A New Risk Index for Predicting Outcomes among Patients Undergoing Carotid Endarterectomy in Large Administrative
Saqib A Chaudhry1, Mohammad R Afzal2, Abdulkader Kassab3
1Zeenat Qureshi Stroke Institute, St. Cloud, Minnesota; Department of Neurology and Ophthalmology, Michigan State University, East Lansing, Michigan.
Insights
A new risk index helps predict patient mortality after carotid endarterectomy (CEA). This tool aids in risk adjustment for comparative studies using large datasets, improving patient outcome analysis.
Area of Science:
- Vascular Surgery
- Health Services Research
- Medical Informatics
Background:
- Carotid endarterectomy (CEA) is a common procedure to prevent stroke.
- Accurate risk adjustment is crucial for evaluating outcomes in CEA patients.
- Existing risk stratification tools may not fully capture in-hospital outcomes.
Purpose of the Study:
- To develop and validate a novel risk index for predicting in-hospital mortality and other adverse outcomes in patients undergoing CEA.
- To provide a tool for risk adjustment in comparative effectiveness research involving CEA.
Main Methods:
- Utilized data from the Nationwide Inpatient Sample (NIS) for derivation (2005-2006) and validation (2007-2009) cohorts.
- Identified predictors of a composite endpoint (stroke, cardiac complications, death) using multivariate logistic regression.
- Assigned points to significant predictors to create a risk index score.
Main Results:
- The derivation cohort included 120,633 patients; the validation cohort had 71,222 patients.
- Key predictors included age, atrial fibrillation, congestive heart failure, smoking, symptomatic status, and chronic renal failure.
- Increasing risk index scores correlated with significantly higher rates of the composite endpoint, with an AUC of 68.5%.
Conclusions:
- A new, validated risk index can effectively stratify risk and adjust for baseline differences in patients undergoing CEA.
- This index is valuable for analyzing outcomes in large administrative datasets for comparative studies.
- The tool supports more accurate risk adjustment in vascular surgery research.
Background:
We developed and validated a new index to provide risk adjustment and to predict in-hospital patient mortality and other outcomes in patients undergoing carotid endarterectomy (CEA).
Methods:
The primary endpoint was occurrence of stroke, cardiac complications, or death during hospitalization for CEA derived from the Nationwide Inpatient Sample. Multivariate logistic regression was performed to identify the effect of clinical and demographic factors on occurrence of the primary endpoint. Data from 2005 to 2006 (study period 1) were used to derive risk index score whereas data from 2007 to 2009 (study period 2) were used for validation of the risk index.
Results:
A total of 120,633 patients with mean age in years [ ±SD] of 71.1[ ±9.5] (42.4% women) underwent CEA during the derivation period. The rate of occurrence of composite endpoint during study period 1 was 3.1%. Predictors of the composite endpoint were (odds ratio [OR], P value) as follows: age 70 years or older (1.15, .013 assigned 1 point), atrial fibrillation (3.18, <.0001 assigned 3 points), Congestive Heart Failure (CHF) (1.81, <.0001 assigned 2 points), cigarette smoking (1.64, <.0001 assigned 2 points), symptomatic status (1.87, <.001 assigned 2 points), and chronic renal failure (1.64, <.0001 assigned 2 points). When applied to the validation cohort (n = 71,222), patients with scores 0-1 (OR 1.6, 95% confidence interval [CI] 1.5-1.8), scores 2-3 (OR 4.0, 95% CI 3.8-4.3), scores 4-5 (OR 7.5, 95% CI 6.8-8.2), and scores greater than 5 (OR 10.9, 95% CI 9.8-12.2) had composite rates of endpoint. The receiver operating characteristic curve of the risk index was 68.5% [±SE 0.5%].
Conclusion:
New risk index will assist in risk adjustment for analyses of outcomes in large administrative data sets for comparative studies involving patients undergoing CEA.
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