Current perspectives on the recognition and management of treatment-resistant schizophrenia: challenges and opportunities
Bibliographic record
Abstract
INTRODUCTION: Treatment-resistant schizophrenia (TRS) significantly impacts patients with schizophrenia, leading to a high disease burden, reduced quality of life, and functional impairment. Many patients fail to respond to standard antipsychotic treatments, requiring specialized therapeutic approaches. Clozapine remains the only approved treatment for patients with TRS, demonstrating effectiveness in reducing symptoms, hospitalizations, and risk of suicide. However, its use is often delayed due to concerns about adverse events, and the need for ongoing monitoring. AREAS COVERED: This critical perspective incorporates insights from psychiatrists in Greece and a comprehensive literature analysis that includes clinical guidelines and systematic reviews. It highlights strategies for early diagnosis and timely initiation of clozapine, while emphasizing practical challenges in its use. Recommendations emphasize reducing treatment delays and overcoming barriers such as inadequate training and hesitancy among clinicians. A comprehensive literature search was conducted on PubMed, Google Scholar, and Cochrane Library without any date restrictions to ensure a thorough review of available evidence. The initial literature search was carried out in September 2024, with a subsequent search conducted in March 2025. EXPERT OPINION: International guidelines consistently recommend clozapine as the first-line treatment for patients with TRS; nevertheless, the authors advocate enhanced awareness to optimize use. Most adverse events can be effectively managed with proper oversight, and early initiation is crucial to improving remission rates and the quality of life of patients with TRS. There is a need for systemic improvements in clinical practice, which requires evidence-based guidance to better address treatment efficacy in this challenging patient population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".