Variability in the Prescription of Cholinesterase Inhibitors and Memantine

Villar-Fernández, I.; Bjerrum, Lars; Feja, Cristina; Rabanaque, María José

doi:10.1159/000253845

Cited by 13 publications

(4 citation statements)

References 39 publications

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“…These were not included as features in the cluster definition but only used for validation purposes. The five outcomes were: Length of time on Cholinesterase inhibitors: defined was length of time on cholinesterase inhibitors, as cholinesterase inhibitors (ChEI) are the most common type of drug prescribed for AD [ 48 ]. It is typically prescribed at the mild to moderate stage of AD [ 49 ] but is discontinued when the drugs are no longer beneficial to the patient.…”

Section: Methodsmentioning

confidence: 99%

Identifying and evaluating clinical subtypes of Alzheimer’s disease in care electronic health records using unsupervised machine learning

Alexander

Barkhof

et al. 2021

BMC Med Inform Decis Mak

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Background Alzheimer’s disease (AD) is a highly heterogeneous disease with diverse trajectories and outcomes observed in clinical populations. Understanding this heterogeneity can enable better treatment, prognosis and disease management. Studies to date have mainly used imaging or cognition data and have been limited in terms of data breadth and sample size. Here we examine the clinical heterogeneity of Alzheimer's disease patients using electronic health records (EHR) to identify and characterise disease subgroups using multiple clustering methods, identifying clusters which are clinically actionable. Methods We identified AD patients in primary care EHR from the Clinical Practice Research Datalink (CPRD) using a previously validated rule-based phenotyping algorithm. We extracted and included a range of comorbidities, symptoms and demographic features as patient features. We evaluated four different clustering methods (k-means, kernel k-means, affinity propagation and latent class analysis) to cluster Alzheimer’s disease patients. We compared clusters on clinically relevant outcomes and evaluated each method using measures of cluster structure, stability, efficiency of outcome prediction and replicability in external data sets. Results We identified 7,913 AD patients, with a mean age of 82 and 66.2% female. We included 21 features in our analysis. We observed 5, 2, 5 and 6 clusters in k-means, kernel k-means, affinity propagation and latent class analysis respectively. K-means was found to produce the most consistent results based on four evaluative measures. We discovered a consistent cluster found in three of the four methods composed of predominantly female, younger disease onset (43% between ages 42–73) diagnosed with depression and anxiety, with a quicker rate of progression compared to the average across other clusters. Conclusion Each clustering approach produced substantially different clusters and K-Means performed the best out of the four methods based on the four evaluative criteria. However, the consistent appearance of one particular cluster across three of the four methods potentially suggests the presence of a distinct disease subtype that merits further exploration. Our study underlines the variability of the results obtained from different clustering approaches and the importance of systematically evaluating different approaches for identifying disease subtypes in complex EHR.

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Section: Methodsmentioning

confidence: 99%

Identifying and evaluating clinical subtypes of Alzheimer’s disease in care electronic health records using unsupervised machine learning

Alexander

Barkhof

et al. 2021

BMC Med Inform Decis Mak

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“…In other west-European countries, the therapy rate is considerably higher: 53% in Spain [19], 46% in Ireland, 47% in Sweden and 50% in France and Finland [16,20]. In east-European countries, the treatment rate is considerably lower, for example in the Czech Republic 9% and Bulgaria 6% [16].…”

Section: Introductionmentioning

confidence: 99%

Effects of general practitioner training and family support services on the care of home-dwelling dementia patients - Results of a controlled cluster-randomized study

Donath

Gräßel

Großfeld-Schmitz

et al. 2010

BMC Health Serv Res

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BackgroundMore than 90% of dementia patients are cared for by their general practitioners, who are decisively involved in the diagnosis, therapy and recommendation of support services. Objective: To test whether special training of general practitioners alters the care of dementia patients through their systematic recommendation of caregiver counseling and support groups.Method129 general practitioners enrolled 390 dementia patients and their informal caregivers in a prospective, three-arm cluster-randomized 2-year study. Arm A constituted usual care, in Arm B and C support groups and caregiver counseling (in Arm B one year after baseline, in Arm C at baseline) were recommended by the general practitioners. The general practitioners received arm-specific training. Diagnostic and therapeutic behavior of physicians was recorded at baseline. Informal caregivers were questioned in follow-up after 2 years about the utilization of support services.ResultsThe diagnostic behavior of the general practitioners conforms to relevant guidelines. The procedure in newly-diagnosed patients does not differ from previously diagnosed patients with the exception of the rate of referral to a specialist. About one-third of the newly-diagnosed dementia patients are given an anti-dementia drug. The utilization of support groups and counseling increased five- and fourfold, respectively. Utilization of other support services remained low (< 10%), with the exception of home nursing and institutional short-term nursing.ConclusionTrained general practitioners usually act in conformity with guidelines with respect to diagnosing dementia, and partly in conformity with the guidelines with respect to recommended drug therapy. Recommendations of support services for informal caregivers by the general practitioner are successful. They result in a marked increase in the utilization rate for the recommended services compared to offers which are not recommended by the general practitioner.Trial registrationISRCTN68329593

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“…Como fortalezas, destacamos que la base de datos analizada en el presente estudio, Farmasalud ha sido utilizada en otros estudios previos (37)(38)(39)(40), constituyendo una herramienta válida y con una buena calidad de registro. Del mismo modo, queremos subrayar el hecho de que no existan estudios recientes en España sobre la utilización de AINE y otros fármacos relacionados con el tratamiento de las EME.…”

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Consumo de fármacos utilizados en el tratamiento del dolor musculoesquético en una cohorte de trabajadores manuales de Zaragoza

Calvo

Álvarez

Malo

2020

Rev. Soc. Esp. Dolor.

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Variability in the Prescription of Cholinesterase Inhibitors and Memantine

Cited by 13 publications

References 39 publications

Identifying and evaluating clinical subtypes of Alzheimer’s disease in care electronic health records using unsupervised machine learning

Identifying and evaluating clinical subtypes of Alzheimer’s disease in care electronic health records using unsupervised machine learning

Effects of general practitioner training and family support services on the care of home-dwelling dementia patients - Results of a controlled cluster-randomized study

Consumo de fármacos utilizados en el tratamiento del dolor musculoesquético en una cohorte de trabajadores manuales de Zaragoza

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