Can Machine Learning Personalize Cardiovascular Therapy in Sepsis?
Catling FJR; Nagendran M; Festor P; Bien Z; Harris S; Faisal AA; Gordon AC; Komorowski M · 2024 · Critical care explorations
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.
The finding, in one line
“Large randomized trials in sepsis have generally failed to find effective novel treatments.”
Abstract (excerpt)
Large randomized trials in sepsis have generally failed to find effective novel treatments. This is increasingly attributed to patient heterogeneity, including heterogeneous cardiovascular changes in septic shock. We discuss the potential…
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WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: Europe PMC · DOI 10.1097/cce.0000000000001087