Evidence map›Paper›PMID 28124225›Full record

ArticleJournal of clinical monitoring and computing2018

Feasibility of automated titration of vasopressor infusions using a novel closed-loop controller.

Joseph Rinehart, Michael Ma, Michael-David Calderon, Maxime Cannesson

Abstract read
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In one paragraph

Article in Journal of clinical monitoring and computing, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
6.7field-weighted citation impact, top 3% 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

25 citing papers in PubMed, 53 citations in OpenAlex.

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  20. Closed-loop regulation of arterial pressure after acute brain death.Journal of clinical monitoring and computing · 2018
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Joseph RinehartDepartment of Anesthesiology & Perioperative Care, University of California Irvine, 101 The City Dr. South, Orange, CA, 92868, USA. jrinehar@uci.edu.
Michael MaDepartment of Anesthesiology & Perioperative Care, University of California Irvine, 101 The City Dr. South, Orange, CA, 92868, USA.
Michael-David CalderonDepartment of Anesthesiology & Perioperative Care, University of California Irvine, 101 The City Dr. South, Orange, CA, 92868, USA.
Maxime CannessonDepartment of Anesthesiology, University of California Los Angeles, Los Angeles, CA, USA.
University of California, Irvine · USUniversity of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blood pressure management is a central concern in critical care patients. For a variety of reasons, titration of vasopressor infusions may be an ideal use-case for computer assistance. Using our previous experience gained in the bench-to-bedside development of a computer-assisted fluid management system, we have developed a novel controller for this purpose. The aim of this preliminary study was to assess the feasibility of using this controller in simulated patients to maintain a target blood pressure in both stable and variable blood-pressure scenarios. We tested the controller in two sets of simulation scenarios: one with stable underlying blood pressure and a second with variable underlying blood pressure. In addition, in the variable phase of the study, we tested infusion-line delays of 8-60 s. The primary outcome for both testing conditions (stable and variable) was % case time in target range. We determined a priori that acceptable performance on the first phase of the protocol would require greater than 95% case-time in-target given the simple nature of the protocol, and for the second phase of the study 80% or greater given the erratic nature of the blood pressure changes taking place. 250 distinct cases for each simulation condition, both managed and unmanaged, were run over 4 days. In the stable hemodynamic conditions, the unmanaged group had an MAP of 57.5 ± 4.6 mmHg and spent only 5.6% of case time in-target. The managed group had an MAP of 70.3 ± 2.6 and spent a total of 99.5% of case time in-target (p < 0.00001 for both comparisons between groups). In the variable hemodynamic conditions, the unmanaged group had an MAP of 53.1 ± 5.0 mmHg and spent 0% of case time in-target. The managed group had an MAP of 70.5 ± 3.2 mmHg (p < 0.00001 compared to unmanaged group) and spent 88.6% of case time in-target (p < 0.00001 compared to unmanaged group), with 6.4% of case time over and 5.1% of case time under target. Increasing infusion lag increased coefficient of variation by about 10% per 15 s of lag (p = 0.001). This study demonstrated that this novel controller for vasopressor administration is able to main a target mean arterial pressure in a simulated physiologic model in the face of random disturbances and infusion-line lag.

Indexed as

AlgorithmsArterial PressureAutomationBlood PressureComputer SystemsCritical CareEquipment DesignFeasibility StudiesFluid TherapyHeart RateHemodynamicsHumansIntensive Care UnitsMonitoring, PhysiologicVasoconstrictor AgentsVasoconstrictor AgentsAutomated titrationBlood-pressure managementClosed-loopSepsis managementVasopressor

Identifiers

PMID28124225
OpenAlexW2581809797

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.