S85. MANAGEMENT OF PHYSICAL HEALTH FOR PEOPLE WITH SCHIZOPHRENIA IN PRIMARY CARE: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Abstract Background We sought to determine how the physical health of people with schizophrenia is managed by family physicians in a primary care setting relative to those without schizophrenia. Methods A comprehensive literature search was conducted in three electronic databases for articles published in English up to January 2019. Studies were included if: (1) study design was observational; (2) population was patients receiving primary care from family physicians; (3) exposure was schizophrenia; (4) comparison was no schizophrenia; and (5) outcome was management of physical health condition. Study details, subject characteristics, methods, and results were extracted from each study and summarized in a qualitative manner. Risk of bias (RoB) for each study was assessed using the CLARITY tool. Results A total of 12 articles met inclusion criteria, including 9 retrospective cohort studies with low RoB and 3 case control studies with moderate RoB. Among patients with diabetes (5 studies), those with schizophrenia received lower rates of guideline-recommended monitoring. Among patients with cardiovascular disease (2 studies), those with schizophrenia received lower rates of guideline-recommended prescriptions (e.g., statins). Among patients at risk for cardiovascular disease (3 studies), those with schizophrenia received lower rates of guideline-recommended screening (e.g., serum cholesterol levels). Among patients at risk for cancer (2 studies), those with schizophrenia received lower rates of guideline-recommended screening (e.g., Papanicolaou test). Discussion Physical health management is an ongoing concern for individuals living with schizophrenia. These individuals often receive poorer care of their physical health by family physicians when compared to individuals without schizophrenia.
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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 | 0.011 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".