Validation a Portable Monitoring Device for Sleep Apnea Diagnosis in a Population Based Cohort Using Synchronized Home Polysomnography

Zou, Ding; Grote, Ludger; Peker, Yüksel; Lindblad, Ulf; Hedner, Jan

doi:10.1093/sleep/29.3.367

Cited by 137 publications

(118 citation statements)

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“…Watch-PAT identifi ed the drivers with RDI > 15 with 89.1% sensitivity and 76.9% specifi city. There are studies confi rming the validation of Watch-PAT device simultaneously with PSG, 5,[8][9][10][11][12] detection of the arousals, 6,13 and assessment of CPAP effi cacy. 14,15 This is the fi rst study evaluating the reliability of Watch-PAT in a particular group, in this case, highway bus drivers.…”

Section: Discussionmentioning

confidence: 99%

“…Most of the studies are with Watch-PAT 100 device. 5,6,[8][9][10][11][12][13][14][15]18,19 Recently, Watch-PAT 200 has been shown to provide quick diagnosis in OSA and to be valid in the diagnosis of OSA during pregnancy. 20,21 Our particular question was the reliability of this device in the diagnosis of obstructive sleep apnea in highway bus drivers.…”

Section: Discussionmentioning

confidence: 99%

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Reliability of the Watch-PAT 200 in Detecting Sleep Apnea in Highway Bus Drivers

Yüceege

Fırat²,

Demir³

et al. 2013

Journal of Clinical Sleep Medicine

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bRIEF SUmmARYCurrent knowledge/Study Rationale: Polysomnography is mandatory in drivers older than 45 years old and those with snoring, witnessed apnea and/or day time sleepiness who are younger than 45 years old, before getting a highway bus driver licence in Turkey, but the number of sleep centers are not enough to test all the applicants. This study has been done to test the accuracy of Watch-PAT device in detecting sleep disordered breathing among the highway bus drivers.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Reliability of the Watch-PAT 200 in Detecting Sleep Apnea in Highway Bus Drivers

Yüceege

Fırat²,

Demir³

et al. 2013

Journal of Clinical Sleep Medicine

View full text Add to dashboard Cite

show abstract

“…5 It has been shown to accurately detect OSA (in laboratory and ambulatory settings), [5][6][7][8] autonomic arousals, 9 and sleep/wake status. 10 The validity of using PAT and actigraphy signals derived from the PAT recorder to detect REM 11 and light/deep 12 sleep has also been demonstrated in two small studies.…”

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

Sleep Staging Based on Autonomic Signals: A Multi-Center Validation Study

Hedner

White

Malhotra

et al. 2011

Journal of Clinical Sleep Medicine

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Study Objectives: One of the most important caveats of ambulatory devices is the inability to record and stage sleep. We assessed an algorithm determining 4 different stages: wake, light sleep, deep sleep, and REM sleep using signals derived from the portable monitor Watch-PAT100 (PAT recorder). Methods: Participants (38 normal subjects and 189 patients with obstructive sleep apnea [OSA]) underwent simultaneous overnight recordings with polysomnography (PSG) and the PAT recorder in a study originally designed to assess the accuracy of the PAT recorder in diagnosing OSA. Light/deep sleep and REM sleep from the PAT recorder recording were automatically scored based on features extracted from time series of peripheral arterial tone amplitudes and inter pulse periods. The PSG scored sleep stages 1 and 2 were classified as light sleep for epoch-by-epoch comparisons. Results:The overall agreement in detecting light/deep and REM sleep were 88.6% ± 5.9% and 88.7% ± 5.5%, respectively. There was a good agreement between PSG and the PAT recorder in quantifying sleep efficiency (78.4% ± 9.9% vs. 78.8% ± 13.4%), REM latency (237 ± 148 vs. 225 ± 159 epochs), and REM percentage (14.4% ± 6.5% vs. 19.3% ± 8.7%). OSA severity did not affect the sensitivity and specificity of the algorithm. The Cohen κ coefficient for detecting all sleep stages: sleep from wake, REM from NREM sleep, and deep from light sleep were 0.48, 0.55, 0.59, and 0.46, respectively. Conclusions: Analysis of autonomic signals from the PAT recorder can detect sleep stages with moderate agreement to more standard techniques in normal subjects and OSA patients. This novel algorithm may provide insights on sleep and sleep architecture when applying the PAT recorder for OSA diagnosis.

