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Background: In Germany, patients receiving oral anticoagulation (OAC) are often treated by general practitioners (GPs), and large proportions of patients receive vitamin K antagonists (VKAs). The quality of OAC in German GP practices, differences between various practices, and improvement potential through implementation of case management, have not yet been investigated satisfactorily.
Based on results of a cluster-randomized controlled trial, we aimed to assess whether OAC quality can be improved, any variations between practices exist and determine practice- and patient-level factors.
Methods: The PICANT trial (2012–2015) was performed in 52 GP practices in Hesse, Germany. Adult patients with long-term indication for OAC received best practice case management in the intervention group. International normalized ratio (INR) values were recorded from anticoagulation passes. The Rosendaal method was used to calculate Time in Therapeutic Range (TTR) at patient level, and mean pooling to obtain center-specific TTR (cTTR) at practice level. The quality of OAC was assessed by TTR and cTTR. Linear model analyses were used to investigate associations between practice−/ patient-level factors and TTR.
Results: Inclusion of 736 patients (49.6% intervention and 50.4% control patients); 690 (93.8%) received phenprocoumon. Within 24 months, the TTR was 75.1% (SD 17.6) in the intervention versus 74.3% (SD 17.8) in the control group (p = 0.670). The cTTR averaged 75.1% (SD 6.5, range: 60.4 to 86.7%) in the intervention versus 74.3% (SD 7.2, range: 52.7 to 85.7%) in the control group (p = 0.668). At practice level, the TTR was significantly lower in practices with a male physician and certification in quality management. At patient level, the TTR was significantly higher in patients with moderate to high compliance, in men, and in patients that performed self-management. The TTR was significantly lower in patients with certain comorbidities, and who were hospitalized.
Conclusions: The intervention did not effectively improve OAC quality compared to routine care. Quality of INR control was generally good, but considerable variation existed between GP practices. The variability indicates optimization potential in some practices. The demonstrated association between patient-level factors and TTR highlights the importance of considering patient characteristics that may impede achieving high quality therapeutic outcomes.
Trial registration: ISRCTN registry, ISRCTN41847489, registered 27 February 2012.
Meeting Abstract : 10. Deutscher Kongress für Versorgungsforschung, 18. GAA-Jahrestagung. Deutsches Netzwerk Versorgungsforschung e. V. ; Gesellschaft für Arzneimittelanwendungsforschung und Arzneimittelepidemiologie e. V. 20.-22.10.2011, Köln
Hintergrund: Multimedikation als Folge von Multimorbidität ist ein zentrales Problem der Hausarztpraxis und erhöht das Risiko für unangemessene Arzneimittel-Verordnungen (VO). Um die Medikation bei älteren, multimorbiden Patienten zu optimieren und zu priorisieren, wurde eine computergestützte, durch Medizinische Fachangestellte (MFA) assistierte, komplexe Intervention (checklistengestütztes Vorbereitungsgespräch sowie Überprüfung eingenommener Medikamente durch MFA, Einsatz des web-basierten ArzneimittelinformationsDienstes AiD, spezifisches Arzt-Patienten-Gespräch) entwickelt und in einer 12-monatigen Pilotstudie auf Machbarkeit getestet. Ein auf 9 Items reduzierter MAI [1] wurde eingesetzt, um dessen Eignung als potentielles primäres Outcome der Hauptstudie zu prüfen.
Material und Methoden: In die Pilotstudie in 20 Hausarztpraxen mit Cluster-Randomisation auf Praxisebene in Kontrollgruppe (Regelversorgung b. empfohlenem Standard) vs. Interventionsgruppe (komplexe Intervention b. empfohlenem Standard) wurden 5 Pat./Praxis eingeschlossen (≥65 Jahre, ≥3 chron. Erkrankungen, ≥5 Dauermedikamente, MMSE ≥26, Lebenserwartung ≥6 Monate). Zur Bewertung des MAI wurden an Baseline (T0), 6 Wo. (T1) & 3 Mon. (T2) nach Intervention erhoben: VO, Diagnosen, Natrium, Kalium & Kreatinin i.S., Größe, Gewicht, Geschlecht, Cumulative Illness Rating Scale (CIRS) [2] durch die Hausarztpraxis; Symptome für unerwünschte Arzneimittelwirkungen im Patienten-Telefoninterview.
