Samuel Lee

University of Cologne
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Articles (10)

Year:

2023

Year:

2022

Aims This network meta-analysis aimed to assess the effect of early coronary angiography (CAG) compared with selective CAG (late and no CAG) for patients after out-of-hospital cardiac arrest without ST-elevation myocardial infarction (NSTE-OHCA). Methods and results A systematic literature search was performed using the EMBASE, MEDLINE and Web of Science databases without restrictions on publication date. The last search was performed on 15 July 2022. Randomized controlled trials (RCTs) and non-randomized studies (NRS) comparing the effect of early CAG to selective CAG after NSTE-OHCA on survival and/or neurological outcomes were included. Meta-analyses were performed based on a DerSimonian-Laird random effects model. A total of 18 studies were identified by the literature search. After the exclusion of two studies due to high risk of bias, 16 studies (six RCTs, ten NRS) were included in the final analyses. Meta-analyses showed a statistically significant increase in survival after early CAG compared with selective CAG in the overall analysis [OR: 1.40, 95% confidence interval (CI): (1.12–1.76), P < 0.01, I2 = 68%]. This effect was lost in the subgroup analysis of RCTs [OR: 0.89, 95% CI: (0.73–1.10), P = 0.29, I2 = 0%]. Random effects model network meta-analysis of NRS based on a Bayesian method showed statistically significant increased survival after late compared with early CAG [OR: 4.20, 95% CI: (1.22, 20.91)]. Conclusion The previously reported superiority of early CAG after NSTE-OHCA is based on NRS at high risk of selection and survivorship bias. The meta-analysis of RCTs does not support routinely performing early CAG after NSTE-OHCA.

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2020

Collaborators (4)

Martin Mollenhauer

University Hospital

GERMANY
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Matti Adam

University of Cologne

GERMANY
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Dennis Mehrkens

University of Cologne

GERMANY
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Alexander Hof

University Hospital

GERMANY
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