Guidelines for screening and monitoring of cardiometabolic risk in schizophrenia: systematic evaluation
Bibliographic record
Abstract
BACKGROUND: Metabolic and cardiovascular health problems have become a major focus for clinical care and research in schizophrenia. AIMS: To evaluate the content and quality of screening guidelines for cardiovascular risk in schizophrenia. METHOD: Systematic review and quality assessment of guidelines/recommendations for cardiovascular risk in people with schizophrenia published between 2000 and 2010, using the Appraisal of Guidelines for Research and Evaluation (AGREE). RESULTS: The AGREE domain scores varied between the 18 identified guidelines. Most guidelines scored best on the domains 'scope and purpose' and 'clarity of presentation'. The domain 'rigour of development' was problematic in most guidelines, and the domains 'stakeholder involvement' and 'editorial independence' scored the lowest. The following measurements were recommended (in order of frequency): fasting glucose, body mass index, fasting triglycerides, fasting cholesterol, waist, high-density lipoprotein/low-density lipoprotein, blood pressure and symptoms of diabetes. In terms of interventions, most guidelines recommended advice on physical activity, diet, psychoeducation of the patient, treatment of lipid abnormalities, treatment of diabetes, referral for advice and treatment, psychoeducation of the family and smoking cessation advice. Compared across all domains and content, four European guidelines could be recommended. CONCLUSIONS: Four of the evaluated guidelines are of good quality and should guide clinicians' screening and monitoring practices. Future guideline development could be improved by increasing its rigour and assuring user and patient involvement.
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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 | 0.030 | 0.115 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".