Understanding the course of persistent symptoms in schizophrenia: Longitudinal findings from the pattern study
Bibliographic record
Abstract
The Pattern study was conducted to provide longitudinal observational data for individual patients with persistent symptoms of schizophrenia. Pattern is an international, multicenter, non-interventional, prospective cohort study of schizophrenia outpatients who were not considered to be in recovery. In the longitudinal phase reported herein, patients were assessed over 1 year using different clinical rating scales. Patient management followed routine local clinical practice. Primary outcome was disease state, defined by the Positive and Negative Syndrome Scale (PANSS), Negative Symptom Factor Score (NSFS), Positive Symptom Factor Score (PSFS), and Personal and Social Performance (PSP) Scale. In total, 1344 protocol-compliant patients (70.9% male) were included. Patients showed a high stability in disease state between consecutive study visits. Persistent negative persistent symptoms and symptomatic remission were the most prevalent and stable disease states. Patients in relapse generally transitioned to negative persistent symptoms or to symptomatic remission. PANSS, PSP, and quality of life ratings remained relatively stable. Relapses occurred in 10% of patients; probability of relapse was associated with younger age, extra-pyramidal symptoms, and more antipsychotic medications. Despite treatment, schizophrenia symptoms tend to remain stable over time, without overall improvement. One of the greatest challenges in schizophrenia is attainment of full symptom remission.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".