Clinical Decision Rules to Improve the Detection of Adverse Drug Events in Emergency Department Patients
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Notice bibliographique
Résumé
OBJECTIVES: Adverse drug events (ADEs) are unintended and harmful consequences of medication use. They are associated with high health resource use and cost. Yet, high levels of inaccuracy exist in their identification in clinical practice, with over one-third remaining unidentified in the emergency department (ED). The study objective was to derive clinical decision rules (CDRs) that are sensitive for the detection of ADEs, allowing their systematic identification early in a patient's hospital course. METHODS: This was a prospective observational cohort study carried out in two Canadian tertiary care hospitals. Participants were adults presenting to the ED having ingested at least one prescription or over-the-counter medication within 2 weeks. Nurses and physicians evaluated patients for standardized clinical findings. A second evaluator performed interobserver assessments of predictor variables in a subset of patients. Pharmacists, who were blinded to the predictor variables, evaluated all patients for ADEs. An independent committee reviewed and adjudicated cases where the ADE assessment was uncertain or the pharmacist's diagnosis differed from the physician's working diagnosis. The primary outcome was an ADE that required a change in medical therapy, diagnostic testing, consultation, or hospital admission. CDRs were derived using kappa coefficients, chi-square statistics, and recursive partitioning. RESULTS: Among 1,591 patients, 131 (8.2%, 95% confidence interval [CI] = 7.0% to 9.7%) were diagnosed with the primary outcome. The following variables were associated with ADEs and were used to derive two CDRs: 1) presence of comorbid conditions, 2) antibiotic use within 7 days, 3) medication changes within 28 days, 4) age ≥ 80 years, 5) arrival by ambulance, 6) triage acuity, 7) recent hospital admission, 8) renal failure, and 9) use of three or more prescription medications. The more sensitive rule had a sensitivity of 96.7% (95% CI = 91.8% to 98.6%) and required 40.8% (95% CI = 37.7% to 42.9%) of patients to have medication review. The more specific rule had a sensitivity 90.8% (95% CI = 81.4% to 95.7%) and required 28.3% of patients to proceed to medication review. CONCLUSIONS: The authors derived CDRs that identified patients with ADEs with high sensitivity. These rules may improve the identification of ADEs early in a patient's hospital course while limiting the number of patients requiring a detailed medication review.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 découle