A preliminary clinical scale to predict the risk of in-hospital death after carotid endarterectomy

Susanna L. Matsen, Bruce Alan Perler, David C. Chang, William R. Flinn, Alan Dardik, Sean D. O'Donnell

Research output: Contribution to journalArticle

Abstract

Objective: Carotid endarterectomy (CEA) remains the gold standard for the treatment of carotid disease, with mortality rates generally at 0.4% to 1.7%. Controversy remains with regards to its role in the treatment of the high-risk surgical population. We developed a new clinical scale incorporating weighted risk factors into a single numerical score that correlates with the risk of in-hospital death after CEA. We propose that this tool may serve to prospectively identify the high-risk patient. Methods: We performed a retrospective analysis of 10 years (1994 to 2003) of the Maryland hospital discharge database. Included in the analysis were patients with (1) International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure code 38.12 (endarterectomy of the vessels of the head and neck other than intracranial vessels) in the primary coding position but not in any secondary position, or (2) Diagnosis Code 433.00 to 433.91 (occlusion/stenosis, precerebral artery), or (3) the Diagnosis-Related Group 5 (extracranial vascular procedure). ICD codes representing preoperative conditions of the patients were identified and evaluated with stepwise regression modeling techniques for association with in-hospital deaths. Different regression models were evaluated and compared by discriminative power as measured by receiver operating characteristics (ROC) and goodness-of-fit to data as measured by r2 and the Hosmer-Lemeshow statistic. A numeric index correlating with the risk of in-hospital death was constructed by rounding the correlation coefficients for the statistically significant variables from the logistic regression. Results: We identified 23,237 cases. The mean age of patients was 70.6 years, with 54.7% male patients. There were 125 in-hospital deaths (0.54%). Patient age and four patient medical conditions emerged with significant associations with in-hospital deaths after CEA, and their relationships can be summarized in a single diagnostic scale: 1 point for age 5%. Conclusions: This new 5-item scale, based on patient age and past medical history, correlates moderately with the rate of in-hospital death after CEA. This clinical index may serve to identify high-risk patients. Future improvements to this diagnostic scale should focus on the diagnostic values of additional laboratory and demographic data.

Original languageEnglish (US)
Pages (from-to)861-868
Number of pages8
JournalJournal of Vascular Surgery
Volume42
Issue number5
DOIs
StatePublished - Nov 2005

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Carotid Endarterectomy
International Classification of Diseases
Endarterectomy
Diagnosis-Related Groups
ROC Curve
Blood Vessels
Pathologic Constriction
Neck
Arteries
Logistic Models
Head
Demography
Databases
Mortality
Therapeutics

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Surgery

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A preliminary clinical scale to predict the risk of in-hospital death after carotid endarterectomy. / Matsen, Susanna L.; Perler, Bruce Alan; Chang, David C.; Flinn, William R.; Dardik, Alan; O'Donnell, Sean D.

In: Journal of Vascular Surgery, Vol. 42, No. 5, 11.2005, p. 861-868.

Research output: Contribution to journalArticle

Matsen, Susanna L. ; Perler, Bruce Alan ; Chang, David C. ; Flinn, William R. ; Dardik, Alan ; O'Donnell, Sean D. / A preliminary clinical scale to predict the risk of in-hospital death after carotid endarterectomy. In: Journal of Vascular Surgery. 2005 ; Vol. 42, No. 5. pp. 861-868.
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abstract = "Objective: Carotid endarterectomy (CEA) remains the gold standard for the treatment of carotid disease, with mortality rates generally at 0.4{\%} to 1.7{\%}. Controversy remains with regards to its role in the treatment of the high-risk surgical population. We developed a new clinical scale incorporating weighted risk factors into a single numerical score that correlates with the risk of in-hospital death after CEA. We propose that this tool may serve to prospectively identify the high-risk patient. Methods: We performed a retrospective analysis of 10 years (1994 to 2003) of the Maryland hospital discharge database. Included in the analysis were patients with (1) International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure code 38.12 (endarterectomy of the vessels of the head and neck other than intracranial vessels) in the primary coding position but not in any secondary position, or (2) Diagnosis Code 433.00 to 433.91 (occlusion/stenosis, precerebral artery), or (3) the Diagnosis-Related Group 5 (extracranial vascular procedure). ICD codes representing preoperative conditions of the patients were identified and evaluated with stepwise regression modeling techniques for association with in-hospital deaths. Different regression models were evaluated and compared by discriminative power as measured by receiver operating characteristics (ROC) and goodness-of-fit to data as measured by r2 and the Hosmer-Lemeshow statistic. A numeric index correlating with the risk of in-hospital death was constructed by rounding the correlation coefficients for the statistically significant variables from the logistic regression. Results: We identified 23,237 cases. The mean age of patients was 70.6 years, with 54.7{\%} male patients. There were 125 in-hospital deaths (0.54{\%}). Patient age and four patient medical conditions emerged with significant associations with in-hospital deaths after CEA, and their relationships can be summarized in a single diagnostic scale: 1 point for age 5{\%}. Conclusions: This new 5-item scale, based on patient age and past medical history, correlates moderately with the rate of in-hospital death after CEA. This clinical index may serve to identify high-risk patients. Future improvements to this diagnostic scale should focus on the diagnostic values of additional laboratory and demographic data.",
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T1 - A preliminary clinical scale to predict the risk of in-hospital death after carotid endarterectomy

