ArticleJournal of medical systems2026
Leveraging High-Frequency Postoperative ICU Arterial Blood Pressure Data from Electronic Health Records for Research: A Brief Report.
Article in Journal of medical systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.