Für den MAI wurde die Angemessenheit jeder VO in den 9 Kategorien Indikation, Effektivität, Dosierung, korrekter & praktikabler Applikationsweg, Arzneimittelwechselwirkung, Drug-disease-Interaktion, Doppelverordnung, Anwendungsdauer 3-stufig bewertet (1 = korrekt - 3 = unkorrekt) und für die Auswertung auf Patientenebene summiert. Die Bewertung erfolgte ohne Kenntnis der Gruppenzugehörigkeit. Deskriptive Statistiken und Reliabilitätsanalysen, ungewichtete Auswertung und Gewichtung n. Bregnhoj [3].
Ergebnisse: Es wurden N=100 Patienten in die Studie eingeschlossen, im Mittel 76 Jahre (Standardabweichung, SD 6; Range, R: 64-93) , 52% Frauen, durchschnittlich 9 VO/Pat. (SD 2; R 4-16), mittlerer CIRS-Score 10 (SD 4; R 0-23). Basierend auf N=851 VO (100 Pat.) zu T0 betrug der Reliabilitätskoeffizient (RK, Cronbachs Alpha) der ungewichteten 9 Items 0,70. Items 1-5 wiesen akzeptable Trennschärfen auf (0,52-0,64), die der Items 6, 7 & 9 fielen mit 0,21-0,29 niedriger aus, die des Item 8 betrug 0,06. Auf der Basis der 9 gewichteten Items fiel die interne Konsistenz des MAI erwartet höher aus (0,75). Die Reliabilitätsanalysen auf VO-Ebene zeigten einen RK von 0,67 (ungewichtet) vs. 0,75 (gewichtet), die Trennschärfen waren vergleichbar. Zur Zwischenauswertung betrug der MAI (T1-T0) in der Interventionsgruppe (5 Praxen, 24 Pat.) -0,9 (SD 5,6), in der Kontrollgruppe (7 Praxen, 35 Pat.) -0,5 (SD 4,9); die Differenz zwischen beiden Gruppen Mi–Mk -0,4 [95% Konfidenzintervall: -3,4;2,6].
Schlussfolgerung: Der MAI ist als potentielles primäres Outcome in der Hauptstudie geeignet: wenige fehlende Werte, Darstellung von Unterschieden prä-post und zwischen den Gruppen, akzeptable interne Konsistenz. Der niedrige Trennschärfekoeffizient des Items 8 weist darauf hin, dass dieses Item nicht mit dem Gesamt-Skalenwert korreliert, auch die Items 6, 7 und 9 korrelieren wesentlich schwächer mit dem Gesamt-Skalenwert als die Items 1 bis 5. Eine Wichtung z.B. der Items 2, 5, 6 und 9 könnte erwogen werden, um den Fokus der Intervention in der Hauptzielgröße angemessen abzubilden.
Following publication of the data presented by von Minckwitz and colleagues it has been brought to our attention that some patients should be scored differently. Stable disease was seen in three of the eighteen patients instead of two of the eighteen patients: one patient with transitional cell carcinoma treated at 4 µg/kg scFv(FRP5)-ETA per day, and two breast cancer patients treated at 4 and 12.5 µg/kg scFv(FRP5)-ETA per day. Disease progression occured in 9 of the eighteen patients evaluated (see corrected Table 2 overleaf). This does not affect the conclusions of our study. In addition we would like to correct the following errors: patient IDs for patients U01 and U02 in the original Table 2 were interchanged. In addition, patient N03 had a grade 3 elevation of gamma-glutamyl transferase, and not grade 2 (see corrected Table 2 overleaf).
