COMPARATIVE STUDY
EVALUATION STUDIES
JOURNAL ARTICLE
Add like
Add dislike
Add to saved papers

Splanchnic vein thrombosis in necrotizing acute pancreatitis: Detection by computed tomographic venography.

AIM: To assess the diagnostic accuracy of computed tomographic venography (CTV) for splanchnic vein thrombosis (SVT) detection in necrotizing acute pancreatitis (AP) patients.

METHODS: Forty-three patients with necrotizing AP who underwent both CTV and digital subtraction angiography (DSA) within 3 d were analyzed in this retrospective comparative study. All CTV procedures were performed with a dual-source CT scanner. The presence and location of SVT were determined via blinded imaging data analyses.

RESULTS: According to the DSA results, 17 (39.5%) of the total 43 patients had SVT. The sensitivity, specificity, positive and negative predictive values of CTV for SVT detection were 100% (95%CI: 77.1%-100%), 92.3% (95%CI: 73.4%-98.7%), 89.5% (95%CI: 65.5%-98.2%) and 100% (95%CI: 82.8%-100%), respectively.

CONCLUSION: CTV is an effective examination for SVT detection in patients with necrotizing AP with high positive and negative predictive values.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app