospitals).</p><p><strong>Patients: </strong>Acute ischemic stroke (AIS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) patients.</p><p><strong>Interventions: </strong>None.</p><p><strong>Measurements and main results: </strong>Importance plots were performed to generate the most predictive factors of WLST. Area under the curve (AUC) for the receiver operating curve were generated for the performance of logistic regression (LR) and random forest (RF) models. Regression analysis was applied to evaluate temporal trends. Among 309,393 AIS patients, 47,485 ICH patients, and 16,694 SAH patients; 9%, 28%, and 19% subsequently had WLST. Patients who had WLST were older (77 vs 70 yr), more women (57% vs 49%), White (76% vs 67%), with greater stroke severity on the National Institutes of Health Stroke Scale greater than or equal to 5 (29% vs 19%), more likely hospitalized in comprehensive stroke centers (52% vs 44%), had Medicare insurance (53% vs 44%), and more likely to have impaired level of consciousness (38% vs 12%). Most predictors associated with the decision to WLST in AIS were age, stroke severity, region, insurance status, center type, race, and level of consciousness (RF AUC of 0.93 and LR AUC of 0.85). Predictors in ICH included age, impaired level of consciousness, region, race, insurance status, center type, and prestroke ambulation status (RF AUC of 0.76 and LR AUC of 0.71). Factors in SAH included age, impaired level of consciousness, region, insurance status, race, and stroke center type (RF AUC of 0.82 and LR AUC of 0.72). Despite a decrease in the rates of early WLST (< 2 d) and mortality, the overall rates of WLST remained stable.</p><p><strong>Conclusions: </strong>In acute hospitalized stroke patients in Florida, factors other than brain injury alone contribute to the decision to WLST. Potential predictors not measured in this study include education, culture, faith and beliefs, and patient/family and physician preferences. The overall rates of WLST have not changed in the last 2 decades.</p>","PeriodicalId":10759,"journal":{"name":"Critical Care Explorations","volume":"5 7","pages":"e0934"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d1/ea/cc9-5-e0934.PMC10292735.pdf","citationCount":"0","resultStr":"{\"title\":\"Predictors and Temporal Trends of Withdrawal of Life-Sustaining Therapy After Acute Stroke in the Florida Stroke Registry.\",\"authors\":\"Ayham Alkhachroum, Lili Zhou, Negar Asdaghi, Hannah Gardener, Hao Ying, Carolina M Gutierrez, Brian M Manolovitz, Daniel Samano, Danielle Bass, Dianne Foster, Nicole B Sur, David Z Rose, Angus Jameson, Nina Massad, Mohan Kottapally, Amedeo Merenda, Robert M Starke, Kristine O'Phelan, Jose G Romano, Jan Claassen, Ralph L Sacco, Tatjana Rundek\",\"doi\":\"10.1097/CCE.0000000000000934\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Temporal trends and factors associated with the withdrawal of life-sustaining therapy (WLST) after acute stroke are not well determined.</p><p><strong>Design: </strong>Observational study (2008-2021).</p><p><strong>Setting: </strong>Florida Stroke Registry (152 hospitals).</p><p><strong>Patients: </strong>Acute ischemic stroke (AIS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) patients.</p><p><strong>Interventions: </strong>None.</p><p><strong>Measurements and main results: </strong>Importance plots were performed to generate the most predictive factors of WLST. Area under the curve (AUC) for the receiver operating curve were generated for the performance of logistic regression (LR) and random forest (RF) models. Regression analysis was applied to evaluate temporal trends. Among 309,393 AIS patients, 47,485 ICH patients, and 16,694 SAH patients; 9%, 28%, and 19% subsequently had WLST. Patients who had WLST were older (77 vs 70 yr), more women (57% vs 49%), White (76% vs 67%), with greater stroke severity on the National Institutes of Health Stroke Scale greater than or equal to 5 (29% vs 19%), more likely hospitalized in comprehensive stroke centers (52% vs 44%), had Medicare insurance (53% vs 44%), and more likely to have impaired level of consciousness (38% vs 12%). Most predictors associated with the decision to WLST in AIS were age, stroke severity, region, insurance status, center type, race, and level of consciousness (RF AUC of 0.93 and LR AUC of 0.85). Predictors in ICH included age, impaired level of consciousness, region, race, insurance status, center type, and prestroke ambulation status (RF AUC of 0.76 and LR AUC of 0.71). Factors in SAH included age, impaired level of consciousness, region, insurance status, race, and stroke center type (RF AUC of 0.82 and LR AUC of 0.72). Despite a decrease in the rates of early WLST (< 2 d) and mortality, the overall rates of WLST remained stable.