Lapi Francesco, Marconi Ettore, Aprile Pierangelo Lora, Magni Alberto, Vetrano Davide Liborio, Rossi Alessandro, Pilotto Alberto, Cricelli Claudio
Health Search, Italian College of General Practitioners and Primary Care, Via del Sansovino 179, 50142, Florence, Italy.
Italian College of General Practitioners and Primary Care, Florence, Italy.
Eur Geriatr Med. 2025 Apr;16(2):583-603. doi: 10.1007/s41999-024-01098-4. Epub 2024 Dec 19.
To assess and compare, through a retrospective cohort study, the relationships between frailty, comorbidity, multimorbidity, and levels of adherence to lipid-lowering drugs (LLDs), antihypertensives and antidepressants.
In a primary care database, we selected a cohort of patients aged 60 or older on December 31, 2022. The date of the first prescription of the aforementioned medications was the study index date. Patients with Variable Medication Possession Ratio (VMPR) > = 80% were classified as properly adherent. Frailty (i.e. Primary Care-Frailty Index), comorbidity (i.e. Charlson Index) and multimorbidity (i.e. disease counts) alternatively entered multivariate logistic regressions along with age and sex. Models' performances in prediction of medications adherence were compared in terms of information (AIC; BIC) and discrimination values (AUC).
Incident users of LLDs, antihypertensives or antidepressants were 4310 (mean age: 67.9 (SD: 6.9); 56.0% females), 5969 (mean age: 69.1 (SD: 7.6); 58.0% females), and 3834 (mean age: 68.7 (SD: 6.9); 66.5% females), respectively. Among users of LLDs (46% adherent) and antidepressants (22% adherent), those who were moderately or severely frail showed a significant 30-32% decrease in adherence. In contrast, users of antihypertensives (46% adherent) showed a 41% increase in adherence when multimorbid. As a whole, the three multivariate models were equally effective in informing on medication adherence, as per AIC and BIC. They also displayed similar discriminatory ability, with AUC scores ranging from 53 to 58%. Regarding the workload of GPs, the number of elderly patients classified as moderately/high frail was less than those with co-morbidities or multimorbidities. For instance, there were approximately 35 users of antihypertensive medications per GP for the moderately frail group, compared to 46 and 66 for the co-morbid and multi-morbid groups, respectively.
These findings showed similar capacity for frailty, comorbidity, and multimorbidity in capturing medications adherence. Given the existence of a validated tool in primary care that aligns well with GPs' workload, frailty seems the most suitable measure for assessing the complexity of older adults in relation to their adherence to long-term medications.
通过一项回顾性队列研究,评估并比较虚弱、共病、多病共存与降脂药物(LLD)、抗高血压药物和抗抑郁药物依从性水平之间的关系。
在一个初级保健数据库中,我们选取了2022年12月31日年龄在60岁及以上的患者队列。上述药物首次处方日期为研究索引日期。可变药物持有率(VMPR)>=80%的患者被归类为依从性良好。虚弱(即初级保健虚弱指数)、共病(即查尔森指数)和多病共存(即疾病计数)与年龄和性别一起交替纳入多变量逻辑回归。根据信息(AIC;BIC)和判别值(AUC)比较模型在预测药物依从性方面的表现。
LLD、抗高血压药物或抗抑郁药物的新使用者分别为4310人(平均年龄:67.9(标准差:6.9);56.0%为女性)、5969人(平均年龄:69.1(标准差:7.6);58.0%为女性)和3834人(平均年龄:68.7(标准差:6.9);66.5%为女性)。在LLD使用者(46%依从)和抗抑郁药物使用者(22%依从)中,中度或重度虚弱者的依从性显著降低30 - 32%。相比之下,抗高血压药物使用者(46%依从)在多病共存时依从性提高了41%。总体而言,根据AIC和BIC,这三个多变量模型在告知药物依从性方面同样有效。它们还表现出相似的判别能力,AUC分数在53%至58%之间。关于全科医生的工作量,被归类为中度/高度虚弱的老年患者数量少于患有共病或多病共存的患者。例如,中度虚弱组每位全科医生大约有35名抗高血压药物使用者,而共病组和多病共存组分别为46名和66名。
这些发现表明,虚弱、共病和多病共存捕捉药物依从性的能力相似。鉴于初级保健中有一个经过验证且与全科医生工作量匹配良好的工具,虚弱似乎是评估老年人长期用药依从性复杂性的最合适指标。