TB Centre, Department of Infectious Disease Epidemiology, London, School of Hygiene & Tropical Medicine (LSHTM) , London, UK.
Bristol Medical School, Population Health Sciences, Bristol, UK.
BMC Public Health. 2023 Oct 14;23(1):2006. doi: 10.1186/s12889-023-16905-z.
Non-adherence to tuberculosis treatment increases the risk of poor treatment outcomes. Digital adherence technologies (DATs), including the smart pillbox (EvriMED), aim to improve treatment adherence and are being widely evaluated. As part of the Adherence Support Coalition to End TB (ASCENT) project we analysed data from a cluster-randomised trial of DATs and differentiated care in Ethiopia to examine individual-factors for poor engagement with the smart pillbox.
Data were obtained from a cohort of trial participants with drug-sensitive tuberculosis (DS-TB) whose treatment started between 1 December 2020 and 1 May 2022, and who were using the smart pillbox. Poor engagement with the pillbox was defined as (i) > 20% days with no digital confirmation and (ii) the count of days with no digital confirmation, and calculated over a two evaluation periods (56-days and 168-days). Logistic random effects regression was used to model > 20% days with no digital confirmation and negative binomial random effects regression to model counts of days with no digital confirmation, both accounting for clustering of individuals at the facility-level.
Among 1262 participants, 10.8% (133/1262) over 56-days and 15.8% (200/1262) over 168-days had > 20% days with no digital confirmation. The odds of poor engagement was less among participants in the higher stratum of socio-economic position (SEP) over 56-days. Overall, 4,689/67,315 expected doses over 56-days and 18,042/199,133 expected doses over 168-days were not digitally confirmed. Compared to participants in the poorest SEP stratum, participants in the wealthiest stratum had lower rates of days not digitally confirmed over 168-days (adjusted rate ratio [RR]:0.79; 95% confidence interval [CI]: 0.65, 0.96). In both evaluation periods (56-days and 168-days), HIV-positive status (RR:1.29; 95%CI: 1.02, 1.63 and RR:1.28; 95%CI: 1.07, 1.53), single/living independent (RR:1.31; 95%CI: 1.03, 1.67 and RR:1.38; 95%CI: 1.16, 1.64) and separated/widowed (RR:1.40; 95%CI: 1.04, 1.90 and RR:1.26; 95%CI: 1.00, 1.58) had higher rates of counts of days with no digital confirmation.
Poorest SEP stratum, HIV-positive status, single/living independent and separated/ widowed were associated with poor engagement with smart pillbox among people with DS-TB in Ethiopia. Differentiated care for these sub-groups may reduce risk of non-adherence to TB treatment.
结核病治疗不依从会增加治疗效果不佳的风险。数字依从技术（DATs），包括智能药盒（EvriMED），旨在提高治疗依从性，并正在广泛评估。作为结束结核支持联盟（ASCENT）项目的一部分，我们分析了埃塞俄比亚 DATs 和差异化护理的一项集群随机试验的数据，以检查与智能药盒不依从的个体因素。
数据来自 2020 年 12 月 1 日至 2022 年 5 月 1 日开始接受药物敏感型肺结核（DS-TB）治疗并使用智能药盒的试验参与者队列。将药盒的不良使用定义为（i）＞20%天没有数字确认和（ii）无数字确认天数的计数，并在两个评估期（56 天和 168 天）进行计算。使用逻辑随机效应回归模型对＞20%天无数字确认进行建模，使用负二项随机效应回归模型对无数字确认天数的计数进行建模，两者均考虑到个体在设施层面的聚类。
在 1262 名参与者中，56 天时有 10.8%（133/1262）和 168 天时有 15.8%（200/1262）＞20%天无数字确认。在较高社会经济地位（SEP）阶层的参与者中，不良使用的可能性较低。总体而言，56 天期间有 4689/67315 个预期剂量和 168 天期间有 18042/199133 个预期剂量未被数字确认。与最贫穷的 SEP 阶层的参与者相比，最富裕阶层的参与者在 168 天期间无数字确认天数的比率较低（调整后的比率比 [RR]：0.79；95%置信区间 [CI]：0.65，0.96）。在两个评估期（56 天和 168 天）中，艾滋病毒阳性状态（RR：1.29；95%CI：1.02，1.63 和 RR：1.28；95%CI：1.07，1.53）、单身/独立居住（RR：1.31；95%CI：1.03，1.67 和 RR：1.38；95%CI：1.16，1.64）和离异/丧偶（RR：1.40；95%CI：1.04，1.90 和 RR：1.26；95%CI：1.00，1.58）与 DS-TB 患者使用智能药盒不良使用的天数计数较高有关。为这些亚组提供差异化护理可能会降低结核病治疗不依从的风险。
