Apnea–hypopnea index as a predictor of atrial fibrillation recurrence following initial pulmonary vein isolation: usefulness of type-3 portable monitor for sleep-disordered breathing

Background: Sleep-disordered breathing (SDB) is an independent risk factor for stroke. The reported prevalence of SDB after stroke ranges from 60 to >70%, while the pre-stroke prevalence of SDB is less well described. Moreover, much of these data are derived from ischemic stroke or mixed ischemic stroke and intracerebral hemorrhage (ICH) cohorts. Studies that assess the prevalence of SDB before and after ICH are lacking, with only one prior study (n=32) that reported a post-ICH SDB prevalence of 78%. We report herein the results of a second, larger, prospective study that assessed the prevalence of pre- and post-ICH. Methods: Participants enrolled in the population-based stroke surveillance study, the Brain Attack Surveillance in Corpus Christi (BASIC) project, with ICH from 2010-2015 were screened for SDB with the well validated ApneaLink Plus portable monitor (SDB defined as apnea-hypopnea index (AHI) ≥10). The Berlin questionnaire was administered, with reference to the pre-ICH state, to assess for possible pre-stroke SDB. Results: Of the 60 ICH participants screened, the median age was 63 years (interquartile range (IQR): 55.5, 74.5). Twenty-one (35%) were female, 54 (90%) were Mexican American, and 53 (88%) had a history of hypertension. The median Glasgow Coma Scale score was 15.0 (IQR: 15.0, 15.0) and the median NIHSS was 5.5 (IQR: 1.5, 8.0). Post-ICH, the median AHI was 9.5 (IQR: 5.5, 19.0); almost half (46.7%) met criteria for SDB. Thirty-four participants (56.7%) screened as high risk for SDB pre-ICH. Conclusion: Sleep-disordered breathing was highly prevalent after ICH, and also likely common before ICH, in this mostly Mexican American, community-based sample. If SDB increases risk for ICH, the findings suggest a potential new treatment target to prevent ICH and recurrent ICH.

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Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic

Canadian Respiratory Journal ◽

10.1155/2020/4936423 ◽

2020 ◽

Vol 2020 ◽

pp. 1-6 ◽

Cited By ~ 1

Author(s):

Yi Rong ◽

Shihan Wang ◽

Hui Wang ◽

Feng Wang ◽

Jingjing Tang ◽

...

Keyword(s):

Predictive Value ◽

Sleep Disordered Breathing ◽

Screening Tool ◽

Characteristic Curve ◽

Population Based ◽

Screening Tools ◽

Apnea Hypopnea Index ◽

Portable Monitor ◽

Number Of Patients ◽

Disordered Breathing

Background. There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies. Aim. To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire. Methods. We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening. Results. Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI ≥ 5), moderate-to-severe (AHI ≥ 15), and severe (AHI ≥ 30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655–0.775) of diagnosing SDB at AHI cutoff of ≥5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046). Conclusion. The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice.

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P661Nocturnal hypoxemic burden in ambulatory patients with atrial fibrillation: a disease-orientated assessment of sleep-disordered breathing severity

European Heart Journal ◽

10.1093/eurheartj/ehz747.0267 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

D Linz ◽

C Nalliah ◽

M Baumert ◽

K Kadhim ◽

M Middeldorp ◽

...

Keyword(s):

Atrial Fibrillation ◽

Sleep Disordered Breathing ◽

Apnea Hypopnea Index ◽

Respiratory Events ◽

Gender And Age ◽

Ambulatory Patients ◽

Overnight Oximetry ◽

The Relationship ◽

Disordered Breathing ◽

Overall Risk

Abstract Background Studies investigating the relationship between sleep-disordered breathing (SDB) and atrial fibrillation (AF) have largely assessed SDB-severity by the apnea–hypopnea index (AHI). However, the AHI does not incorporate nocturnal hypoxemic burden, which may increase the risk of non-paroxysmal AF (nPAF) as the clinical manifestation of more progressed AF substrates. This investigation sought to systematically characterize and compare the composition of AHI and hypoxemic burden with the aim to defining a disease-orientated metric for SDB-severity best associated with prevalent nPAF. Methods Polysomnography including overnight oximetry data were obtained in 435 consecutive ambulatory AF patients to determine the composition of AHI (apneas vs. hypopneas), the number of acute episodic desaturations per hour (oxygen desaturation index, ODI) and the composition of total time spent below 90% oxygen saturation (T90Total) attributed to acute desaturations (T90Desaturation). Logistic regression analysis was used to characterize the association with prevalent nPAF. Results One hundred sixty-nine AF patients (38%) had nPAF and one third (n=149, 34%) had moderate-to-severe SDB (AHI>15). 82% of the median total AHI (9.4 [3.6–20.1]) could be attributed to hypopneas. Only 29% of events were associated with episodic desaturations, which contributed to 96% (T90Desaturation) of the variation in T90Total. The high variability in durations and nadirs of distinct desaturation events can expose patients to long T90Total, even if the AHI is low. Not AHI, but T90Total and ODI were associated with nPAF independent of gender and age. However, diabetes, hypertension and body mass index contributed more significantly to the overall risk of nPAF. Conclusions In AF patients, hypopneas constitute a majority of respiratory events during sleep. Patients with low AHI can still be exposed to high nocturnal hypoxemic burden, which is mainly a cumulative consequence of episodic desaturations. T90Total and ODI, but not AHI, were associated with nPAF independent of gender and age, but concomitant modifiable risk factors made a more significant contribution to the overall risk of nPAF versus PAF.

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