Lactate in bipolar disorder: A systematic review and meta‐analysis
Bibliographic record
Abstract
Bipolar disorder (BD) is a debilitating mood disorder with no specific biological marker. No novel treatment has been developed specifically for BD in the last several decades. Although the pathophysiology of BD remains unclear, there is strong evidence in the literature supporting the role of mitochondrial dysfunction in BD. In this systematic review, we identified and investigated 12 studies that measure lactate, which is a direct marker for mitochondrial dysfunction, in BD patients and healthy controls. Six studies measured lactate levels in the brain through proton echo‐planar spectroscopy or magnetic resonance spectroscopy and five of these studies reported significantly elevated lactate levels in patients with BD. Two studies reporting cerebrospinal fluid lactate levels also found significantly elevated lactate in BD compared to healthy controls. Two other studies that reported peripheral lactate levels did not demonstrate significant findings. The meta‐analysis, using standardized means and a random‐effect model for five studies that measured brain lactate levels, corroborated the findings of the systematic review. Although the meta‐analysis had a nearly significant overall effect (Z = 1.97, P = 0.05), high statistical heterogeneity (I2 = 86%) and possible publication bias suggest that the results should be interpreted with caution. To validate lactate abnormalities in BD, further studies should be carried out, including larger sample sizes, not excluding female patients, and using standardized methodologies. Peripheral lactate levels and other bioenergetic markers should be thoroughly studied to better understand the role of mitochondrial dysfunction in BD and to help develop more objective diagnostic tools.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.023 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".