A Scoping Review of Registered Clinical Studies on Mild Traumatic Brain Injury and Concussion (2000 to 2019)
Bibliographic record
Abstract
BACKGROUND: While many patients with mild traumatic brain injury (mTBI) or concussion recover completely, prolonged postconcussion symptoms remain a challenge for patients and an opportunity for clinical research. This has led to numerous research initiatives over the last 2 decades. OBJECTIVE: To review the characteristics of clinical studies on management of mTBI/concussion; and to examine their definitions of mTBI/concussion. METHODS: This scoping review included all clinical studies on diagnosis and management of patients with mTBI/concussion registered at www.clinicaltrials.gov from 2000 to June/2019. The terms "mild TBI/concussion" were used for the primary search. Definitions of mTBI/concussion were obtained from the protocols. When a definition was missing in the website, the study's investigators were contacted for clarification. RESULTS: There were 225 interventional and 95 observational studies. Most of the studies are focused on treatment (54.7%) or diagnosis (37.5%), while 3.4% examined preventive measures, 2.8% evaluated prognostic instruments, and 1.6% developed registries. Most of the studies in this American database were single-center initiatives led by American and Canadian institutions. The definitions of mTBI/concussion differed widely among 109 studies. CONCLUSION: The results of this review suggest that most of the clinical studies are focused on diagnosis and non-pharmacological therapies for patients with mTBI/concussion. The large number of differing definitions of mTBI/concussion among the studies creates significant limitations when comparing studies. The requirements for registering research protocols on mTBI/concussion should include the necessity to state the definition being used. There is a need for consensus on a uniform definition of concussion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.151 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.048 | 0.054 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".