Quantifying statistical uncertainty in metrics of sleep disordered breathing.
Quantifying statistical uncertainty in metrics of sleep disordered breathing.
复制标题
量化睡眠呼吸障碍指标的统计不确定性。
DOI：
10.1016/j.sleep.2019.06.003
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发表时间：
2020
期刊：
影响因子：
4.8
通讯作者：
Prerau,MichaelJ
中科院分区：
文献类型：
--
作者：
Thomas,RobertJ;Chen,Shuqiang;Eden,UriT;Prerau,MichaelJ
背景呼吸暂停低通气指数(AHI)(或其衍生指标)是描述睡眠呼吸障碍的主要临床指标，其相对于阈值的值决定了诊断的严重程度和是否有资格获得治疗补偿。然而，指标值被视为完美的点估计，不能衡量统计上的不确定性。因此，目前的做法不能很好地解释由于偶然而导致的诊断/合格性的差异。在本文中，我们量化了与睡眠呼吸障碍呼吸事件指数相关的统计不确定性，以及不确定性对治疗合格性的影响。方法我们使用非参数Bootstrap对事件间隔时间进行不确定性的经验估计，以及反映当前AHI公式的理论泊松估计。结果与结论平均95%经验可信区间宽度为每小时11.500±6.208次事件/小时，平均95%泊松可信区间宽度为每小时5.998±2.897次事件/小时，提示不确定性可能是当前诊断框架内的主要混淆因素。在有症状人群(ESS>；10)中的278名受试者中，27%(76/278)在95%的经验可信区间内有不确定的诊断。在全人群中的2049名受试者中，43%(880/2049)的人在95%的经验可信区间内有不确定的诊断。纳入不确定诊断的受试者使符合条件的患者数量在有症状的人群中增加了21.3%，在全体人群中增加了84.8%。排除不确定诊断的受试者，在95%的经验可信区间内，符合条件的患者数量在有症状的人群中减少了12.4%，在总体人群中减少了34.8%。其他分析表明，通过对范围广泛的边缘病例进行额外测试来获得诊断统计学意义实际上是不可行的。总体而言，这些结果表明，AHI的不确定性是一项重要的额外信息，将极大地有益于临床实践，将不确定性纳入流行病学分析可能有助于提高研究人员将AHI与合并症和长期结果强有力地联系起来的能力。
BackgroundThe apnea-hypopnea index (AHI) (or one of its derivatives) is the primary clinical metric for characterizing sleep disordered breathing—the value of which with respect to a threshold determines severity of diagnosis and eligibility for treatment reimbursement. The index value, however, is taken as a perfect point estimate, with no measure of statistical uncertainty. Thus, current practice does not robustly account for variability in diagnosis/eligibility due to chance. In this paper, we quantify the statistical uncertainty associated with respiratory event indices for sleep disordered breathing and the effect of uncertainty on treatment eligibility.MethodsWe develop an empirical estimate of uncertainty using a non-parametric bootstrap on the interevent times, as well as a theoretical Poisson estimate reflecting the current formulation of the AHI. We then apply these methods to estimate AHI uncertainty for 2049 subjects (954/1095 M/F, age: mean 69 ± 9.1) from the Multi-Ethnic Study of Atherosclerosis (MESA).Results and ConclusionsThe mean 95% empirical confidence interval width was 11.500 ± 6.208 events per hour and the mean 95% theoretical Poisson confidence interval width was 5.998 ± 2.897 events per hour, suggesting that uncertainty is likely a major confounding factor within the current diagnostic framework. Of the 278 subjects in the symptomatic population (ESS>10), 27% (76/278) had uncertain diagnoses given the 95% empirical confidence interval. Of the 2049 subjects in the full population, 43% (880/2049) had uncertain diagnoses given the 95% empirical confidence interval. The inclusion of subjects with uncertain diagnoses increases the number of eligible patients by 21.3% for the symptomatic population and by 84.8% for the full population. The exclusion of subjects with uncertain diagnoses given the 95% empirical confidence interval decreases the number of eligible patients by 12.4% for the symptomatic population and by 34.8% for full population. Additional analyses suggest that it is practically infeasible to gain diagnostic statistical significance through additional testing for a broad range of borderline cases. Overall, these results suggest that AHI uncertainty is a vital additional piece of information that would greatly benefit clinical practice, and that the inclusion of uncertainty in epidemiological analysis might help improve the ability for researchers to robustly link AHI with co-morbidities and long-term outcomes.
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影响因子：
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