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气道正压滴定诱发中枢性睡眠呼吸暂停的临床预测因素

Clinical predictors of central sleep apnea evoked by positive airway pressure titration.

作者信息

Moro Marilyn, Gannon Karen, Lovell Kathy, Merlino Margaret, Mojica James, Bianchi Matt T

机构信息

Neurology Department.

Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA.

出版信息

Nat Sci Sleep. 2016 Jul 27;8:259-66. doi: 10.2147/NSS.S110032. eCollection 2016.

Abstract

PURPOSE

Treatment-emergent central sleep apnea (TECSA), also called complex apnea, occurs in 5%-15% of sleep apnea patients during positive airway pressure (PAP) therapy, but the clinical predictors are not well understood. The goal of this study was to explore possible predictors in a clinical sleep laboratory cohort, which may highlight those at risk during clinical management.

METHODS

We retrospectively analyzed 728 patients who underwent PAP titration (n=422 split-night; n=306 two-night). Demographics and self-reported medical comorbidities, medications, and behaviors as well as standard physiological parameters from the polysomnography (PSG) data were analyzed. We used regression analysis to assess predictors of binary presence or absence of central apnea index (CAI) ≥5 during split-night PSG (SN-PSG) versus full-night PSG (FN-PSG) titrations.

RESULTS

CAI ≥5 was present in 24.2% of SN-PSG and 11.4% of FN-PSG patients during titration. Male sex, maximum continuous positive airway pressure, and use of bilevel positive airway pressure were predictors of TECSA, and rapid eye movement dominance was a negative predictor, for both SN-PSG and FN-PSG patients. Self-reported narcotics were a positive predictor of TECSA, and the time spent in stage N2 sleep was a negative predictor only for SN-PSG patients. Self-reported history of stroke and the CAI during the diagnostic recording predicted TECSA only for FN-PSG patients.

CONCLUSION

Clinical predictors of treatment-evoked central apnea spanned demographic, medical history, sleep physiology, and titration factors. Improved predictive models may be increasingly important as diagnostic and therapeutic modalities move away from the laboratory setting, even as PSG remains the gold standard for characterizing primary central apnea and TECSA.

摘要

目的

治疗引发的中枢性睡眠呼吸暂停(TECSA),也称为复杂性呼吸暂停,在5%-15%的睡眠呼吸暂停患者接受气道正压通气(PAP)治疗期间出现,但临床预测因素尚不明确。本研究的目的是在临床睡眠实验室队列中探索可能的预测因素,这可能会突出临床管理过程中处于风险的人群。

方法

我们回顾性分析了728例接受PAP滴定的患者(n=422例分夜滴定;n=306例两夜滴定)。分析了人口统计学、自我报告的合并症、药物和行为以及多导睡眠图(PSG)数据中的标准生理参数。我们使用回归分析来评估分夜PSG(SN-PSG)与整夜PSG(FN-PSG)滴定期间中枢性呼吸暂停指数(CAI)≥5的二元存在或不存在的预测因素。

结果

滴定期间,24.2%的SN-PSG患者和11.4%的FN-PSG患者CAI≥5。对于SN-PSG和FN-PSG患者,男性、最大持续气道正压通气以及使用双水平气道正压通气是TECSA的预测因素,快速眼动优势是负向预测因素。自我报告使用麻醉药品是TECSA的正向预测因素,仅对于SN-PSG患者,N2期睡眠时长是负向预测因素。自我报告的中风病史和诊断记录期间的CAI仅对FN-PSG患者预测TECSA。

结论

治疗诱发的中枢性呼吸暂停的临床预测因素涵盖人口统计学、病史、睡眠生理学和滴定因素。随着诊断和治疗方式逐渐远离实验室环境,改进的预测模型可能变得越来越重要,即便PSG仍然是表征原发性中枢性呼吸暂停和TECSA的金标准。

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