Evidence map›Paper›PMID 36738227›Full record

ArticleJournal of neurotrauma2023

Optimizing Choice and Timing of Behavioral Outcome Tests After Repetitive Mild Traumatic Brain Injury: A Machine Learning-Based Approach on Multiple Pre-Clinical Experiments.

Philipp Lassarén, Grace Conley, Masen L Boucher, Ashley N Conley, Nicholas J Morriss, Jianhua Qiu, Rebekah C Mannix, Eric Peter Thelin

Abstract read
In one paragraph

Article in Journal of neurotrauma, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Philipp LassarénDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Grace ConleyDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.
Masen L BoucherDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.
Ashley N ConleySchool of Medicine, Boston University, Boston, Massachusetts, USA.
Nicholas J MorrissDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.
Jianhua QiuDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.
Rebekah C MannixDivision of Emergency Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.
Eric Peter ThelinDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

Funding

Genetic Analysis and Manipulation Core (GAEC)P50HD105351 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI Hisashi Umemori · 2021 to 2026
$9.4M
NICHD NIH HHS P50 HD105351
6 · The paper itself

Abstract

Repetitive mild traumatic brain injury (rmTBI) is a potentially debilitating condition with long-term sequelae. Animal models are used to study rmTBI in a controlled environment, but there is currently no established standard battery of behavioral tests used. Primarily, we aimed to identify the best combination and timing of behavioral tests to distinguish injured from uninjured animals in rmTBI studies, and secondarily, to determine whether combinations of independent experiments have better behavioral outcome prediction accuracy than individual experiments. Data from 1203 mice from 58 rmTBI experiments, some of which have already been published, were used. In total, 11 types of behavioral tests were measured by 37 parameters at 13 time points during the first 6 months after injury. Univariate regression analyses were used to identify optimal combinations of behavioral tests and whether the inclusion of multiple heterogenous experiments improved accuracy.

Indexed as

Brain ConcussionAnimalsBehavior, AnimalDisease Models, AnimalMaze LearningMiceModels, Animalanimal studiesbehavioral outcomesMorris water mazerepetitive mild traumatic brain injury

Identifiers

PMID36738227
PMCPMC10458377

What OpenQuestion holds

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LicenceCC BY
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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.