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“…However, PTT is not a current transaction for screening at OSAS patients. On the other hand, although PAT has been subject to the reports as a screening test with its high compliance with PSG, a completely dedicated device and software are needed (7)(8)(9)(10) Table 1. Demographic and HRV parameters of case and control groups cardiovascular diseases such as hypertension, ischemic heart disease, and congestive heart failure has been demonstrated quite well.…”

Section: Discussionmentioning

confidence: 99%

Heart rate variability analysis of single channel electrocardiogram can help to differentiate high- risk patients with obstructive sleep apnea syndrome - a study on diagnostic accuracy

Karasulu¹,

Dalar²,

Sökücü³

et al. 2012

Anadolu Kardiyol Derg

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Heart rate variability analysis of single-channel electrocardiogram can help to differentiate high-risk patients with obstructive sleep apnea syndrome -a study on diagnostic accuracyTek kanal elektrokardiyografide kalp hızı değişkenliği analizi yüksek riskli obstrüktif uyku apne sendromlu hastaları tanımlamada yardımcı olabilir-Bir doğruluk değeri çalışması ABSTRACTObjective: To evaluate the usefulness of heart rate variability analysis (HRV) analysis from the long duration electrocardiogram (ECG) recordings as a screening test for the diagnosis of moderate-to-severe obstructive sleep apnea syndrome (OSAS). Methods: Recordings from 87 patients who were admitted to sleep laboratory for polysomnographic study (PSG) were evaluated. Finally 30 cases with apnea-hypopnea index (AHI)≥15/hour included in patient's group (male/female: 22/8; mean age: 49±10 years) and 21 cases with AHI<5 were included in control group (male/female: 10/11; mean age: 48±11 years). From the ECG recordings taken as a part of PSG, time -domain and frequency -domain HRV parameters were evaluated and their accuracy in the diagnosis of OSAS was investigated using ROC analysis.Results: Statistically significant differences were found in HRV variables in time-domain parameters such as SDNN, SDNN index; frequencydomain parameters VLF, LF, nuLF, nuHF, LF/HF and geometric parameter HRV triangular index values in between groups. Cut-off value of 16 for the HRV triangular index was found to be 50% sensitive and 85.7% specific with a positive likelihood ratio (LR) of 3.50% and negative LR of 0.58% When the total power was higher than 9.611, then the analysis sensitivity was 53.3%, specificity was 95.6%, positive LR was 11.2% and negative LR was 0.49% When the SDNN was higher than 83 then its sensitivity was 80%, specificity was 76.2%, positive LR was 3.36% and negative LR was 0.26% For the cut off value of 62 calculated for SDNN index, sensitivity was 73.3%, specificity was 85.7%, positive LR was 5.13% and negative LR was 0.31%, for the cut off value of 9.12 was calculated for VLF, sensitivity was 90.4% specificity was 50% positive LR was 1.81% and negative LR was 0.19%. Conclusion: Heart rate variability analysis done over routine single channel ECG data gathered through routine Holter applications may be helpful in distinguishing moderate-to-severe OSAS patients from mild OSAS patients and non-OSAS control subjects.(Anadolu Kardiyol Derg 2012; 12: 331-8) Key words: Diagnosis, electrocardiography, heart rate, polysomnography, sleep apnea, sensitivity, specificity Original Investigation Özgün Araşt›rma 331ÖZET Amaç: Çalışmanın amacı uzun süreli tek kanal elektrokardiyogram (EKG) kaydı üzerinden yapılan kalp atım hızı değişkenliği (HRV) analizinin orta ve ağır tıkayıcı uyku apne hipopne sendromu (TUA) hastalarının taranmasına katkısını araştırmaktır.Yöntemler: Hastanemizin uyku laboratuvarına başvurarak polisomnografi yapılan 87 hastanın kayıtları değerlendirildi. Değerlendirme sonucunda apne-hipopne indeksi (AHI)≥15/saatin üzerinde bulunan 30 kişi olgu ...

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Validation a Portable Monitoring Device for Sleep Apnea Diagnosis in a Population Based Cohort Using Synchronized Home Polysomnography

Cited by 137 publications

References 40 publications

Reliability of the Watch-PAT 200 in Detecting Sleep Apnea in Highway Bus Drivers

Reliability of the Watch-PAT 200 in Detecting Sleep Apnea in Highway Bus Drivers

Sleep Staging Based on Autonomic Signals: A Multi-Center Validation Study

Heart rate variability analysis of single channel electrocardiogram can help to differentiate high- risk patients with obstructive sleep apnea syndrome - a study on diagnostic accuracy

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