Pneumatosis intestinalis and porto-mesenteric venous gas: a multicenter study

Marta Della Seta, Roman Kloeckner, Daniel Pinto dos Santos, Thula Cannon Walter-Rittel, Felix Hahn, Jörn Henze, Annika Gropp, Johann Pratschke, Bernd Hamm, Dominik Geisel, Timo Alexander Auer*

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

Background: Estimating the prognosis of patients with pneumatosis intestinalis (PI) and porto-mesenteric venous gas (PMVG) can be challenging. The purpose of this study was to refine prognostication to improve decision making in daily clinical routine. Methods: A total of 290 patients with confirmed PI were included in the final analysis. The presence of PMVG and mortality (90d follow-up) were evaluated with regard to the influence of possible risk factors. Furthermore, a linear estimation model was devised combining significant parameters to calculate accuracies for predicting death in patients undergoing surgery by means of a defined operation point (ROC-analysis). Results: Overall, 90d mortality was 55.2% (160/290). In patients with PI only, mortality was 46.5% (78/168) and increased significantly to 67.2% (82/122) in combination with PMVG (median survival: PI: 58d vs. PI and PMVG: 41d; p < 0.001). In the entire patient group, 53.5% (155/290) were treated surgically with a 90d mortality of 58.8% (91/155) in this latter group, while 90d mortality was 51.1% (69/135) in patients treated conservatively. In the patients who survived > 90d treated conservatively (24.9% of the entire collective; 72/290) PMVG/PI was defined as “benign”/reversible. PMVG, COPD, sepsis and a low platelet count were found to correlate with a worse prognosis helping to identify patients who might not profit from surgery, in this context our calculation model reaches accuracies of 97% specificity, 20% sensitivity, 90% PPV and 45% NPV. Conclusion: Although PI is associated with high morbidity and mortality, „benign causes” are common. However, in concomitant PMVG, mortality rates increase significantly. Our mathematical model could serve as a decision support tool to identify patients who are least likely to benefit from surgery, and to potentially reduce overtreatment in this subset of patients.

OriginalspracheEnglisch
Aufsatznummer129
ZeitschriftBMC medical imaging
Jahrgang21
Ausgabenummer1
ISSN1471-2342
DOIs
PublikationsstatusVeröffentlicht - 12.2021

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