Catheter-directed Therapy for the Treatment of Massive Pulmonary Embolism: Systematic Review and Meta-analysis of Modern Techniques

2009 ◽  
Vol 20 (11) ◽  
pp. 1431-1440 ◽  
Author(s):  
William T. Kuo ◽  
Michael K. Gould ◽  
John D. Louie ◽  
Jarrett K. Rosenberg ◽  
Daniel Y. Sze ◽  
...  
2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
R Chopard ◽  
P Nielsen ◽  
F Ius ◽  
H Pilichowski ◽  
N Meneveau

Abstract Background and objectives The optimal pulmonary revascularization strategy in acute massive pulmonary embolism (PE) requiring the implantation extra corporeal membrane oxygenation remains controversial, and data are sparse. Methods We conducted a systematic review and meta-analysis of available evidence regarding the use of mechanical reperfusion (i.e. surgical or catheter-based embolectomy) and fibrinolytic strategies (i.e. systemic fibrinolysis, catheter-directed fibrinolysis, or as stand-alone therapy) in terms of mortality and bleeding outcomes. Results The literature search identified 835 studies, 17 of which were included or a total of 321 PE patients with ECMO. In total, 31.1% were treated with mechanical pulmonary reperfusion, while 78.9% received fibrinolytic strategies. The mortality rate was 23.0% in the mechanical reperfusion group and 43.1% in the fibrinolysis group (Figure). The pooled OR for mortality with mechanical reperfusion was 0.46 (95% CI, 0.213–0.997; I2=28.3%) versus fibrinolysis. The rate of bleeding in PE patients under ECMO was 29.1% in the mechanical reperfusion group and 26.0% in the fibrinolytic reperfusion (OR, 1.09; 95% CI, 0.46–2.54; I2=0.0%) among 10 eligible studies with available bleeding data. The meta-regression model did not identify any relationship between the covariates “more than one pulmonary reperfusion therapy” and “ECMO implantation before pulmonary reperfusion therapy”, and outcomes. Conclusions The results of the present meta-analysis and meta-regression suggest that surgical embolectomy yields the best results, regardless of the timing of VA-ECMO implantation in the reperfusion timeline, and regardless of whether fibrinolysis has been administered or not. FUNDunding Acknowledgement Type of funding sources: None.


Lung ◽  
2015 ◽  
Vol 193 (5) ◽  
pp. 639-651 ◽  
Author(s):  
Anurag Bajaj ◽  
Parul Rathor ◽  
Vishal Sehgal ◽  
Besher Kabak ◽  
Ajay Shetty ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shelly Soffer ◽  
Eyal Klang ◽  
Orit Shimon ◽  
Yiftach Barash ◽  
Noa Cahan ◽  
...  

AbstractComputed tomographic pulmonary angiography (CTPA) is the gold standard for pulmonary embolism (PE) diagnosis. However, this diagnosis is susceptible to misdiagnosis. In this study, we aimed to perform a systematic review of current literature applying deep learning for the diagnosis of PE on CTPA. MEDLINE/PUBMED were searched for studies that reported on the accuracy of deep learning algorithms for PE on CTPA. The risk of bias was evaluated using the QUADAS-2 tool. Pooled sensitivity and specificity were calculated. Summary receiver operating characteristic curves were plotted. Seven studies met our inclusion criteria. A total of 36,847 CTPA studies were analyzed. All studies were retrospective. Five studies provided enough data to calculate summary estimates. The pooled sensitivity and specificity for PE detection were 0.88 (95% CI 0.803–0.927) and 0.86 (95% CI 0.756–0.924), respectively. Most studies had a high risk of bias. Our study suggests that deep learning models can detect PE on CTPA with satisfactory sensitivity and an acceptable number of false positive cases. Yet, these are only preliminary retrospective works, indicating the need for future research to determine the clinical impact of automated PE detection on patient care. Deep learning models are gradually being implemented in hospital systems, and it is important to understand the strengths and limitations of these algorithms.


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