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Record W2110994259 · doi:10.1136/bjsports-2013-092190

The effects of rest and treatment following sport-related concussion: a systematic review of the literature

2013· review· en· W2110994259 on OpenAlexaff
Kathryn Schneider, Grant L. Iverson, Carolyn A. Emery, Paul McCrory, Stanley A. Herring, Willem Meeuwisse

Bibliographic record

VenueBritish Journal of Sports Medicine · 2013
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsAlberta Children's HospitalUniversity of CalgaryUniversity of British ColumbiaAlberta Health Services
Fundersnot available
KeywordsCINAHLRest (music)Physical therapyBed restMedicineConcussionPhysical medicine and rehabilitationMEDLINERehabilitationSystematic reviewMeta-analysisInjury preventionPoison controlPsychiatryPsychological interventionInternal medicineEmergency medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the evidence for rest, treatment, and rehabilitation following sport-related concussion (SRC). DATA SOURCES: PubMed, CINAHL, PsychInfo, Cochrane Controlled Trials Registers, Health STAR, Sport Discus, EMBASE, Web of Science, and ProQuest. STUDY SELECTION: Articles were included if they met the following criteria: original research, reported SRC as a source of injury, and evaluated the effect of rest or treatment. DATA EXTRACTION: Study design, participants, treatment, outcome measures, and key findings. DATA SYNTHESIS: Three studies met the inclusion criteria for evaluating the effects of rest and twelve for treatment. Low-intensity aerobic exercise may be of benefit. CONCLUSIONS: The current evidence evaluating the effect of rest and treatment following SRC is sparse. An initial period of rest may be of benefit. Low-level exercise and multimodal physiotherapy may be of benefit for those who are slow to recover. There is a strong need for high level studies evaluating the effects of rest and treatment following SRC.

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)0.008
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.037
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.006
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.335
Teacher spread0.311 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations203
Published2013
Admission routes1
Has abstractyes

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