Postmaturity in a genetic subtype of schizophrenia
Bibliographic record
Abstract
OBJECTIVE: To determine whether postmaturity (gestation > 41 weeks), small for gestational age (SGA), and other pregnancy and birth complications that may elevate risk for neurodevelopmental disorders, are associated with elevated risk for schizophrenia in 22q11 Deletion Syndrome (22qDS), a genetic subtype of schizophrenia. METHOD: Antepartum and intrapartum features were examined in 20 adults with 22qDS-schizophrenia and three comparison groups: newborn encephalopathy (n = 164) and healthy newborn controls (n = 400) from Badawi et al.'s (Br Med J 1998, 317: 1549) study, and 16 non-psychotic 22qDS adults (22qDS-NP). RESULTS: Postmaturity (OR 13.0, 95% CI 3.95, 42.77; P < 0.001) and SGA (OR 3.59, 95% CI 1.23, 10.5; P = 0.03) were more prevalent in 22qDS-SZ than controls. Postmaturity was non-significantly more prevalent in 22qDS-SZ than in newborn encephalopathy (P = 0.06) or 22qDS-NP (P = 0.2). SGA showed similar rates in the two 22qDS groups and newborn encephalopathy, but was more prevalent in 22qDS-NP than controls (P = 0.05). CONCLUSION: The results suggest that postmaturity may be associated with expression of schizophrenia in a 22qDS subtype of schizophrenia. SGA may be a non-specific marker of neurodevelopmental disturbance.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".