Evidence map›Paper›PMID 35620767›Full record

ArticleCritical care explorations2022

Detection of Hemodynamic Status Using an Analytic Based on an Electrocardiogram Lead Waveform.

Florian F Schmitzberger, Ashley E Hall, Morgan E Hughes, Ashwin Belle, Bryce Benson, Kevin R Ward, Benjamin S Bassin

Open access · goldAbstract read
In one paragraph

Article in Critical care explorations, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Florian F SchmitzbergerDepartment of Emergency Medicine, Michigan Medicine, Ann Arbor, MI.
Ashley E HallDepartment of Emergency Medicine, Michigan Medicine, Ann Arbor, MI.
Morgan E HughesDepartment of Emergency Medicine, Michigan Medicine, Ann Arbor, MI.
Ashwin BelleFifth Eye, Inc., Ann Arbor, MI.
Bryce BensonFifth Eye, Inc., Ann Arbor, MI.
Kevin R WardDepartment of Emergency Medicine, Michigan Medicine, Ann Arbor, MI.
Benjamin S BassinDepartment of Emergency Medicine, Michigan Medicine, Ann Arbor, MI.
Michigan Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesDelayed identification of hemodynamic deterioration remains a persistent issue for in-hospital patient care. Clinicians continue to rely on vital signs associated with tachycardia and hypotension to identify hemodynamically unstable patients. A novel, noninvasive technology, the Analytic for Hemodynamic Instability (AHI), uses only the continuous electrocardiogram (ECG) signal from a typical hospital multiparameter telemetry monitor to monitor hemodynamics. The intent of this study was to determine if AHI is able to predict hemodynamic instability without the need for continuous direct measurement of blood pressure.

designRetrospective cohort study.

settingSingle quaternary care academic health system in Michigan. PATIENTS: Hospitalized adult patients between November 2019 and February 2020 undergoing continuous ECG and intra-arterial blood pressure monitoring in an intensive care setting.

interventionsNone. MEASUREMENTS AND MAIN

resultsOne million two hundred fifty-two thousand seven hundred forty-two 5-minute windows of the analytic output were analyzed from 597 consecutive adult patients. AHI outputs were compared with vital sign indications of hemodynamic instability (heart rate > 100 beats/min, systolic blood pressure < 90 mm Hg, and shock index of > 1) in the same window. The observed sensitivity and specificity of AHI were 96.9% and 79.0%, respectively, with an area under the curve (AUC) of 0.90 for heart rate and systolic blood pressure. For the shock index analysis, AHI's sensitivity was 72.0% and specificity was 80.3% with an AUC of 0.81.

conclusionsThe AHI-derived hemodynamic status appropriately detected the various gold standard indications of hemodynamic instability (hypotension, tachycardia and hypotension, and shock index > 1). AHI may provide continuous dynamic hemodynamic monitoring capabilities in patients who traditionally have intermittent static vital sign measurements.

Indexed as

artificial intelligencecritical caredecision support systemsheart rate variabilityhemodynamic monitoringmachine learning

Identifiers

PMID35620767
PMCPMC9116956
OpenAlexW4280531674

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.