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Record W4246810090 · doi:10.21203/rs.3.rs-72770/v1

Prognostic Factors for Persistent Symptoms in Adults With Mild Traumatic Brain Injury: Protocol for an Overview of Systematic Reviews

2020· preprint· en· W4246810090 on OpenAlexafffund
Julien Déry, Élaine de Guise, Marie‐Ève Lamontagne

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité de MontréalUniversité Laval
FundersUniversité Laval
KeywordsTraumatic brain injuryProtocol (science)MedicineSystematic reviewIntensive care medicinePsychologyNeuroscienceMEDLINEPsychiatryAlternative medicinePathologyBiology

Abstract

fetched live from OpenAlex

Abstract Background: Mild traumatic brain injury (mTBI) is an increasing public health problem, and persistent symptoms following mTBI have several functional consequences. Understanding the prognosis of a condition is an important component of clinical decision-making and can help to guide prevention of long-term disabilities and to intervene with mTBI patients. Prognosis of chronic symptoms in mTBI has stimulated several empirical primary research papers and many systematic reviews. We aim to integrate these heterogenous factors into a model in order to have a better understanding of such prognostic factors on the development of chronic symptoms.Methods: We will conduct an overview of systematic reviews following steps described in the Cochrane Handbook. We will search for systematic reviews in databases using a search strategy to include articles that review evidence about prognosis of persistent symptoms after an mTBI in the adult population. Two reviewers will independently screen all references and then select eligible reviews based on eligibility criteria. Any disagreements will be discussed by the two reviewers and if consensus is not reached, we will consult a third reviewer. A data extraction grid will be used to extract relevant information. The risk of bias included will be rated using ROBIS tool. Data will be synthesized into a comprehensive conceptual map in order to have a better understanding of the predictor factors that could impact the recovery after mTBI.Discussion: Results will help multiple stakeholders, such as clinicians and rehabilitation program managers, to understand the prognosis of long-term consequences following an mTBI. It could guide stakeholders to recognize predisposing, precipitating, and perpetuating factors of their patients and to invest their time and resources on patients needing the most.Systematic review registration: PROSPERO CRD42020176676

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)0.079
metaresearch head score (Gemma)0.109
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.079
Threshold uncertainty score0.418

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.109
Meta-epidemiology (narrow)0.0090.007
Meta-epidemiology (broad)0.0210.025
Bibliometrics0.0180.017
Science and technology studies0.0050.005
Scholarly communication0.0090.011
Open science0.0060.008
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0640.009

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 head0.559
GPT teacher head0.537
Teacher spread0.022 · 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
GenreProtocol

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

Citations0
Published2020
Admission routes2
Has abstractyes

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