Predicting Significant Iliac Vein Compression Using a Probability Scoring System Derived From Minimal Luminal Area on Computed Tomography Angiography in Patients 65 Years of Age or Younger.


Journal

The Journal of invasive cardiology
ISSN: 1557-2501
Titre abrégé: J Invasive Cardiol
Pays: United States
ID NLM: 8917477

Informations de publication

Date de publication:
Jan 2021
Historique:
entrez: 1 1 2021
pubmed: 2 1 2021
medline: 24 8 2021
Statut: ppublish

Résumé

The presence of 50% or more stenosis on intravascular ultrasound (IVUS) is considered diagnostic of iliac vein compression (ILVC) by most operators. We have previously developed a scoring system combining minimal luminal area (MLA) at the compression site and age to predict ILVC as seen on IVUS. We present a revised and improved scoring system following an additional number of patients and limited to patients 65 years of age and younger. Patients were included from retrospective (n = 52) and prospective (n = 18) registries of consecutive patients who underwent computed tomography angiography (CTA) of the pelvis with venous filling and IVUS within a few weeks apart to evaluate for symptomatic ILVC at a single cardiovascular practice. Quantitative vascular analysis was performed on all images obtained. MLA and age were used to calculate a score derived from a previously published logistic regression formula. Patients >65 years in age were excluded. The predicted findings from the score were compared with the actual presence of compression on IVUS. The revised scoring system is based on a score of < or ≥ 0.533824 and MLA (mm²) of <140, ≥140 to <200, and ≥200. The negative predictive value (NPV) and positive predictive value (NPV and PPV) of each cut-off in predicting ILVC on IVUS were calculated. A total of 70 symptomatic patients were included (mean age, 52.6 ± 12.3 years). The model offered the following: accuracy = 54/70 (77.1%); sensitivity = 51/52 (98.1%); specificity = 3/18 (16.7%); PPV = 51/66 (77.3%); and NPV = 3/4 (75.0%). A scoring system using MLA on CTA and age provides a fairly accurate diagnostic test to predict the presence of significant ILVC as seen on IVUS.

Sections du résumé

BACKGROUND BACKGROUND
The presence of 50% or more stenosis on intravascular ultrasound (IVUS) is considered diagnostic of iliac vein compression (ILVC) by most operators. We have previously developed a scoring system combining minimal luminal area (MLA) at the compression site and age to predict ILVC as seen on IVUS. We present a revised and improved scoring system following an additional number of patients and limited to patients 65 years of age and younger.
METHODS METHODS
Patients were included from retrospective (n = 52) and prospective (n = 18) registries of consecutive patients who underwent computed tomography angiography (CTA) of the pelvis with venous filling and IVUS within a few weeks apart to evaluate for symptomatic ILVC at a single cardiovascular practice. Quantitative vascular analysis was performed on all images obtained. MLA and age were used to calculate a score derived from a previously published logistic regression formula. Patients >65 years in age were excluded. The predicted findings from the score were compared with the actual presence of compression on IVUS. The revised scoring system is based on a score of < or ≥ 0.533824 and MLA (mm²) of <140, ≥140 to <200, and ≥200. The negative predictive value (NPV) and positive predictive value (NPV and PPV) of each cut-off in predicting ILVC on IVUS were calculated.
RESULTS RESULTS
A total of 70 symptomatic patients were included (mean age, 52.6 ± 12.3 years). The model offered the following: accuracy = 54/70 (77.1%); sensitivity = 51/52 (98.1%); specificity = 3/18 (16.7%); PPV = 51/66 (77.3%); and NPV = 3/4 (75.0%).
CONCLUSION CONCLUSIONS
A scoring system using MLA on CTA and age provides a fairly accurate diagnostic test to predict the presence of significant ILVC as seen on IVUS.

Identifiants

pubmed: 33385981

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

E16-E18

Auteurs

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Classifications MeSH