Predicting vaginal birth after previous cesarean: Using machine‐learning models and a population‐based cohort in Sweden
Charlotte Lindblad Wollmann; Kyle D. Hart; Can Liu; Aaron B. Caughey; Olof Stephansson; Jonathan M. Snowden · 2020 · Acta Obstetricia Et Gynecologica Scandinavica
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 (excerpt)
INTRODUCTION: Predicting a woman's probability of vaginal birth after cesarean could facilitate the antenatal decision-making process. Having a previous vaginal birth strongly predicts vaginal birth after cesarean. Delivery outcome in…
Excerpt shown for reference under fair use — read the full paper at the publisher.
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/aogs.14020