Study Family History of Psychiatry Disorders in Schizophrenia Patients
Bibliographic record
Abstract
Background: Schizophrenia is a chronic heterogeneous mental disorder that often has debilitating long-term outcomes. Our aim in this study is to survey history of psychiatric disorders in first-degree relatives of schizophrenia patients and its association with the disease clinical and demographic profile. Methods: In this retrospective study the hospital records of all schizophrenia patients that had been admitted in Ibn Sina Psychiatric Hospital from March 2018 to March 2019 were surveyed. Histories of any psychiatry disorders in the first-degree relatives of the schizophrenia patients were searched. The patients with positive family history were compared with those with negative family history in regard to age of onset, sex, negative symptoms, substance abuse and education level. Results: Of 250 files that were studied, 62 (24.2%) patients had family history of psychiatry disorders. Schizophrenia (10.8%), schizoaffective disorder (7.2%) and bipolar disorder (4.2%) were the most common psychiatry disorders in first-degree relatives of schizophrenia patients. Male sex, lower age at onset, substance abuse, negative symptoms, and lower education were more frequently observed in schizophrenia patients with positive family history. Conclusions: Our study demonstrated that family histories of schizophrenia, schizoaffective and bipolar disorder were higher in family history of schizophrenia patients than normal population. Furthermore, positive family history for psychiatric disorder is associated with worse prognosis in schizophrenia patients. J Neurol Res. 2020;10(6):231-234 doi: https://doi.org/10.14740/jnr631
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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 | 0.000 |
| 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".