Psychoradiologic abnormalities of white matter in patients with bipolar disorder: diffusion tensor imaging studies using tract-based spatial statistics
Bibliographic record
Abstract
Background: An increasing number of psychoradiology studies that use tract-based spatial statistics (TBSS) of diffusion tensor imaging have reported abnormalities of white matter in patients with bipolar disorder; however, robust conclusions have proven elusive, especially considering some important clinical and demographic factors. In the present study, we performed a quantitative meta-analysis of TBSS studies to elucidate the most consistent white-matter abnormalities in patients with bipolar disorder. Methods: We conducted a systematic search up to May 2017 for all TBSS studies comparing fractional anisotropy (FA) between patients with bipolar disorder and healthy controls. We performed anisotropic effect size–signed differential mapping meta-analysis. Results: We identified a total of 22 data sets including 556 patients with bipolar disorder and 623 healthy controls. We found significant FA reductions in the genu and body of the corpus callosum in patients with bipolar disorder relative to healthy controls. No regions of increased FA were reported. In subgroup analyses, the FA reduction in the genu of the corpus callosum retained significance in patients with bipolar disorder type I, and the FA reduction in the body of the corpus callosum retained significance in euthymic patients with bipolar disorder. Meta-regression analysis revealed that the percentage of female patients was negatively correlated with reduced FA in the body of the corpus callosum. Limitations: Data acquisition, patient characteristics and clinical variables in the included studies were heterogeneous. The small number of diffusion tensor imaging studies using TBSS in patients with bipolar disorder type II, as well as the lack of other clinical information, hindered the application of subgroup meta-analyses. Conclusion: Our study consistently identified decreased FA in the genu and body of the corpus callosum, suggesting that interhemispheric communication may be the connectivity most affected in patients with bipolar disorder.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".