Prepulse inhibition in patients with bipolar disorder: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Prepulse inhibition (PPI) is a measurement method for the sensory gating process, which helps the brain adapt to complex environments. PPI may be reduced in patients with bipolar disorder (BD). This study investigated PPI deficits in BD and pooled the effect size of PPI in patients with BD. Methods We conducted a literature search on PPI in patients with BD from inception to July 27, 2019 in PubMed, Embase, Cochrane Library databases, and Chinese databases. No age, sex, and language restriction were set. The calculation formula was PPI = 100 - [100*((prepulse - pulse amplitude) / pulse amplitude)]. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of studies. Results Ten eligible papers were identified, of which five studies including a total of 141 euthymic patients and 132 healthy controls (HC) were included in the meta-analysis. Compared with HC, euthymic patients with BD had significantly lower PPI at the 60 ms interstimulus interval (ISI) between pulse and prepulse (P = 0.476, I2 = 0.0%, SMD = − 0.32, 95% CI = − 0.54 - -0.10). Sensitivity analysis shows no significant change in the combined effect value after removing any single study. There was no publication bias using the Egger’s test at 60 ms (P = 0.606). The meta-analysis of PPI at the 60 ms ISI could have significant clinical heterogeneity in mood episode state, as well as lack of data on BD I or II subtypes. Conclusions Euthymic patients with BD show PPI deficits at the 60 ms, suggesting a deficit in the early sensory gate underlying PPI. The PPI inhibition rate at a 60 ms interval is a stable index. More research is needed in the future to confirm this outcome, and to delve deeper into the mechanisms behind deficits.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".