Clinical Studies

Arousals Validation Detected by WatchPAT | WatchPAT vs. PSG Validation of Sleep Indices |  WatchPAT Sleep Stages Validation  | Deep and Light Validation | Treatment Assessment | Download Summary of Evidence

Numerous validation studies demonstrated a high degree of correlation in RDI and AHI between WatchPAT and PSG sleep studies. With WatchPAT, both RDI and AHI scores are highly reproducible, showing correlation between home and in-laboratory sleep studies.

WatchPAT has excellent reliability with minimal failure rate (1%) during data acquisition or data analysis, and minimal technician time compared to PSG.

WatchPAT monitors changes in peripheral arterial tone and activity, as well as in blood oxygen saturation levels. It also identifies sleep apnea events just like the equipment used inPSG sleep studies performed in hospital sleep labs.

WatchPAT has been the subject of numerous clinical trials resulting in over 130 peer-reviewed papers and abstracts. Of these, 13 manuscripts validate WatchPAT by comparing it head-to-head with full polysomnography (PSG). In fact, more validation articles vs. PSG have been published in peer-reviewed journals about WatchPAT than with any other portable sleep-testing device.

WatchPAT is the most precise, user-friendly ambulatory sleep apnea diagnostic tool available. Its groundbreaking combination of technology and ease of use is unparalleled.

The 13 peer-reviewed articles on WatchPAT are listed below along with a brief synopsis of each:

Arousals Validation Detected by the WatchPAT

1.    Autonomic Arousal Index (AAI): An Automated Detection based on Peripheral Arterial Tonometry. 
       Pillar G, Bar A, Shlitner A, Schnall RP, Sheffy J, Lavie P. SLEEP 2002; 25(5):543-549.

Pillar et al. (2002) showed that arousals from sleep are associated with increased sympathetic activation and are therefore associated with peripheral vasoconstriction measured by PAT signal attenuation combined with an increase in pulse rate (derived from the PAT).  An independently studied group of 40 sleep apnea patients simultaneously recorded by both PSG and PAT system were used to develop an automated algorithm based on the PAT signal for the detection of arousals from sleep. The algorithm was further validated in a separate group of 96 subjects. The PSG recordings were manually(blindly) analyzed for arousals based onAmerican Academy of Sleep Medicine (AASM) criteria, while PAT was scored automatically according to the developed automated algorithm. A significant correlation was shown between PSG and PAT arousals (R=0.82, p<0.0001) with good agreement across a wide range of values, and with a ROC curve having an area under the curve of 0.88. The authors concluded that automated analysis of the peripheral arterial tone signal can detect EEG arousals from sleep in a relatively quick and reproducible fashion.

2.    Pillar G, Bar A, Bettito M, Schnall R, Dvir I, Sheffy J, Lavie P.  An automatic ambulatory device for detection of AASM defined arousals from sleep: the WP100.  Sleep Medicine 2003; 4(3):207-212.

Pillar et al. (2003) studied 68 subjects who underwent a whole night simultaneous recording of PSG and WatchPAT. The PSG recordings were blindly scored  for arousals based onAASM criteria, while the WatchPAT provided automatic scoring based on the previously developed algorithm. The authors determined that there was a significant correlation between AASM arousals derived from the PSG and autonomic arousals derived from the WatchPAT (R=0.87, P<0.001), with consistency across a wide range of values of AHI. The sensitivity and specificity of the WatchPAT in detecting patients with at least 20 arousals per hour of sleep were 0.80 and 0.79, respectively, with an ROC having an area under the curve of 0.87. They concluded that automatic analysis of the PAT signal derived from the ambulatory device WatchPAT can accurately identify arousals from sleep in a simple and time-saving fashion.

WatchPAT vs. PSG Validation of Sleep Indices

3.    Evaluation of a Portable Device Based on Peripheral Arterial Tone for Unattended Home Sleep Studies.
      Bar A, Pillar G, Dvir I, Sheffy J, Schnall RP, Lavie P. Chest2003; 123(3): 695-703.