Background: Cumulative anticholinergic exposure, also known as anticholinergic burden, is associated with a variety of adverse outcomes. However, studies show that anticholinergic effects tend to be underestimated by prescribers, and anticholinergics are the most frequently prescribed potentially inappropriate medication in older patients. The grading systems and drugs included in existing scales to quantify anticholinergic burden differ considerably and do not adequately account for patients’ susceptibility to medications. Furthermore, their ability to link anticholinergic burden with adverse outcomes such as falls is unclear. This study aims to develop a prognostic model that predicts falls in older general practice patients, to assess the performance of several anticholinergic burden scales, and to quantify the added predictive value of anticholinergic symptoms in this context.
Methods: Data from two cluster-randomized controlled trials investigating medication optimization in older general practice patients in Germany will be used. One trial (RIME, n = 1,197) will be used for the model development and the other trial (PRIMUM, n = 502) will be used to externally validate the model. A priori, candidate predictors will be selected based on a literature search, predictor availability, and clinical reasoning. Candidate predictors will include socio-demographics (e.g. age, sex), morbidity (e.g. single conditions), medication (e.g. polypharmacy, anticholinergic burden as defined by scales), and well-being (e.g. quality of life, physical function). A prognostic model including sociodemographic and lifestyle-related factors, as well as variables on morbidity, medication, health status, and well-being, will be developed, whereby the prognostic value of extending the model to include additional patient-reported symptoms will be also assessed. Logistic regression will be used for the binary outcome, which will be defined as “no falls” vs. “≥1 fall” within six months of baseline, as reported in patient interviews. Discussion: As the ability of different anticholinergic burden scales to predict falls in older patients is unclear, this study may provide insights into their relative importance as well as into the overall contribution of anticholinergic symptoms and other patient characteristics. The results may support general practitioners in their clinical decision-making and in prescribing fewer medications with anticholinergic properties.
Background: Unwanted anticholinergic effects are both underestimated and frequently overlooked. Failure to identify adverse drug reactions (ADRs) can lead to prescribing cascades and the unnecessary use of over-thecounter products. The objective of this systematic review and meta-analysis is to explore and quantify the frequency and severity of ADRs associated with amitriptyline vs. placebo in randomized controlled trials (RCTs) involving adults with any indication, as well as healthy individuals. Methods: A systematic search in six electronic databases, forward/backward searches, manual searches, and searches for Food and Drug Administration (FDA) and European Medicines Agency (EMA) approval studies, will be performed. Placebo-controlled RCTs evaluating amitriptyline in any dosage, regardless of indication and without restrictions on the time and language of publication, will be included, as will healthy individuals. Studies of topical amitriptyline, combination therapies, or including <100 participants, will be excluded. Two investigators will screen the studies independently, assess methodological quality, and extract data on design, population, intervention, and outcomes ((non-)anticholinergic ADRs, e.g., symptoms, test results, and adverse drug events (ADEs) such as falls). The primary outcome will be the frequency of anticholinergic ADRs as a binary outcome (absolute number of patients with/without anticholinergic ADRs) in amitriptyline vs. placebo groups. Anticholinergic ADRs will be defined by an experienced clinical pharmacologist, based on literature and data from Martindale: The Complete Drug Reference. Secondary outcomes will be frequency and severity of (non-)anticholinergic ADRs and ADEs. The information will be synthesized in meta-analyses and narratives. We intend to assess heterogeneity using metaregression (for indication, outcome, and time points) and I2 statistics. Binary outcomes will be expressed as odds ratios, and continuous outcomes as standardized mean differences. Effect measures will be provided using 95% confidence intervals. We plan sensitivity analyses to assess methodological quality, outcome reporting etc., and subgroup analyses on age, dosage, and duration of treatment. Discussion: We will quantify the frequency of anticholinergic and other ADRs/ADEs in adults taking amitriptyline for any indication by comparing rates for amitriptyline vs. placebo, hence, preventing bias from disease symptoms and nocebo effects. As no standardized instrument exists to measure it, our overall estimate of anticholinergic ADRs may have limitations.