Academic Journal
Detection of asymptomatic carotid stenosis in patients with lower extremity arterial disease: development and external validations of a risk score
| Title: | Detection of asymptomatic carotid stenosis in patients with lower extremity arterial disease: development and external validations of a risk score |
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| Authors: | Poorthuis, MHF, Morris, DR, de Borst, GJ, Bots, ML, Greving, JP, Visseren, FLJ, Sherliker, P, Clack, R, Clarke, R, Lewington, S, Bulbulia, R, Halliday, A |
| Publisher Information: | Oxford University Press |
| Publication Year: | 2022 |
| Collection: | Oxford University Research Archive (ORA) |
| Description: | Background: Recommendations for screening patients with lower extremity arterial disease (LEAD) to detect asymptomatic carotid stenosis (ACS) are conflicting. Prediction models might identify patients at high risk of ACS, possibly allowing targeted screening to improve preventive therapy and compliance. Methods: We conducted aA systematic search for prediction models for ≥50% ACS in patients with LEAD was conducted. A prediction model in screened patients from the United States with anklebrachial index (ABI) of ≤0.9 was subsequently developed and . We assessed for discrimination and calibration. Finally, external validation in two independent cohorts, comprising 5400 cases from the United Kingdom and 1536 cases from the Netherlands. Results: After screening 4721 studies, no previously published prediction models were found. For development of our new model, data of 112,117 cases were used, of whom 6354 (5.7%) had ≥50% and 2801 (2.5%) had ≥70% ACS. Age, sex, smoking status, history of hypercholesterolemia, stroke/TIA, CHD and measured SBP were predictors of ACS. The model discriminated well, with an area under receiver operator characteristic (AUROC) curve of 0.71 (95%CI, 0.71-0.72) for ≥50% and 0.73 (95%CI, 0.72-0.74) for ≥70% ACS. Screening the 20% cases at highest risk detected 13.1% with ≥50% [number needed to screen (NNS: 8)], and 5.8% with ≥70% ACS (NNS: 17). This yielded 44.2% and 46.9% of cases with ≥50% and ≥70% ACS, respectively. External validation showed reliable discrimination and adequate calibration. Conclusion: The present risk score can predict significant ACS in LEAD cases reliably. This approach can be used to inform targeted screening of high-risk individuals to enhance detection of ACS. |
| Document Type: | article in journal/newspaper |
| Language: | English |
| Relation: | https://doi.org/10.1093/bjs/znab040 |
| DOI: | 10.1093/bjs/znab040 |
| Availability: | https://doi.org/10.1093/bjs/znab040 https://ora.ox.ac.uk/objects/uuid:31c9f8c8-df60-447c-ad90-17a60212072b |
| Rights: | info:eu-repo/semantics/openAccess ; CC Attribution (CC BY) |
| Accession Number: | edsbas.AA6893F6 |
| Database: | BASE |
| DOI: | 10.1093/bjs/znab040 |
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