Bar et al. (2003) aimed to validate the efficacy, reliability, and reproducibility of the WatchPAT device for the diagnosis of OSA.  102 subjects underwent in-laboratory full PSG simultaneously with WatchPAT recording. The PSG recordings were blindly scored for apnea/hypopnea according to the American Academy of Sleep Medicine criteria (1999) and the RDI [PSG-RDI] was calculated. The WatchPAT data were analyzed automatically for the PAT RDI (PRDI) .Across a wide range of RDI levels, the PRDI was highly correlated with the PSG-RDI (r = 0.88, p < 0.0001), with an area under the ROC curve of 0.82 and 0.87 for thresholds of 10 events per hour and 20 events per hour, respectively. The PRDI scores were also highly reproducible, showing high correlation between home and in-laboratory sleep studies (r =0.89, p < 0.001). The authors concluded that the WatchPAT may offer an accurate, robust, and reliable ambulatory method for the detection of OSAS with minimal patient discomfort.

4.    Validation a Portable Monitoring Device for Sleep Apnea Diagnosis in a Population Based Cohort Using Synchronized Home Polysomnography. 
       Zou D, Grote L, Peker Y, Lindblad U, Hedenr J. SLEEP 2006; 29(3):367-374.

Zou et al. (2006) aimed to assess the accuracy of the WatchPAT todiagnose OSA using at home un-attended simultaneous PSG and Watch-PAT recording in a population-based cohort, i.e. in a population sample not preselected for OSA symptoms. This was the first ever validation of a portable device vs. PSG at the home environment rather than in the sleep-lab environment offering a new standard for validating portable devices. They randomly recruited 98 subjects from the SKARA study in Sweden. The accuracy of WatchPAT in RDI, AHI, ODI, and sleep-wake detection was assessed by comparison with data from the simultaneously recorded PSG. WatchPAT RDI, AHI, and ODI correlated closely (0.88, 0.90, and 0.92; p < .0001, respectively) with the corresponding indexes obtained by PSG. The area under the ROC curve for WatchPAT AHI and RDI were 0.93 and 0.90 for the PSG-AHI and RDI thresholds of 10 and 20 (p < .0001) respectively. The agreement of the sleep-wake assessment was 82 ± 7%. The authors concluded that the WatchPAT was reasonably accurate for unattended home diagnosis ofOSA in a population sample not preselected for OSA symptoms. 

5.    Assessment of a Wrist-worn Device in the Detection of Obstructive Sleep Apnea. 
     Ayas N. TA, Pittman S, MacDonald M, White D.Sleep Medicine 2003; 4(5):435-442.

Ayas et al. (2003) aimed to assess the accuracy of the WatchPAT to diagnose OSA in 30 subjects by applying simultaneous in-laboratory PSG and WatchPAT full-night recording and comparing the two. A significant correlation was shown between the two methods (r = 0:87, p <0:001). To assess sensitivity and specificity of WatchPAT, ROC curves were constructed using a variety of AHI threshold values (10, 15, 20, and 30). Optimal combinations of sensitivity and specificity for the various thresholds were 82.6/71.4, 93.3/73.3, 90.9/84.2, and 83.3/91.7, respectively. The authors concluded that the WatchPAT is a device that can detect OSA with reasonable accuracy and that it may be a usefulmethod to diagnose OSA.

6.    Using a Wrist-Worn Device Based on Peripheral Arterial Tonometry to Diagnose Obstructive Sleep Apnea: In-Laboratory and Ambulatory Validation. 
     Pittman SD, Ayas NT, MacDonald MM, Malhotra A, Fogel RB, White D. SLEEP 2004; 27(5):923-933.