AU - Matsen, Susanna L.

AU - Perler, Bruce Alan

AU - Chang, David C.

AU - Flinn, William R.

AU - Dardik, Alan

AU - O'Donnell, Sean D.

PY - 2005/11

Y1 - 2005/11

N2 - Objective: Carotid endarterectomy (CEA) remains the gold standard for the treatment of carotid disease, with mortality rates generally at 0.4% to 1.7%. Controversy remains with regards to its role in the treatment of the high-risk surgical population. We developed a new clinical scale incorporating weighted risk factors into a single numerical score that correlates with the risk of in-hospital death after CEA. We propose that this tool may serve to prospectively identify the high-risk patient. Methods: We performed a retrospective analysis of 10 years (1994 to 2003) of the Maryland hospital discharge database. Included in the analysis were patients with (1) International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure code 38.12 (endarterectomy of the vessels of the head and neck other than intracranial vessels) in the primary coding position but not in any secondary position, or (2) Diagnosis Code 433.00 to 433.91 (occlusion/stenosis, precerebral artery), or (3) the Diagnosis-Related Group 5 (extracranial vascular procedure). ICD codes representing preoperative conditions of the patients were identified and evaluated with stepwise regression modeling techniques for association with in-hospital deaths. Different regression models were evaluated and compared by discriminative power as measured by receiver operating characteristics (ROC) and goodness-of-fit to data as measured by r2 and the Hosmer-Lemeshow statistic. A numeric index correlating with the risk of in-hospital death was constructed by rounding the correlation coefficients for the statistically significant variables from the logistic regression. Results: We identified 23,237 cases. The mean age of patients was 70.6 years, with 54.7% male patients. There were 125 in-hospital deaths (0.54%). Patient age and four patient medical conditions emerged with significant associations with in-hospital deaths after CEA, and their relationships can be summarized in a single diagnostic scale: 1 point for age 5%. Conclusions: This new 5-item scale, based on patient age and past medical history, correlates moderately with the rate of in-hospital death after CEA. This clinical index may serve to identify high-risk patients. Future improvements to this diagnostic scale should focus on the diagnostic values of additional laboratory and demographic data.

AB - Objective: Carotid endarterectomy (CEA) remains the gold standard for the treatment of carotid disease, with mortality rates generally at 0.4% to 1.7%. Controversy remains with regards to its role in the treatment of the high-risk surgical population. We developed a new clinical scale incorporating weighted risk factors into a single numerical score that correlates with the risk of in-hospital death after CEA. We propose that this tool may serve to prospectively identify the high-risk patient. Methods: We performed a retrospective analysis of 10 years (1994 to 2003) of the Maryland hospital discharge database. Included in the analysis were patients with (1) International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure code 38.12 (endarterectomy of the vessels of the head and neck other than intracranial vessels) in the primary coding position but not in any secondary position, or (2) Diagnosis Code 433.00 to 433.91 (occlusion/stenosis, precerebral artery), or (3) the Diagnosis-Related Group 5 (extracranial vascular procedure). ICD codes representing preoperative conditions of the patients were identified and evaluated with stepwise regression modeling techniques for association with in-hospital deaths. Different regression models were evaluated and compared by discriminative power as measured by receiver operating characteristics (ROC) and goodness-of-fit to data as measured by r2 and the Hosmer-Lemeshow statistic. A numeric index correlating with the risk of in-hospital death was constructed by rounding the correlation coefficients for the statistically significant variables from the logistic regression. Results: We identified 23,237 cases. The mean age of patients was 70.6 years, with 54.7% male patients. There were 125 in-hospital deaths (0.54%). Patient age and four patient medical conditions emerged with significant associations with in-hospital deaths after CEA, and their relationships can be summarized in a single diagnostic scale: 1 point for age 5%. Conclusions: This new 5-item scale, based on patient age and past medical history, correlates moderately with the rate of in-hospital death after CEA. This clinical index may serve to identify high-risk patients. Future improvements to this diagnostic scale should focus on the diagnostic values of additional laboratory and demographic data.

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