Work

Leveraging High-Frequency Postoperative ICU Arterial Blood Pressure Data from Electronic Health Records for Research: A Brief Report

Year: 2026

Type: article

Abstract: Postoperative blood pressure fluctuations after cardiac surgery are highly clinically relevant, yet analyzing high-frequency arterial pressure data remains challenging. In this study, we introduce a novel methodology for processing minute-by-minute postoperative intensive care unit (ICU) arterial pressure data. The pipeline implements a series of systematic data-cleaning steps to resolve artifacts and ensure physiological plausibility, and deploys a multi-stage imputation framework to address missing intervals. Our approach constructs longitudinal blood pressure profiles that quantify the time spent within predefined blood pressure ranges, minimizing assumptions and enhancing data utility for research. We detail a rigorous and reusable workflow for data extraction, cleaning, and imputation, which may address limitations of previous methods and offer a framework to build a robust exposure metric for future research utilizing postoperative arterial pressure data.

Source: Journal of Medical Systems

DOI: 10.1007/s10916-026-02472-4

Authors: Gen Li, Robert E. Freundlich, Benjamin French, David R. McIlroy

Institutions: Vanderbilt University Medical Center, Vanderbilt University

Language: English

Topic: Machine Learning in Healthcare

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,990