Pittman et al. (2004) assessed the WatchPAT in diagnosing OSA in the home environment. 30 subjects completed two overnight diagnostic studies with the test device: 1 night in the laboratory with concurrent PSG and one night in the home with only the WatchPAT. This study presents significantly good correlation between PSG and WatchPAT indices. Home studies were performed with no technical failures. The authors concluded in this study of a population of 30 patients suspected of having OSA that the WatchPAT can quantify an ODI that compares very well with Medicare criteria for defining respiratory events and an RDI thatcompares favorablywith AASM criteria for defining respiratory events and that the device can be used with a low failure rate in the lab and home for self-administered testing.

7.    A comparison of polysomnography and the WatchPAT in the diagnosis of obstructive sleep apnea. 
     Kenny P. Pang, Christine G. Gourin and David J. Terris.  Otolaryngology–Head and Neck Surgery (2007) 137, 665-668.

Pang et al. (2007) conducted a study of 37 consecutively selected patients referred to a sleep lab for suspected OSA using simultaneous recording of WatchPAT and PSG in the sleep laboratory. They found high correlation, sensitivity, and specificity between the WatchPAT and PSG (0.93, 0.96 and 0.8, respectively).  The authors concluded that, in addition to demonstrating a high correlation with PSG, WatchPAT is a small, lightweight, inexpensive, reliable, accurate, easy to use, and safe.

WatchPAT Sleep Stages Validation

8.    A Novel adaptive wrist actigraphy algorithm for Sleep-Wake assessment in sleep apnea patients. Hedner J, Pillar G, Pittman DS, Zou D, Grote L, White D. SLEEP 2004; 27(8):1560-1566.

Hedner et al. (2004) validated the wake/sleep detection of the WatchPAT in 228 OSA patients and normal volunteers in a three sites multi-center study – Boston (PI Dr. D White), Gothenburg (PI Dr. J Hedner) and Haifa (PI Dr. G Pillar). All subjects underwent a simultaneous WatchPAT and PSG recording that were later compared on a standard 30sec epoch-by-epoch base. The agreement between the WatchPAT and PSG ranged from 86% in normal volunteers to 86%, 84% and 80% in mild, moderate and severe OSA patients respectively. The authors concluded that this simple method for assessment of total sleep time may provide a useful tool for the accurate quantification of obstructive sleep apnea in the home environment.

9.    Detecting REM sleep from the finger:  automatic REM sleep algorithm based on Peripheral Arterial Tone (PAT) and actigraphy.       Herscovici S, Peer A, Papyan S, Lavie p. Physiological Measurement 2007; 28(2): 129-140.
Herscovici et al. (2007) described and validated the WatchPAT algorithms for detecting REM/Non-REM sleep states. For the validation, 30 subjects were recorded simultaneously with PSG and WatchPAT. A 30 second epoch-by-epoch agreement between the WatchPAT and PSG of 90% for REM stage detection was reported.

The authors concluded that the convenience of obtaining information on REM sleep using an unattended and simple-to-operate hand-mounted device may add clinically important information in the diagnosis and follow-up of sleep apnea patients. Such information may be valuable in assessing the effect of breathing disorders in sleep on sleep structure and identifying patients with REM-related sleep apnea. Furthermore,aspost- treatment increase in REM sleep is associated with subjective improvement in sleep quality, this added feature of the WatchPAT will be useful in evaluating the efficacy of treatment in sleep apnea patients.

Deep and Light Validation

10.    Bresler M, Sheffy K, Pillar G, Preiszler M, Herscovici S, Differentiating between light and deep sleep stages using an Ambulatory Device Based on Peripheral Arterial Tonometry. 
     Physiol Meas. 2008; 29(5): 571-584.

Bresler et al., (2008) described and validated the WatchPAT algorithms for the detection of Deep/Light Sleep stages. For the validation,  44 subjects ( normal, mild OSA, moderate OSA and severe OSA)  were recorded simultaneously with PSG and WatchPAT during a full night sleep recording at the sleep lab . A 30 second epoch-by-epoch agreementbetween the WatchPAT and PSG  of 80%for Deepand Light Sleep stages detection was reported.
The authors concluded that together with the previously described algorithms to detect wake non-REM and REM sleep, they believe that the current study shows that sleepcan be comprehensively staged even without recording EEG, based on actigraphy and autonomic nervous system signals derived from the PAT signal.

