Division of Respiratory therapy, Department of Chest Medicine, Taipei Veterans General Hospital, No. 201, Sec. 2, Shih-Pai Road, Taipei 112, Taiwan, Republic of China.
School of Respiratory Therapy, Taipei Medical University, Taipei, Taiwan, Republic of China.
NPJ Prim Care Respir Med. 2017 Oct 16;27(1):59. doi: 10.1038/s41533-017-0060-8.
Life-long smoking cessation is a critical public health objective, but it is difficult for numerous people. This study aimed to identify the independent predictors of 1-year abstinence in smokers motivated to quit and participating in an intervention program. This 6-year retrospective observational cohort study was conducted in smokers who participated in an intervention program. The exhaled carbon monoxide (CO) was sequentially measured on day 1, 8, 15, and 22 of the intervention program. The primary outcome measure was smoking status at 1 year of follow-up. A total of 162 participants were enrolled and divided into a successful quit group (n = 52) and unsuccessful quit group (n = 110). Using a multivariate logistic regression analysis, we reported that the intention to quit (adjusted odds ratio [AOR] = 1.475, 95% confidence interval [CI] = 1.169-1.862, P-value = 0.001), varenicline use (AOR = 3.199, 95% CI = 1.290-7.934, P -value = 0.012) and the exhaled CO level on day 8 (AOR = 0.937, 95% CI = 0.885-0.992, P-value = 0.025) independently predicted 1-year smoking cessation. Moreover, the level of exhaled CO < 4.5 parts per million on day 8 significantly predict successful 1-year smoking cessation (area under curve 0.761, sensitivity 88.2%, and specificity 57.8%, P-value < 0.001). These independent predictors including intention to quit, varenicline use, and exhaled CO level on day 8, may help primary care physicians rearrange resources and refine the strategies for intervention programs to achieve a higher rate of long-term smoking cessation.
IDENTIFYING PREDICTORS OF SUCCESS: Researchers in Korea identify key predictors that pinpoint people most likely to quit smoking successfully during intervention programs. Millions are spent each year supporting people to quit smoking. However, successful quitters remain in the minority, with only 9-35 per cent of those in intervention programs abstaining for at least a year. Hsin-Kuo Ko at Taipei Veterans General Hospital and co-workers identified key independent indicators of successful abstinence in 162 smokers attending an intervention program. Alongside having a high intention to quit and using varenicline medication, a potential predictor is having an exhaled carbon monoxide (CO) level of less than 4.5 parts-per-million by day 8 of the course. Exhaled CO is higher in smokers than in non-smokers. Measuring CO levels one week into courses may be a useful biomarker to identify those fully committed to quit.
识别有戒烟意愿并参与干预项目的吸烟者中，1 年戒烟的独立预测因素。
这是一项为期 6 年的回顾性观察队列研究，在参与干预项目的吸烟者中进行。在干预项目的第 1、8、15 和 22 天，连续测量呼出的一氧化碳（CO）。主要观察指标为随访 1 年时的吸烟状况。共纳入 162 名参与者，分为成功戒烟组（n=52）和不成功戒烟组（n=110）。采用多变量逻辑回归分析，报告显示戒烟意愿（调整优势比[OR] = 1.475，95%置信区间[CI] = 1.169-1.862，P 值 = 0.001）、使用伐尼克兰（OR = 3.199，95%CI = 1.290-7.934，P 值 = 0.012）和第 8 天的呼出 CO 水平（OR = 0.937，95%CI = 0.885-0.992，P 值 = 0.025）独立预测 1 年戒烟。此外，第 8 天呼出 CO 水平<4.5ppm 可显著预测 1 年成功戒烟（曲线下面积 0.761，灵敏度 88.2%，特异性 57.8%，P 值 < 0.001）。这些独立的预测因素包括戒烟意愿、伐尼克兰的使用以及第 8 天的呼出 CO 水平，这可能有助于初级保健医生重新安排资源，完善干预项目的策略，以提高长期戒烟的成功率。
确定成功的预测因素：韩国的研究人员确定了关键的预测因素，可以确定在干预计划中最有可能成功戒烟的人。每年都有数百万人的资源用于支持人们戒烟。然而，成功戒烟者仍属少数，只有 9-35%的干预计划参与者至少坚持一年不吸烟。台北荣民总医院的 Hsin-Kuo Ko 及其同事在 162 名参加干预计划的吸烟者中确定了成功戒烟的关键独立指标。除了有强烈的戒烟意愿和使用伐尼克兰药物外，另一个潜在的预测因素是在疗程第 8 天呼出的一氧化碳（CO）水平低于 4.5ppm。吸烟者呼出的 CO 比不吸烟者高。在课程的第一周测量 CO 水平可能是一种有用的生物标志物，可以识别那些完全有意愿戒烟的人。
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