Department of Pharmaceutical and Administrative Sciences, University of Health Sciences and Pharmacy, St. Louis, MO, USA.
School of Pharmacy, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.
Age Ageing. 2023 Sep 1;52(9). doi: 10.1093/ageing/afad167.
Long-term opioid use and associated adverse outcomes have increased dramatically in recent years. Limited research is available on long-term opioid use in older adults.
We aimed to determine the incidence and predictors of long-term or persistent opioid use (POU) amongst opioid-naïve older adults without a cancer diagnosis.
This was a retrospective cohort study using five national administrative healthcare databases in New Zealand. We included all opioid-naïve older adults (≥65 years) who were initiated on opioid therapy between January 2013 and June 2018. The outcome of interest was POU, defined as having continuously filled ≥1 opioid prescription within 91-180 days after the index opioid prescription. Multivariable logistic regression was used to examine the predictors of POU.
The final sample included 268,857 opioid-naïve older adults; of these, 5,849(2.2%) developed POU. Several predictors of POU were identified. The use of fentanyl (adjusted odds ratio (AOR) = 3.61; 95% confidence interval (CI) 2.63-4.95), slow-release opioids (AOR = 3.02; 95%CI 2.78-3.29), strong opioids (AOR = 2.03; 95%CI 1.55-2.65), Charlson Comorbidity Score ≥ 3 (AOR = 2.09; 95% CI 1.78-2.46), history of substance abuse (AOR = 1.52; 95%CI 1.35-1.72), living in most socioeconomically deprived areas (AOR = 1.40; 95%CI 1.27-1.54), and anti-epileptics (AOR = 2.07; 95%CI 1.89-2.26), non-opioid analgesics (AOR = 2.05; 95%CI 1.89-2.21), antipsychotics (AOR = 1.96; 95%CI 1.78-2.17) or antidepressants (AOR = 1.50; 95%CI 1.41-1.59) medication use were the strongest predictors of POU.
A significant proportion of patients developed POU, and several factors were associated with POU. The findings will enable healthcare providers and policymakers to target early interventions to prevent POU and related adverse events.
近年来，长期使用阿片类药物及其相关不良后果显著增加。针对老年人长期使用阿片类药物的研究有限。
本研究旨在确定无癌症诊断的老年阿片类药物初治患者中，长期或持续使用阿片类药物（POU）的发生率和预测因素。
这是一项在新西兰五个国家行政医疗保健数据库中进行的回顾性队列研究。我们纳入了所有在 2013 年 1 月至 2018 年 6 月期间开始使用阿片类药物治疗的阿片类药物初治老年人（≥65 岁）。主要结局是 POU，定义为在开具阿片类药物处方后的 91-180 天内持续连续开处≥1 张阿片类药物处方。多变量逻辑回归用于研究 POU 的预测因素。
最终纳入 268857 名阿片类药物初治老年人；其中 5849 名（2.2%）发展为 POU。确定了几个 POU 的预测因素。使用芬太尼（调整优势比（AOR）=3.61；95%置信区间（CI）2.63-4.95）、缓释阿片类药物（AOR=3.02；95%CI 2.78-3.29）、强阿片类药物（AOR=2.03；95%CI 1.55-2.65）、Charlson 合并症评分≥3（AOR=2.09；95%CI 1.78-2.46）、药物滥用史（AOR=1.52；95%CI 1.35-1.72）、居住在最贫困的社会经济地区（AOR=1.40；95%CI 1.27-1.54）、抗癫痫药（AOR=2.07；95%CI 1.89-2.26）、非阿片类镇痛药（AOR=2.05；95%CI 1.89-2.21）、抗精神病药（AOR=1.96；95%CI 1.78-2.17）或抗抑郁药（AOR=1.50；95%CI 1.41-1.59）的使用是 POU 的最强预测因素。
相当一部分患者发展为 POU，且多种因素与 POU 相关。研究结果将使医疗保健提供者和决策者能够针对早期干预措施，以预防 POU 和相关不良事件。
