Determinants of Patient-Rated and Clinician-Rated Illness Severity in Schizophrenia
Bibliographic record
Abstract
OBJECTIVE: The contribution of specific symptoms on ratings of global illness severity in patients with schizophrenia is not well understood. The present study examined the clinical determinants of clinician and patient ratings of overall illness severity. METHOD: This study included 1,010 patients with a DSM-IV diagnosis of schizophrenia who participated in the baseline visit of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study conducted between January 2001 and December 2004 and who had available symptom severity, side effect burden, cognition, and community functioning data. Both clinicians and patients completed the 7-point Clinical Global Impressions-Severity of Illness scale (CGI-S), the primary measure of interest in the present study. Symptoms were rated using the Positive and Negative Syndrome Scale and the Calgary Depression Scale for Schizophrenia, and functional status with the Quality of Life Scale. Neurocognition, insight, and medication-related side effects were also evaluated. RESULTS: Clinicians rated illness severity significantly higher than patients (P < .001). There was moderate overlap between CGI-S ratings made by clinicians and patients, with almost one third of patients showing substantial (ie, greater than 1 point) discrepancies with clinician ratings. Clinician-rated CGI-S scores were most strongly associated with positive symptoms, with additional independent contributions made by negative, disorganized, and depressive symptoms, as well as functional outcome (all P values < .01). Patient-rated CGI-S scores, on the other hand, were most closely related to depressive symptoms, with additional independent contributions made by positive and anxiety symptoms, clinical insight, and neurocognition (all P values < .01). Depressive symptoms were the strongest predictor of patient-rated CGI-S scores even in patients with good clinical insight (P < .001). CONCLUSIONS: Patient and clinician views of overall illness severity are not necessarily interchangeable and differ in their clinical correlates. Taking these differences into account may enhance patient engagement in care and improve outcomes. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00014001.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".