Evidence map›Paper›PMID 30255214›Full record

Trial reportAnnals of biomedical engineering2019

Quantifying Movement in Preterm Infants Using Photoplethysmography.

Ian Zuzarte, Premananda Indic, Dagmar Sternad, David Paydarfar

Open access · greenAbstract readClinical Trial
In one paragraph

Trial report in Annals of biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 27 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

4 authors at 2 institutions in 1 country.

Ian ZuzarteDepartment of Bioengineering, Northeastern University, Boston, MA, USA.
Premananda IndicDepartment of Electrical Engineering, University of Texas, Tyler, TX, USA.
Dagmar SternadDepartments of Biology, Electrical and Computer Engineering, and Physics, Northeastern University, Boston, MA, USA.
David PaydarfarDepartment of Neurology, Dell Medical School, and Institute for Computational Engineering and Sciences, The University of Texas, 1701 Trinity St. Stop Z0700, Health Discovery Bldg, 5.708A, Austin, TX, 78712, USA. david.paydarfar@austin.utexas.edu.
Northeastern University · USThe University of Texas at Tyler · US

Funding

Research Resource for Complex Physiologic SignalsR01GM104987 · NIGMS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI GOLDBERGER, ARY LOUIS, MARK, ROGER GREENWOOD · 2012 to 2019
$5.8M
Pre-Vent ApneaU01HL133536 · NHLBI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI AMBALAVANAN, NAMASIVAYAM, INDIC, PREMANANDA PAI · 2016 to 2020
$2.6M
Quantification of Predictive Motor Impairments in Individuals with ASDR21HD089731 · NICHD · NORTHEASTERN UNIVERSITY · PI SINHA, PAWAN, STERNAD, DAGMAR · 2017 to 2018
$450k
Eunice Kennedy Shriver National Institute of Child Health and Human Development HD089731National Science Foundation 1664815NHLBI NIH HHS HL133536NHLBI NIH HHS U01 HL133536NICHD NIH HHS R21 HD089731NIGMS NIH HHS GM104987NIGMS NIH HHS R01 GM104987
6 · The paper itself

Abstract

Long-term recordings of movement in preterm infants might reveal important clinical information. However, measurement of movement is limited because of time-consuming and subjective analysis of video or reluctance to attach additional sensors to the infant. We evaluated whether photoplethysmogram (PPG), routinely used for oximetry in preterm infants in the neonatal intensive care unit (NICU), can provide reliable long-term measurements of movement. In 18 infants [mean post-conceptional age (PCA) 31.10 weeks, range 29-34.29 weeks], we designed and tested a wavelet-based algorithm that detects movement signals from the PPG. The algorithm's performance was optimized relative to subjective assessments of movement using video and accelerometers attached to two limbs and force sensors embedded within the mattress (five infants, three raters). We then applied the optimized algorithm to infants receiving routine care in the NICU without additional sensors. The algorithm revealed a decline in brief movements (< 5 s) with increasing PCA (13 infants, r = - 0.87, p < 0.001, PCA range 27.3-33.9 weeks). Our findings suggest that quantitative relationships between motor activity and clinical outcomes in preterm infants can be studied using routine photoplethysmography.

Indexed as

AlgorithmsInfant, PrematureIntensive Care UnitsMovementSignal Processing, Computer-AssistedFemaleHumansInfant, NewbornMalePhotoplethysmographyContinuous wavelet transformMotor developmentMovement detectionPhotoplethysmographyPreterm movement

Identifiers

PMID30255214
PMCPMC6344309
OpenAlexW2892553441

What OpenQuestion holds

Textmetadata
LicenceTDM
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.