Evidence map›Paper›PMID 34244908›Full record

ArticleAnnals of biomedical engineering2021

Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation.

Xianghao Zhan, Yiheng Li, Yuzhe Liu, August G Domel, Hossein Vahid Alizadeh, Zhou Zhou, Nicholas J Cecchi, Samuel J Raymond, Stephen Tiernan, Jesse Ruan and 5 more

Abstract read
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In one paragraph

Article in Annals of biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

9 citing papers in PubMed, 35 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

15 authors at 3 institutions in 2 countries.

Xianghao Zhan *Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Yiheng Li *Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA.
Yuzhe LiuDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA. yuzheliu@stanford.edu.ORCID http://orcid.org/0000-0002-9451-0620
August G DomelDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Hossein Vahid AlizadehDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Zhou ZhouDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Nicholas J CecchiDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Samuel J RaymondDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Stephen TiernanTechnological University Dublin, Dublin, Ireland.
Jesse RuanFord Motor Company, 3001 Miller Rd, Dearborn, MI, 48120, USA.
Saeed BarbatFord Motor Company, 3001 Miller Rd, Dearborn, MI, 48120, USA.
Olivier GevaertDepartment of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA.
Michael M ZeinehDepartment of Radiology, Stanford University, Stanford, 94305, CA, USA.
Gerald A GrantDepartment of Neurosurgery, Stanford University, Stanford, 94305, CA, USA.
David B CamarilloDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Stanford University · USFord Motor Company (United States) · USTechnological University Dublin · IE

Funding

Disseminating a validated mouthguard sensor to investigate the effect of head impacts on brain healthR24NS098518 · NINDS · STANFORD UNIVERSITY · PI CAMARILLO, DAVID, GRANT, GERALD ARTHUR · 2018 to 2021
$1.1M
NIH HHS R24NS098518
6 · The paper itself

Abstract

Brain tissue deformation resulting from head impacts is primarily caused by rotation and can lead to traumatic brain injury. To quantify brain injury risk based on measurements of kinematics on the head, finite element (FE) models and various brain injury criteria based on different factors of these kinematics have been developed, but the contribution of different kinematic factors has not been comprehensively analyzed across different types of head impacts in a data-driven manner. To better design brain injury criteria, the predictive power of rotational kinematics factors, which are different in (1) the derivative order (angular velocity, angular acceleration, angular jerk), (2) the direction and (3) the power (e.g., square-rooted, squared, cubic) of the angular velocity, were analyzed based on different datasets including laboratory impacts, American football, mixed martial arts (MMA), NHTSA automobile crashworthiness tests and NASCAR crash events. Ordinary least squares regressions were built from kinematics factors to the 95% maximum principal strain (MPS95), and we compared zero-order correlation coefficients, structure coefficients, commonality analysis, and dominance analysis. The angular acceleration, the magnitude and the first power factors showed the highest predictive power for the majority of impacts including laboratory impacts, American football impacts, with few exceptions (angular velocity for MMA and NASCAR impacts). The predictive power of rotational kinematics about three directions (x: posterior-to-anterior, y: left-to-right, z: superior-to-inferior) of kinematics varied with different sports and types of head impacts.

Indexed as

Accidents, TrafficModels, StatisticalAccelerationAutomobilesBiomechanical PhenomenaBrain Injuries, TraumaticData Interpretation, StatisticalFootballHeadHumansMartial ArtsMouth ProtectorsRegression AnalysisRotationWearable Electronic DevicesCommonality analysisDominance analysisHead impactRegression interpretationTraumatic brain injury

Identifiers

PMID34244908
OpenAlexW3179535140

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.