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Record W4304775943 · doi:10.1177/23259671221127049

Responsiveness of the Post-Concussion Symptom Scale to Monitor Clinical Recovery After Concussion or Mild Traumatic Brain Injury

2022· article· en· W4304775943 on OpenAlexafffund
Pierre Langevin, Pierre Frémont, Philippe Fait, Jean‐Sébastien Roy

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité LavalCorActive (Canada)Centre for Interdisciplinary Research in Rehabilitation
FundersFonds de Recherche du Québec - SantéPoznańskie Centrum Superkomputerowo-SiecioweRéseau Provincial de Recherche en Adaptation-RéadaptationAmerican Orthopaedic Society for Sports Medicine
KeywordsMinimal clinically important differenceConcussionMedicinePhysical therapyTraumatic brain injuryRehabilitationReceiver operating characteristicPhysical medicine and rehabilitationPost-concussion syndromeRating scaleNeck painCohortPoison controlInjury preventionRandomized controlled trialInternal medicinePsychiatryPsychologyEmergency medicine

Abstract

fetched live from OpenAlex

Background: The Post-Concussion Symptom Scale (PCSS) is used to assess the number and intensity of symptoms after a concussion/mild traumatic brain injury. However, its responsiveness to monitor clinical recovery has yet to be determined. Purpose: To evaluate the responsiveness of the PCSS to change and longitudinal validity in patients with persistent postconcussive symptoms as well as to explore the responsiveness of other clinical outcome measures to monitor recovery of physical symptoms in patients with persistent postconcussive symptoms. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: Patients with persistent symptoms after a concussion (N = 109) were evaluated using self-reported questionnaires at baseline and after a 6-week rehabilitation program. The program consisted of an individualized symptom-limited aerobic exercise program combined with education. Questionnaires included the PCSS, Neck Disability Index (NDI), Headache Disability Inventory (HDI), Dizziness Handicap Inventory (DHI), and Numeric Pain Rating Scale (NPRS) related to 1) neck pain and 2) headache. Internal responsiveness was evaluated using the effect size (ES) and standardized response mean (SRM), and external responsiveness was determined with the minimal clinically important difference (MCID) calculated using a receiver operating characteristic curve. The global rating of change was used as the external criterion. Pearson correlations were used to determine the longitudinal validity. Results: The PCSS was highly responsive (ES and SRM, >1.3) and had an MCID of 26.5 points (of 132) for the total score and 5.5 (of 22) for the number of symptoms. For longitudinal validity, low to moderate correlations were found between changes in PCSS and changes in NDI, HDI, and DHI. The NDI, HDI, DHI, and NPRS were also highly responsive (ES and SRM, >0.8). Conclusion: All questionnaires including the PCSS were highly responsive and can be used with confidence by clinicians and researchers to evaluate change over time in a concussion population with persistent symptoms.

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)0.030
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 score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.049
GPT teacher head0.374
Teacher spread0.325 · 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

Citations18
Published2022
Admission routes2
Has abstractyes

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