Impact of Pharmacist Interventions in Patients with Dyslipidemia: A Systematic Review
Notice bibliographique
Résumé
Purpose: To determine the effect of pharmacistled interventions in dyslipidemia on clinical and process outcomes. Methods: Search: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, International Pharmaceutical Abstracts, HealthSTAR, Pascal, MEDLINE In-Process & Other Non-Indexed Citations, CINAHL Plus with Full Text, Health-Source: Nursing Edition, Academic Search Complete, BIOSIS Previews, Science Citation Index Expanded and Social Sciences Citation Index were searched from their inception to September 2008. Where possible an RCT filter was used. Article screening and selection: Inclusion criteria were: 1) RCTs and 2) pharmacist-provided pharmaceutical care, either independently or as part of a health care team or a collaborative agreement (team-directed) with other health care providers. There were no restrictions on language, sample size, study duration or practice setting. Quality assessment: Risk of bias was assessed using the Cochrane Collaboration's Risk of Bias tool and studies were judged as low, high or unclear risk of bias. Data Extraction: Data extraction was performed by 2 independent reviewers using a standardized data collection form. Outcomes: The primary outcome was absolute reduction in LDL cholesterol. Secondary outcomes included proportion of patients at target, initiation/modification of lipid therapy, compliance with lipid therapy, health-related quality of life and patient satisfaction. Data Analysis: Data were analyzed using a random effects model with analysis based on the Der-Simonian-Laird method. Calculations included odds ratio for dichotomous data and weighted mean difference (WMD) or standardized mean differences for continuous data. Subgroup analyses or meta-regression were conducted to investigate possible sources of heterogeneity. An indirect comparison of pharmacist-directed versus pharmacist collaborative care interventions was done. Sensitivity analysis was performed based on risk of bias. Results: A total of 8422 articles were retrieved from the search. From these, 114 articles were selected for full review, and 12 articles were included. The overall difference in LDL ( n = 543 patients) was not statistically significant (WMD −0.09 mmol/L, 95% CI −0.23, 0.04). The difference in total cholesterol was statistically significant (WMD −0.16, 95% CI −0.30, −0.02). Patients followed by a pharmacist were 3 times more likely to be at target (OR 2.9, 95% CI 1.1–7.5) and 2 times more likely to have their cholesterol measured (OR 2.4, 95% CI 1.6–3.6). Conclusions: Pharmacist interventions in a variety of settings have an impact on the lowering of total cholesterol. Patients receiving interventions that included pharmacist care were more likely to be at target and have their lipid panel measured. The types of interventions provided by pharmacists vary in terms of setting and components.
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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 | 0,013 | 0,049 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,012 | 0,009 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 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 ».