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Effect of a Machine Learning–Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial

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Effect of a Machine Learning–Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial
Wijnberge M et al.
PaperEvaluateClassical (pre-LLM)Open access

First RCT of an ML early warning in the OR: reduced hypotension (single centre)

Journal
JAMA
Year
2020
DOI
10.1001/jama.2020.0592 (as found)
Paper type
RCT

DOI (confirmed 2026-09-27): https://doi.org/10.1001/jama.2020.0592

Free full text (Unpaywall, 2026-09-27): https://jamanetwork.com/journals/jama/articlepdf/2761469/jama_wijnberge_2020_pc_200001.pdf

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More details
Open-access status
Not confirmed
Track and node
Anaes · AI RCTs
Depth level
Evaluate
Currency note
Pre-LLM; landmark

Resource-list status: S
Listed under: Anaesthesia / perioperative & critical-care specialty: Papers

Link checked: 2026-09-27 · Details researched: 2026-09-27Report a problem