Does Mild Traumatic Brain Injury Increase the Risk for Dementia? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Mild traumatic brain injury (mTBI) is a putative risk factor for dementia; however, despite having apparent face validity, the evidence supporting this hypothesis remains inconclusive. Understanding the role of mTBI as a risk factor is becoming increasingly important given the high prevalence of mTBI, and the increasing societal burden of dementia. OBJECTIVE: Our objective was to use the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) format to determine if an association exists between mTBI and dementia and related factors, and to quantify the degree of risk. METHODS: In this format, two authors conducted independent database searches of PubMed, PsycInfo, and CINAHL using three search blocks to find relevant papers published between 2000 and 2020. Relevant studies were selected using pre-defined inclusion/exclusion criteria, and bias scoring was performed independently by the two authors before a subset of studies was selected for meta-analysis. Twenty-one studies met the inclusion criteria for this systematic review. RESULTS: The meta-analysis yielded a pooled odds ratio of 1.96 (95% CI 1.698-2.263), meaning individuals were 1.96 times more likely to be diagnosed with dementia if they had a prior mTBI. Most studies examining neuropsychiatric and neuroimaging correlates of dementia found subtle, persistent changes after mTBI. CONCLUSION: These results indicate that mTBI is a risk factor for the development of dementia and causes subtle changes in performance on neuropsychiatric testing and brain structure in some patients.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".