Treatment Assessment 

11.    Pittman SD et al., Follow-up assessment of CPAP efficacy in patients with obstructive sleep apnea using an ambulatory device based on peripheral arterial tonometry. 
     Sleep Breath (2006) 10: 123–131.

In Pittman et al. (2006) the authors assessed the accuracy of the WatchPAT in detecting residual episodes of sleep disordered breathing (SDB) duringCPAP therapy in a three sitesmulti-center study: Boston(PI Dr. D White), Gainesville (PI Dr. R Berry) andHaifa (PI Dr. G Pillar).Seventy patients using CPAP for at least three months were evaluated using WatchPAT and PSG simultaneously.  For RDI ≥ 15, the area under the ROC curve was 0.95, leading the authors to conclude that WatchPAT can accurately identified participants with moderate–severe SDB while using CPAP.

12.    Townsend D, Sharma A, Brauer E, Scattarelli D, et al.  Assessing Efficacy, Outcomes, and Cost Savings for Patients with Obstructive Sleep Apnea Using Two Diagnostic and Treatment Strategies.
     Sleep Diagnosis and Therapy 2007; 1(7): 1-8.

Townsend et al. performed an extensive studies that evaluated treatment outcomes in patients diagnosed with an HST (Home Sleep Test) device and PSG, respectively. This community-based study followed 103 patients who were randomized to either home diagnosis using WatchPAT or in-lab diagnosis using PSG.  The study evaluated the CPAP compliance andquality oflife measures three months and six months following CPAP initiation. All measures between the two groups were comparable, the study demonstrated a significant decrease  in overall cost of diagnosis per patient in the  WatchPAT group compared to the  PSG group of  899.74 ± 975 USD and 2,252.73 ± 877 USD respectively (p<0.0001). 
Theauthors concluded that the WatchPAT is a valuable tool that can successfully assess obstructive sleep apnea in a select group of patients when used by sleep medicine specialists. Clinical outcomes including CPAP adherence and quality of life measure are largely equivalent when assessed via PSG or portable monitoring. Cost savings for individual participating in portable monitoring are substantial. 

13.    Berry RB, Hill G, Thompson L, McLaurin V, Randall M.  Portable Monitoring and Auto-Titration versus Polysomnography forthe Diagnosis and Treatment of Sleep Apnea.     Sleep 2008; 31:1423-1431.

Berry et al. randomized parallel group study of 106 patients (53 in each of two groups) with daytime sleepiness at the Veterans Administration Medical Center, Gainesville,  that compared a clinical pathway using the WatchPAT for diagnosis of OSA followed by an unattended auto-titrating positive airway pressure (APAP)to determine an effective continuous positive airway pressure (CPAP) with another pathway using in sleep-laboratory PSG for diagnosis of OSA and titrating CPAP pressure.  At a clinic visit six weeks after starting CPAP, 40 of the 53 patients in the Watch-PAT-APAP group who were diagnosed with OSA and auto titrated  and accepted CPAP as a treatment (78.4% of those diagnosed with OSA and 88.8% of those who started CPAP) and 39 of the 53 patients in the PSG group who were diagnosed with OSA and accepted CPAP as a treatment (81% of those with OSAand 90.6% of those who startedCPAP) were still using CPAP (p=NS).  The mean nightly adherence, decrease in Epworth sleepiness scale, improvement in the global Functional Outcome of Sleep Questionnaire score, and CPAP satisfaction did not differ between the groups.  The investigators concluded that the clinical pathway utilizing the WatchPAT and APAP titration resulted in similar CPAP adherence and clinical outcomes as one using PSG.

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