The HEP Score: A Nomogram-Derived Hematoma Expansion Prediction Scale
Background Identification of intracerebral hemorrhage (ICH) patients at risk of substantial hematoma expansion (SHE) could facilitate the selection of candidates likely to benefit from therapies aiming to minimize ICH growth. We aimed to develop a grading tool that can be quickly used during the hyp...
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description | Background
Identification of intracerebral hemorrhage (ICH) patients at risk of substantial hematoma expansion (SHE) could facilitate the selection of candidates likely to benefit from therapies aiming to minimize ICH growth. We aimed to develop a grading tool that can be quickly used during the hyperacute phase to predict the risk of SHE.
Methods
We reviewed data from 237 spontaneous ICH patients who had baseline head CT scan within 12 h of symptom onset and follow-up CT during the following 72 h. We performed logistic regression analyses to determine the predictors of SHE (defined as an absolute increase in ICH volume >6 ml or an increase >33 % on follow-up CT). We identified 6 predictors; each was assigned a point in the graphic interface of a nomogram which was used to construct a scoring system—The Hematoma Expansion Prediction (HEP) Score, varying from 0 to 18 points. We evaluated the ability of the model to predict the probability of SHE using c-statistics.
Results
SHE occurred in 74 patients (31.2 %). The final model to predict SHE included 6 variables: time from onset to baseline CT (3 were at greatest risk for SHE.
Conclusions
We developed and internally validated a novel nomogram and an easy to use score which accurately predict the probability of SHE based on six easily obtainable parameters. This could be useful for treatment decision and stratification. External prospective validation of the HEP score is warranted before its application to other populations. |
doi_str_mv | 10.1007/s12028-015-0147-4 |
format | Article |
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Identification of intracerebral hemorrhage (ICH) patients at risk of substantial hematoma expansion (SHE) could facilitate the selection of candidates likely to benefit from therapies aiming to minimize ICH growth. We aimed to develop a grading tool that can be quickly used during the hyperacute phase to predict the risk of SHE.
Methods
We reviewed data from 237 spontaneous ICH patients who had baseline head CT scan within 12 h of symptom onset and follow-up CT during the following 72 h. We performed logistic regression analyses to determine the predictors of SHE (defined as an absolute increase in ICH volume >6 ml or an increase >33 % on follow-up CT). We identified 6 predictors; each was assigned a point in the graphic interface of a nomogram which was used to construct a scoring system—The Hematoma Expansion Prediction (HEP) Score, varying from 0 to 18 points. We evaluated the ability of the model to predict the probability of SHE using c-statistics.
Results
SHE occurred in 74 patients (31.2 %). The final model to predict SHE included 6 variables: time from onset to baseline CT (<3 vs. 3–12 h), history of dementia, current smoking, antiplatelet use, Glasgow Comma Scale score, and the presence of subarachnoid hemorrhage on baseline scan. The model had satisfactory discrimination ability with a bootstrap corrected c-index of 0.76 (95 % CI 0.69–0.83) and good calibration. Patients with a total HEP score >3 were at greatest risk for SHE.
Conclusions
We developed and internally validated a novel nomogram and an easy to use score which accurately predict the probability of SHE based on six easily obtainable parameters. This could be useful for treatment decision and stratification. External prospective validation of the HEP score is warranted before its application to other populations.</description><identifier>ISSN: 1541-6933</identifier><identifier>EISSN: 1556-0961</identifier><identifier>DOI: 10.1007/s12028-015-0147-4</identifier><identifier>PMID: 25963292</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Aged ; Aged, 80 and over ; Anticoagulants ; Blood pressure ; Calibration ; Cardiac arrhythmia ; Cardiovascular disease ; Cerebral Hemorrhage - complications ; Cerebral Hemorrhage - diagnostic imaging ; Coronary vessels ; Creatinine ; Critical Care Medicine ; Dementia ; Diabetes ; Female ; Hematoma ; Hematoma - diagnosis ; Hematoma - diagnostic imaging ; Hematoma - etiology ; Hemorrhage ; Humans ; Hyperlipidemia ; Hypertension ; Intensive ; Internal Medicine ; Ischemia ; Male ; Medical imaging ; Medicine ; Medicine & Public Health ; Models, Statistical ; Neurology ; Nomograms ; Original Article ; Probability ; Radiography ; Risk Factors ; Stroke ; Transient ischemic attack ; Vein & artery diseases</subject><ispartof>Neurocritical care, 2015-10, Vol.23 (2), p.179-187</ispartof><rights>Springer Science+Business Media New York 2015</rights><rights>Springer Science+Business Media New York 2015.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c508t-7802817055ab461e86ae1a06c3063fcdf4373383fe714caf1f3188e4433697ef3</citedby><cites>FETCH-LOGICAL-c508t-7802817055ab461e86ae1a06c3063fcdf4373383fe714caf1f3188e4433697ef3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12028-015-0147-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2920657260?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21387,21388,27923,27924,33529,33530,33743,33744,41487,42556,43658,43804,51318,64384,64386,64388,72340</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25963292$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yao, Xiaoying</creatorcontrib><creatorcontrib>Xu, Ye</creatorcontrib><creatorcontrib>Siwila-Sackman, Erica</creatorcontrib><creatorcontrib>Wu, Bo</creatorcontrib><creatorcontrib>Selim, Magdy</creatorcontrib><title>The HEP Score: A Nomogram-Derived Hematoma Expansion Prediction Scale</title><title>Neurocritical care</title><addtitle>Neurocrit Care</addtitle><addtitle>Neurocrit Care</addtitle><description>Background
Identification of intracerebral hemorrhage (ICH) patients at risk of substantial hematoma expansion (SHE) could facilitate the selection of candidates likely to benefit from therapies aiming to minimize ICH growth. We aimed to develop a grading tool that can be quickly used during the hyperacute phase to predict the risk of SHE.