</p><p><strong>Conclusions: </strong>In acute hospitalized stroke patients in Florida, factors other than brain injury alone contribute to the decision to WLST. Potential predictors not measured in this study include education, culture, faith and beliefs, and patient/family and physician preferences. The overall rates of WLST have not changed in the last 2 decades.</p>\",\"PeriodicalId\":10759,\"journal\":{\"name\":\"Critical Care Explorations\",\"volume\":\"5 7\",\"pages\":\"e0934\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d1/ea/cc9-5-e0934.PMC10292735.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Critical Care Explorations\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1097/CCE.0000000000000934\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/7/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Critical Care Explorations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/CCE.0000000000000934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/7/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
急性中风后撤消维持生命疗法（WLST）的时间趋势和相关因素尚未明确：观察性研究（2008-2021 年）：佛罗里达州卒中登记处（152 家医院）：急性缺血性卒中（AIS）、脑出血（ICH）和蛛网膜下腔出血（SAH）患者：测量和主要结果测量和主要结果：绘制了重要性图，以得出最能预测 WLST 的因素。为逻辑回归（LR）和随机森林（RF）模型的性能生成了接收者操作曲线下面积（AUC）。回归分析用于评估时间趋势。在 309,393 例 AIS 患者、47,485 例 ICH 患者和 16,694 例 SAH 患者中，分别有 9%、28% 和 19% 随后出现了 WLST。接受 WLST 的患者年龄更大（77 岁 vs 70 岁）、女性更多（57% vs 49%）、白人更多（76% vs 67%）、根据美国国立卫生研究院卒中量表大于或等于 5 级的卒中严重程度更高（29% vs 19%）、更有可能在综合卒中中心住院（52% vs 44%）、有医疗保险（53% vs 44%）、更有可能意识受损（38% vs 12%）。在 AIS 中，与决定 WLST 最相关的预测因素是年龄、卒中严重程度、地区、保险状况、中心类型、种族和意识水平（RF AUC 为 0.93，LR AUC 为 0.85）。ICH 的预测因素包括年龄、意识受损程度、地区、种族、保险状况、中心类型和卒中前行走状况（RF AUC 为 0.76，LR AUC 为 0.71）。导致 SAH 的因素包括年龄、意识受损程度、地区、保险状况、种族和卒中中心类型（RF AUC 为 0.82，LR AUC 为 0.72）。尽管早期 WLST（< 2 d）率和死亡率有所下降，但总体 WLST 率保持稳定：结论：在佛罗里达州的急性住院脑卒中患者中，除脑损伤外，其他因素也是决定是否进行 WLST 的因素。本研究未测量的潜在预测因素包括教育、文化、信仰和信念以及患者/家属和医生的偏好。在过去 20 年中，WLST 的总体使用率没有变化。
Measurements and main results: Importance plots were performed to generate the most predictive factors of WLST. Area under the curve (AUC) for the receiver operating curve were generated for the performance of logistic regression (LR) and random forest (RF) models. Regression analysis was applied to evaluate temporal trends. Among 309,393 AIS patients, 47,485 ICH patients, and 16,694 SAH patients; 9%, 28%, and 19% subsequently had WLST. Patients who had WLST were older (77 vs 70 yr), more women (57% vs 49%), White (76% vs 67%), with greater stroke severity on the National Institutes of Health Stroke Scale greater than or equal to 5 (29% vs 19%), more likely hospitalized in comprehensive stroke centers (52% vs 44%), had Medicare insurance (53% vs 44%), and more likely to have impaired level of consciousness (38% vs 12%). Most predictors associated with the decision to WLST in AIS were age, stroke severity, region, insurance status, center type, race, and level of consciousness (RF AUC of 0.93 and LR AUC of 0.85). Predictors in ICH included age, impaired level of consciousness, region, race, insurance status, center type, and prestroke ambulation status (RF AUC of 0.76 and LR AUC of 0.71). Factors in SAH included age, impaired level of consciousness, region, insurance status, race, and stroke center type (RF AUC of 0.82 and LR AUC of 0.72). Despite a decrease in the rates of early WLST (< 2 d) and mortality, the overall rates of WLST remained stable.
Conclusions: In acute hospitalized stroke patients in Florida, factors other than brain injury alone contribute to the decision to WLST. Potential predictors not measured in this study include education, culture, faith and beliefs, and patient/family and physician preferences. The overall rates of WLST have not changed in the last 2 decades.
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