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Impaired Dynamic Cerebral Autoregulation to Postural Stress Following Concussive Injuries in Adolescents

2017· article· en· W2892772084 on OpenAlexaffabout
M. Erin Moir, Kolten C. Abbott, Christopher S. Balestrini, Lisa Fischer, Douglas D. Fraser, J. Kevin Shoemaker

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsChildren’s Health Research InstituteWestern University
Fundersnot available
KeywordsConcussionMedicineCerebral autoregulationTranscranial DopplerCerebral blood flowAutoregulationBlood pressureAnesthesiaHeart ratePopulationPoison controlCardiologyPhysical therapyInternal medicineInjury preventionEmergency medicine

Abstract

fetched live from OpenAlex

Concussions disproportionately affect adolescents and ongoing maturation places this population at increased risk for prolonged recovery and long‐term impairments in neurologic functioning. Although cerebrovascular impairments are believed to contribute to concussion symptoms and recovery, little information exists regarding brain vasomotor control in adolescent concussion, particularly during rapid changes in blood pressure that demand a dynamic cerebral autoregulatory response. The current investigation tested the hypothesis that adolescent concussion is marked by impaired dynamic cerebral autoregulation (CA). Twenty‐two adolescents diagnosed with a concussion (CONC; 13 females; 15 ± 1 years; 26 ± 20 days post‐injury, SCAT3 symptom score = 12 ± 6) and twenty‐seven healthy controls (CTRL; 15 females; 14 ± 2 years; SCAT3 symptom score = 6 ± 4) completed two repeated sit‐to‐stand trials. CONC were followed through their rehabilitation for up to 12‐weeks. Arterial blood pressure (ABP), cerebral blood flow velocity (CBFV), end‐tidal carbon dioxide partial pressure (P et CO 2 ), and heart rate (HR) were measured continuously with finger photoplethysmography (Finapres Medical Systems BV), transcranial Doppler ultrasound (Multigon Industries), a gas analyzer (AD Instruments), and a standard 3‐lead electrocardiogram (ECG), respectively. Furthermore, cardiac output (CO) was provided via the Model flow algorithm and cerebrovascular resistance (CVR) was calculated. The rate of the drop in CVR relative to the change in ABP provided the rate of regulation (RoR). The drop in ABP with standing was similar between CONC and CTRL (25 ± 8 vs. 24 ± 7 mmHg; p = 0.62) although the time to ABP nadir was longer in CONC compared with CTRL (7.2 ± 1.1 vs. 6.1 ± 1.3 sec; p = 0.002). Similarly, time to CBFV nadir was longer in CONC compared with CTRL (5.9 ± 1.4 vs. 4.4 ± 2.0 sec; p = 0.003). Compared to CTRL, RoR was reduced in CONC at study entry (0.21 ± 0.06 vs. 0.16 ± 0.04 sec −1 ; p = 0.005). However, at the time of CONC final visit (SCAT3 symptom score = 4 ± 5), RoR improved to levels similar to CTRL (0.20 ± 0.08 vs. 0.21 ± 0.06 sec −1 ; p = 0.55). During sitting and standing, CONC and CTRL had similar P et CO 2 . The change in heart rate with standing was similar between CONC and CTRL (30 ± 6 vs. 26 ± 9 bpm; p = 0.09) although the time to peak HR was longer in CONC compared with CTRL (10.8 ± 2.5 vs. 9.4 ± 2.0 sec; p = 0.004). Furthermore, a similar increase in CO was witnessed with standing in CONC and CTRL (1.4 ± 1.6 vs. 1.7 ± 0.7 L/min; p = 0.28). Impairments in dynamic CA are evident in adolescents following a concussive injury which recover in accordance with clinical symptoms. Therefore, RoR may aid decisions regarding diagnosis, rehabilitation, and recovery of adolescent concussion. Support or Funding Information Research supported by the Children's Health Research Institute (London, Canada).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.297
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2017
Admission routes2
Has abstractyes

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