Biomarkers of neuroprogression and late staging in bipolar disorder: A systematic review
Bibliographic record
Abstract
Background:Bipolar disorder may undertake a progressive course in a subset of patients, and research efforts have been made to understand the biological basis underlying this process. This systematic review examined the literature available on biological markers associated with illness progression in bipolar disorder.Methods:Peer-reviewed articles were assessed using Embase, PsycINFO and PubMed, as well as from external sources. After initial screening, a total of 871 citations from databases and other sources were identified. Participants with a diagnosis of bipolar disorder were included in our systematic review; however, studies with participants younger than 15 or older than 65 were excluded. All studies were assessed using the Newcastle-Ottawa Scale assessment tool, and data pertaining to the results were extracted into tabular form using Google Sheets and Google Documents. The systematic review was registered on PROSPERO international prospective register of systematic reviews (ID Number: CRD42020154305).Results:A total of 35 studies were included in the systematic review. Increased ventricular size and reduction of grey matter volume were the most common brain changes associated with illness progression in bipolar disorder. Among the several biomarkers evaluated in this systematic review, findings also indicate a role of peripheral inflammatory markers in this process.Discussion:The studies evaluating the biological basis of the illness progression in bipolar disorder are still scarce and heterogeneous. However, current evidence supports the notion of neuroprogression, the pathophysiological process related to progressive brain changes associated with clinical progression in patients with bipolar disorder. The increase in peripheral inflammatory biomarkers and the neuroanatomical changes in bipolar disorder suggest progressive systemic and structural brain alterations, respectively.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".