A REAL-WORLD STUDY OF POINT OF CARE MONITORING (POCM) FOR CLOZAPINE BLOODWORK IN A COMMUNITY SETTING
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».