A REAL-WORLD STUDY OF POINT OF CARE MONITORING (POCM) FOR CLOZAPINE BLOODWORK IN A COMMUNITY SETTING
Bibliographic record
Abstract
Abstract Background Clozapine is the only antipsychotic indicated for Treatment Resistant Schizophrenia (TRS) and the only antipsychotic shown to reduce suicidality. Clozapine has been shown to reduce all-cause mortality and rehospitalization (1,2). Despite schizophrenia treatment guideline recommendations less than quarter of TRS patients are prescribed clozapine. On average, it takes 10 years before a patient is initiated on clozapine (3); patients will typically receive more than 7 different antipsychotics, 2/3 will have been prescribed more than 3 antipsychotics together, and at higher than monograph recommendations. Treatment delay is correlated with impaired functionality, poorer outcome and greater disease burden and costs. Despite the effectiveness of clozapine, there is a reluctance to use it because of: patient concerns, e.g., blood test frequency; physician concerns, e.g., side effect management; system issues e.g., registration and monitoring; and medication use complexity e.g., dosing and titration (4). This has been further impacted by the COVID-19 pandemic, with patients either not being initiated or switched because of concerns about difficulties in blood monitoring (5). Aims & Objectives Clozapine utilization has been shown to increase with implementation of specific educational programs, audits, clozapine clinics, Point-of-Care (POC) testing (6), and involvement of allied health care professionals such as pharmacists. We conducted a Quality Improvement (QI) study of POC Monitoring (POCM) to evaluate patient experiences of required blood monitoring in a community setting. Method A POCM device (PRONTO) is approved in Canada and allows for real-time evaluation of white blood cell and neutrophil counts from a finger-tip capillary blood sample obtained using a standard lancet. Patients registered to the Clozaril Support and Assistance Network (CSAN) were switched from a regular laboratory (LAB) service to POCM - conducted by on-site nursing staff in a group home setting. Patients completed 7 Likert-scale questions assessing, from 0 – 10, their perceptions of: pain, fear, preference, worry (about what is done with the sample), overall experience, and which test provides better and more involvement in care. Results A total of 23 questionnaires were completed by patients on clozapine who previously attended at a local laboratory. Patients rated POCM as less painful than LAB (1.76 vs. 4.60); preferable (8.33 vs. 1.80); and a positive experience (8.89 vs. 3.59). Patients were less afraid of POCM than LAB (0.59 vs.1.80) and less worried (1.50 vs. 2.45). Patients rated being more involved in their care with POCM than with LAB (6.45 vs. 3.15) and that their care was better (6.67 vs. 3.28). All patients remained on clozapine and maintained full adherence with monitoring requirements. Discussion & Conclusion This is the first comprehensive evaluation of POCM for clozapine in a community mental health setting. There was a high degree of patient preference for POCM compared with traditional laboratory venipuncture. POCM potentially removes barriers to clozapine use given its acceptance by patients, ease of use, flexibility, rapidity, convenience, and decreased invasiveness. POCM is cost-effective as patients do not need to be transported to a laboratory and contributes to the safer monitoring of clozapine patients (particularly during pandemic situations). References x
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".