A Validation Study of the NightOwl PAT-based Home Sleep Apnea Test

2019 ◽  
Author(s):  
Keyword(s):  
Sleep Apnea ◽  
Validation Study ◽  
Apnea Test

scholarly journals Analysis of nocturnal desaturation waveforms using algorithms in patients with idiopathic pulmonary fibrosis

2021 ◽  
Author(s):  
Yuichiro Yasuda ◽  
Tatsuya Nagano ◽  
Shintaro Izumi ◽  
Mina Yasuda ◽  
Kosuke Tsuruno ◽  
...  
Keyword(s):  
Sleep Apnea ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Diagnostic Algorithm ◽  
Sleep Time ◽  
Periodic Pattern ◽  
Apnea Hypopnea Index ◽  
Apnea Test ◽  
Eligibility Criteria ◽  
Obstructive Sleep

Abstract Purpose Sleep-disordered breathing is recognized as a comorbidity in patients with idiopathic pulmonary fibrosis (IPF). Among them, nocturnal hypoxemia has been reported to be associated with poor prognosis and disease progression. We developed a diagnostic algorithm to classify nocturnal desaturation from percutaneous oxygen saturation (SpO2) waveform patterns: sustained pattern, periodic pattern, and intermittent pattern. We then investigated the prevalence of nocturnal desaturation and the association between the waveform patterns of nocturnal desaturation and clinical findings of patients with IPF. Methods We prospectively enrolled patients with IPF from seven general hospitals between April 2017 and March 2020 and measured nocturnal SpO2 and nasal airflow by using a home sleep apnea test. An algorithm was used to classify the types of nocturnal desaturation. We evaluated the association between sleep or clinical parameters and each waveform pattern of nocturnal desaturation. Results Among 60 patients (47 men) who met the eligibility criteria, there were 3 cases with the sustained pattern, 49 cases with the periodic pattern, and 41 cases with the intermittent pattern. Lowest SpO2 during sleep and total sleep time spent with SpO2 < 90% were associated with the sustained pattern, and apnea–hypopnea index was associated with the intermittent pattern. Conclusion We demonstrated the prevalence of each waveform and association between each waveform and sleep parameters in patients with IPF. This classification algorithm may be useful to predict the degree of hypoxemia or the complication of obstructive sleep apnea.

474 Phenotyping of patients with Moderate to Severe OSA on Polysomnography after Negative Home Sleep Apnea Testing

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A187-A187
Author(s):  
Sarah Sarfraz ◽  
Lindsay McCullough ◽  
Henry Arantes ◽  
Alejandra Lastra
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Flow Time ◽  
Apnea Hypopnea Index ◽  
Apnea Test ◽  
Recording Time ◽  
Time Flow ◽  
Obstructive Sleep ◽  
Severe Sleep Apnea ◽  
Apnea Testing

Abstract Introduction Polysomnography (PSG) is the gold standard for the diagnosis of obstructive sleep apnea (OSA). Given cost, insurance restrictions and in some cases limited access to sleep center testing, the use of home based sleep apnea testing is becoming increasingly more common. A proportion of patients with technically adequate HSAT who are negative end up having significant disease on PSG. The characteristics of patients who are found to have moderate to severe sleep apnea on polysomnogram (PSG) after a negative home sleep apnea test (HSAT) are not known. We aim to phenotype these patients. Methods We conducted a retrospective chart review from March 2018 to February 2020. A total of 953 adult patients (18 years old and older) underwent HSAT, 248 tests resulted negative (apnea-hypopnea index &lt;5/h). Out of the negative HSAT, 17 patients had moderate to severe obstructive sleep apnea on PSG. Those were included for analysis. Data on patient characteristics such as age, body mass index (BMI), gender, STOP-BANG, ESS and comorbidities was gathered. Respiratory disturbance index, recording time, flow time, oximetry time on HSAT was recorded. PSG recording time, baseline AHI, supine AHI and non-supine AHI were also noted. Technically inadequate HSAT were excluded from analysis. Results The percentage of patients with negative HSAT who were found to have moderate to severe sleep apnea on PSG and were included for analysis was 6.85% (n17). Mean age was 41 years. Mean BMI was 33 kg/m2. Common comorbidities were hypertension (29%), asthma (17.6 %), depression (17.6%), anxiety (11.7%) and reflux (5.9%). Average ESS was 11.7 and STOP-BANG was 3.8. The mean recording time was 477 minutes, flow time 391 minutes and oximetry time was 426 minutes on HSAT. Average PSG recording time was 433 minutes. Average AHI was 24 with supine being 33.2/h and non-supine 17.9/h. Conclusion A proportion of patients with negative HSAT have moderate to severe OSA on follow-up polysomnogram. These patients were young, with lower-class obesity, more positional OSA, and no associated complex comorbidities. Re-evaluation of current diagnostic algorithms and further research is needed to phenotype this at-risk group, as first-line PSG may be more cost-effective and efficient. Support (if any):