Methods
We reviewed data from 237 spontaneous ICH patients who had baseline head CT scan within 12 h of symptom onset and follow-up CT during the following 72 h. We performed logistic regression analyses to determine the predictors of SHE (defined as an absolute increase in ICH volume >6 ml or an increase >33 % on follow-up CT). We identified 6 predictors; each was assigned a point in the graphic interface of a nomogram which was used to construct a scoring system—The Hematoma Expansion Prediction (HEP) Score, varying from 0 to 18 points. We evaluated the ability of the model to predict the probability of SHE using c-statistics.
Results
SHE occurred in 74 patients (31.2 %). The final model to predict SHE included 6 variables: time from onset to baseline CT (<3 vs. 3–12 h), history of dementia, current smoking, antiplatelet use, Glasgow Comma Scale score, and the presence of subarachnoid hemorrhage on baseline scan. The model had satisfactory discrimination ability with a bootstrap corrected c-index of 0.76 (95 % CI 0.69–0.83) and good calibration. Patients with a total HEP score >3 were at greatest risk for SHE.
Conclusions
We developed and internally validated a novel nomogram and an easy to use score which accurately predict the probability of SHE based on six easily obtainable parameters. This could be useful for treatment decision and stratification. External prospective validation of the HEP score is warranted before its application to other populations.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Anticoagulants</subject><subject>Blood pressure</subject><subject>Calibration</subject><subject>Cardiac arrhythmia</subject><subject>Cardiovascular disease</subject><subject>Cerebral Hemorrhage - complications</subject><subject>Cerebral Hemorrhage - diagnostic imaging</subject><subject>Coronary vessels</subject><subject>Creatinine</subject><subject>Critical Care Medicine</subject><subject>Dementia</subject><subject>Diabetes</subject><subject>Female</subject><subject>Hematoma</subject><subject>Hematoma - diagnosis</subject><subject>Hematoma - diagnostic imaging</subject><subject>Hematoma - etiology</subject><subject>Hemorrhage</subject><subject>Humans</subject><subject>Hyperlipidemia</subject><subject>Hypertension</subject><subject>Intensive</subject><subject>Internal Medicine</subject><subject>Ischemia</subject><subject>Male</subject><subject>Medical imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Models, Statistical</subject><subject>Neurology</subject><subject>Nomograms</subject><subject>Original Article</subject><subject>Probability</subject><subject>Radiography</subject><subject>Risk Factors</subject><subject>Stroke</subject><subject>Transient ischemic attack</subject><subject>Vein & artery diseases</subject><issn>1541-6933</issn><issn>1556-0961</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp1kE1LAzEQhoMotlZ_gBdZ8OJlNd_Z9VZqtULRQus5pNnZuqW7qUkr-u9N2aogeAgZyDPvTB6Ezgm-Jhirm0AoplmKiYiHq5QfoC4RQqY4l-RwV3OSypyxDjoJYYkxVbkSx6hDRS4ZzWkXDWevkIyGk2RqnYfbpJ88udotvKnTO_DVOxTJCGqzcbVJhh9r04TKNcnEQ1HZza6cWrOCU3RUmlWAs_3dQy_3w9lglI6fHx4H_XFqBc42qcriukRhIcycSwKZNEAMlpZhyUpblJwpxjJWgiLcmpKUjGQZcM6YzBWUrIeu2ty1d29bCBtdV8HCamUacNugY3auCOU8j-jlH3Tptr6J2-n4cSyFohJHirSU9S4ED6Ve-6o2_lMTrHeOdetYR8d651jz2HOxT97Oayh-Or6lRoC2QIhPzQL87-j_U78AwuuDTQ</recordid><startdate>20151001</startdate><enddate>20151001</enddate><creator>Yao, Xiaoying</creator><creator>Xu, Ye</creator><creator>Siwila-Sackman, Erica</creator><creator>Wu, Bo</creator><creator>Selim, Magdy</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope></search><sort><creationdate>20151001</creationdate><title>The HEP Score: A Nomogram-Derived Hematoma Expansion Prediction Scale</title><author>Yao, Xiaoying ; Xu, Ye ; Siwila-Sackman, Erica ; Wu, Bo ; Selim, Magdy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c508t-7802817055ab461e86ae1a06c3063fcdf4373383fe714caf1f3188e4433697ef3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Anticoagulants</topic><topic>Blood pressure</topic><topic>Calibration</topic><topic>Cardiac arrhythmia</topic><topic>Cardiovascular disease</topic><topic>Cerebral Hemorrhage - complications</topic><topic>Cerebral Hemorrhage - diagnostic imaging</topic><topic>Coronary vessels</topic><topic>Creatinine</topic><topic>Critical Care Medicine</topic><topic>Dementia</topic><topic>Diabetes</topic><topic>Female</topic><topic>Hematoma</topic><topic>Hematoma - diagnosis</topic><topic>Hematoma - diagnostic imaging</topic><topic>Hematoma - etiology</topic><topic>Hemorrhage</topic><topic>Humans</topic><topic>Hyperlipidemia</topic><topic>Hypertension</topic><topic>Intensive</topic><topic>Internal Medicine</topic><topic>Ischemia</topic><topic>Male</topic><topic>Medical imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Models, Statistical</topic><topic>Neurology</topic><topic>Nomograms</topic><topic>Original Article</topic><topic>Probability</topic><topic>Radiography</topic><topic>Risk Factors</topic><topic>Stroke</topic><topic>Transient ischemic attack</topic><topic>Vein & artery diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yao, Xiaoying</creatorcontrib><creatorcontrib>Xu, Ye</creatorcontrib><creatorcontrib>Siwila-Sackman, Erica</creatorcontrib><creatorcontrib>Wu, Bo</creatorcontrib><creatorcontrib>Selim, Magdy</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>Neurocritical care</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yao, Xiaoying</au><au>Xu, Ye</au><au>Siwila-Sackman, Erica</au><au>Wu, Bo</au><au>Selim, Magdy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The HEP Score: A Nomogram-Derived Hematoma Expansion Prediction Scale</atitle><jtitle>Neurocritical care</jtitle><stitle>Neurocrit Care</stitle><addtitle>Neurocrit Care</addtitle><date>2015-10-01</date><risdate>2015</risdate><volume>23</volume><issue>2</issue><spage>179</spage><epage>187</epage><pages>179-187</pages><issn>1541-6933</issn><eissn>1556-0961</eissn><abstract>Background
Identification of intracerebral hemorrhage (ICH) patients at risk of substantial hematoma expansion (SHE) could facilitate the selection of candidates likely to benefit from therapies aiming to minimize ICH growth. We aimed to develop a grading tool that can be quickly used during the hyperacute phase to predict the risk of SHE.
Methods
We reviewed data from 237 spontaneous ICH patients who had baseline head CT scan within 12 h of symptom onset and follow-up CT during the following 72 h. We performed logistic regression analyses to determine the predictors of SHE (defined as an absolute increase in ICH volume >6 ml or an increase >33 % on follow-up CT). We identified 6 predictors; each was assigned a point in the graphic interface of a nomogram which was used to construct a scoring system—The Hematoma Expansion Prediction (HEP) Score, varying from 0 to 18 points. We evaluated the ability of the model to predict the probability of SHE using c-statistics.
Results
SHE occurred in 74 patients (31.2 %). The final model to predict SHE included 6 variables: time from onset to baseline CT (<3 vs. 3–12 h), history of dementia, current smoking, antiplatelet use, Glasgow Comma Scale score, and the presence of subarachnoid hemorrhage on baseline scan. The model had satisfactory discrimination ability with a bootstrap corrected c-index of 0.76 (95 % CI 0.69–0.83) and good calibration. Patients with a total HEP score >3 were at greatest risk for SHE.
Conclusions
We developed and internally validated a novel nomogram and an easy to use score which accurately predict the probability of SHE based on six easily obtainable parameters. This could be useful for treatment decision and stratification. External prospective validation of the HEP score is warranted before its application to other populations.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>25963292</pmid><doi>10.1007/s12028-015-0147-4</doi><tpages>9</tpages></addata></record> |
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subjects | Aged Aged, 80 and over Anticoagulants Blood pressure Calibration Cardiac arrhythmia Cardiovascular disease Cerebral Hemorrhage - complications Cerebral Hemorrhage - diagnostic imaging Coronary vessels Creatinine Critical Care Medicine Dementia Diabetes Female Hematoma Hematoma - diagnosis Hematoma - diagnostic imaging Hematoma - etiology Hemorrhage Humans Hyperlipidemia Hypertension Intensive Internal Medicine Ischemia Male Medical imaging Medicine Medicine & Public Health Models, Statistical Neurology Nomograms Original Article Probability Radiography Risk Factors Stroke Transient ischemic attack Vein & artery diseases |
title | The HEP Score: A Nomogram-Derived Hematoma Expansion Prediction Scale |
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