Ultrasound guidance for femoral venous access in patients undergoing pulmonary vein isolation: A quasi‐randomized study
Péter Kupó; T Riesz; László Sághy; Máté Vámos; Gábor Bencsik; Attila Makai; Mária Kohári; A Benak · 2023 · Journal of Cardiovascular Electrophysiology
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
INTRODUCTION: Routine ultrasound (US) guidance for femoral venous access to decrease vascular complications of atrial fibrillation (AF) ablation procedures has been advocated. However, the benefit has not been unequivocally demonstrated by randomized-trial data. METHODS: Consecutive patients undergoing pulmonary vein isolation (PVI) on uninterrupted anticoagulant treatment were included. A quasi-random allocation to either US-guided or conventional puncture group was based on which of the two procedure rooms the patient was scheduled in, with only one of the rooms equipped with a US machine in
Abstract by Péter Kupó; T Riesz; László Sághy; Máté Vámos; Gábor Bencsik; Attila Makai; Mária Kohári; A Benak, Journal of Cardiovascular Electrophysiology (2023) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
A Randomized Trial of Intraarterial Treatment for Acute Ischemic Stroke
Negative / Null Result ReportDuodenal Infusion of Donor Feces for Recurrent Clostridium difficile
Negative / Null Result ReportStenting versus Endarterectomy for Treatment of Carotid-Artery Stenosis
Negative / Null Result ReportEffects of Combination Lipid Therapy in Type 2 Diabetes Mellitus
Replication FailureA Randomized Trial of Bevacizumab for Newly Diagnosed Glioblastoma
Negative / Null Result ReportSpironolactone for Heart Failure with Preserved Ejection Fraction
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.1111/jce.15893