Does every obese sleep apnea patients need CPAP treatment before bariatric surgery: Results of a validation study

2020 ◽  
Vol 4 (4) ◽  
pp. 266-271
Author(s):  
Frédéric Sériès ◽  
Maxime Martin ◽  
Isabelle Boutin ◽  
Simon Marceau ◽  
Jean Bussières ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Sleep Apnea ◽  
Validation Study ◽  
Cpap Treatment

scholarly journals Detecting central sleep apnea in adult patients using WatchPAT—a multicenter validation study

2019 ◽  
Vol 24 (1) ◽  
pp. 387-398 ◽  
Author(s):  
Giora Pillar ◽  
Murray Berall ◽  
Richard Berry ◽  
Tamar Etzioni ◽  
Noam Shrater ◽  
...  
Keyword(s):  
Sleep Apnea ◽  
Validation Study ◽  
Central Sleep Apnea ◽  
Adult Patients ◽  
Multicenter Validation

scholarly journals 0610 Prevalence of Positional Obstructive Sleep Apnea Based on 3% Vs 4% Oxygen Desaturation Using Home Sleep Apnea Testing

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A233-A234
Author(s):  
M Mandal ◽  
R Rengan ◽  
S Rani ◽  
J Ramzy ◽  
M Vega Sanchez ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Oxygen Desaturation ◽  
Apnea Hypopnea Index ◽  
Apnea Test ◽  
Positional Obstructive Sleep Apnea ◽  
Obstructive Sleep ◽  
Respiratory Event ◽  
Home Sleep Apnea Testing ◽  
Definition Of

Abstract Introduction Approximately 30% of patient with obstructive sleep apnea (OSA) have positional OSA [non-supine apnea-hypopnea index (AHI) &lt; 5 events/hr]. However, the prevalence is based on variable definitions for hypopneas related to the degree of oxygen desaturation. In addition, use of a home sleep apnea test (HSAT) to identify positional OSA is limited. We hypothesized that in patients evaluated with an HSAT, using a definition for hypopneas based on 4% compared to 3% oxygen desaturation will significantly decrease the percentage diagnosed with positional OSA. Methods Fourteen patients with positional OSA based on a non-supine respiratory event index (REI) &lt; 5 events/hr were included. The initial diagnosis was determined based on a hypopnea definition of ≥ 3% oxygen desaturation. The studies were reanalyzed using a hypopnea definition of ≥ 4% oxygen desaturation. Results Fourteen patients [9 (64%) males, 46±14 yrs, BMI 31±6 kg/m2, ESS 7±5, REI 9±3 events/hr, mean SaO2 94±2%, lowest SaO2 81±6%, %TST SaO2 &lt; 90% 4±6%] were identified with positional OSA (supine REI 16±7 events/hr, non-supine REI 3±1 events/hr) using a hypopneas definition of ≥ 3% oxygen desaturation. When reanalyzed using a hypopnea ≥ 4% oxygen desaturation there was a significant decrease in the REI to 7±2 events/hr (p&lt;0.001). Three patients (21%) no longer were considered to have OSA. These patients were younger (32±14 vs. 50±11yrs, p=0.03) and had less severe OSA (REI 6±1 vs. 9±3 events/hr (p=0.04), but there was no difference in BMI (32±11 vs. 31±5 kg/m2, p=0.9) or mean and lowest SaO2 (96±0.4 vs. 94±2%, p=0.13, and 82±8 vs. 81±6%, p=0.9, respectively). Conclusion In patients with mild positional OSA, using a hypopnea definition of at least 4% vs. 3% oxygen desaturation on a HSAT will have a significant effect on the overall REI and often exclude patients who would otherwise be treated for OSA. Support None.

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