Gómez-Gómez Carmen, Moya-Molina Miguel Ángel, Tey-Aguilera Manuel Jesús, Flores-Azofra Jorge, González-Caballero Juan Luis
Department of Biochemistry and Molecular Biology, School of Medicine, University of Cadiz, 11002 Cádiz, Spain.
Department of Neurology, Hospital Universitario Puerta del Mar (HUPM), University of Cadiz, 11009 Cádiz, Spain.
Healthcare (Basel). 2023 Aug 7;11(15):2219. doi: 10.3390/healthcare11152219.
Polypharmacy has been linked to cognitive decline. However, interventions targeting modifiable risk factors, some of which are targets of the most commonly used drugs, could reduce the prevalence of dementia. Our aim was to determine the drug prescription regimen at baseline, prior to the diagnosis of mild cognitive impairment (MCI), and its possible association with progression to dementia. Data were collected from the electronic medical records of 342 MCI outpatients diagnosed during 2006-2017 at their first neurology consultation. We followed the classical three-step method of statistical analysis, starting with a Latent Class Analysis (LCA) to discover subgroups of drug prescription probability. Half of the patients were under polypharmacy (≥5 drugs), 17.5% had no recorded medication, 33.3% progressed to dementia (94.7% in ≤5 years), and 84.1% of them to Alzheimer's disease (AD). According to the LCA and based on 20 therapeutic indicators obtained from 240 substances and regrouped according the Anatomical Therapeutic Chemical Classification, we identified a four-profile model: (1) low (35.7% of patients); (2) mixed (28.7%); (3) cardio-metabolic (19.3%); and (4) psychotropic (16.4%). The binomial regression logistic model showed that profiles 2 and 3 (and 4 for AD), with a higher drug prescription conditioned probability against classic risk factors, were protective than profile 1 (OR = 0.421, = 0.004; OR = 0.278, = 0.000; OR = 0.457, = 0.040, respectively), despite polypharmacy being significant in profiles 2 and 3 (mean > 7 drugs) vs. profile 1 (1.4 ± 1.6) ( = 0.000). Patients in the latter group were not significantly older, although being aged 65-79 years old quadrupled (OR = 4.217, = 000) and being >79 tripled (OR = 2.945, = 0.010) the conversion risk compared to patients <65 years old. According to the proposed analytical model, profiling the heterogeneous association of risk factors, which were taken prior to diagnosis, could be explored as an indicator of prior care and a predictor of conversion to dementia.
多重用药与认知能力下降有关。然而，针对可改变的风险因素进行干预，其中一些是最常用药物的靶点，可能会降低痴呆症的患病率。我们的目的是确定在轻度认知障碍（MCI）诊断之前基线时的药物处方方案，及其与进展为痴呆症的可能关联。数据收集自2006年至2017年期间在首次神经科会诊时被诊断为MCI的342名门诊患者的电子病历。我们遵循经典的三步统计分析方法，首先进行潜在类别分析（LCA）以发现药物处方概率的亚组。一半的患者接受多重用药（≥5种药物），17.5%没有用药记录，33.3%进展为痴呆症（94.7%在≤5年内），其中84.1%进展为阿尔茨海默病（AD）。根据LCA并基于从240种物质中获得并根据解剖治疗化学分类重新分组的20个治疗指标，我们确定了一个四分类模型：（1）低（35.7%的患者）；（2）混合（28.7%）；（3）心脏代谢（19.3%）；和（4）精神药物（16.4%）。二项式回归逻辑模型显示，与经典风险因素相比，具有较高药物处方条件概率的第2类和第3类（AD为第4类）比第1类具有保护作用（OR = 0.421，P = 0.004；OR = 0.278，P = 0.000；OR = 0.457，P = 0.040），尽管第2类和第3类中的多重用药情况（平均>7种药物）与第1类（1.4±1.6）相比具有显著性（P = 0.000）。后一组患者年龄并没有显著更大，尽管65 - 79岁的患者与<65岁的患者相比，转化风险增加了四倍（OR = 4.217，P = 0.000），>79岁的患者增加了两倍（OR = 2.945，P = 0.010）。根据所提出的分析模型，对诊断前采用的风险因素的异质关联进行分类，可作为前期护理的指标和转化为痴呆症的预测指标进行探索。
