Pre‐pulse inhibition deficits in individuals at clinical high‐risk for psychosis: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Aim Neurophysiological markers of schizophrenia may help identify individuals who are at an increased risk of developing psychosis. As an operational measure of sensorimotor gating, pre‐pulse inhibition (PPI) deficit has been investigated in clinical high‐risk (CHR) individuals. In this study, we performed a systematic review and meta‐analysis of studies that investigated PPI in CHR individuals. Methods Relevant studies published as of July 2019 were retrieved from the PubMed, Cochrane, Embase, PscyINFO, EBSCO and Chinese databases. PPI was evaluated by calculating the standard mean differences (SMDs) between CHR individuals and healthy controls (HC) in meta‐analysis. Quality of studies was assessed using the Newcastle‐Ottawa Scale. I 2 index was used to assess heterogeneity and Egger's test was used to assess publication bias. Results Eight studies were found to be eligible. The meta‐analysis included five studies with a combined study population of 184 CHR subjects and 161 HC. CHR individuals showed lower PPI levels compared to HC in 120 ms inter‐stimulus interval or stimulus onset asynchrony paradigm ( P = .491, SMD = −0.62). No significant heterogeneity was observed in 120 ms PPI paradigm ( χ 2 = 3.41, P = .491, I 2 = 0.0%). Conclusion CHR individuals had lower PPI level compared to HC in 120 ms paradigm, which were relatively stable and significant. The results indicate the presence of information processing and inhibitory problems prior to the development of full‐blown psychosis. PPI may be clinically used as an objective indicator to supplement the understanding of CHR individuals.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".