• Pacing Clin Electrophysiol · Oct 2006

    Feasibility of automated detection of advanced sleep disordered breathing utilizing an implantable pacemaker ventilation sensor.

    • Alaa Shalaby, Charles Atwood, Claudius Hansen, Martin Konermann, Pradip Jamnadas, Kent Lee, Roger Willems, Jesse Hartley, Jeffrey Stahmann, Jonathan Kwok, Quan Ni, and Joerg Neuzner.
    • Division of Cardiology, Pittsburgh VA Healthcare System, University of Pittsburgh, Pittsburgh, PA 15240, USA. Alaa.Shalaby@med.va.gov
    • Pacing Clin Electrophysiol. 2006 Oct 1; 29 (10): 1036-43.

    ObjectivesThis study tested the feasibility of automatically detecting advanced sleep disordered breathing (SDB) from a pacemaker trans-thoracic impedance sensor.BackgroundSDB is prevalent yet under-diagnosed in patients with cardiovascular disease. The potential for automated detection of SDB in patients receiving pacemakers with respiration sensors has not been fully explored. We hypothesized that the trans-thoracic impedance sensor could be utilized for automatic detection of advanced SDB.MethodsPatients underwent overnight polysomnography (PSG). The pacemaker trans-thoracic impedance signal was simultaneously recorded and time synchronized with the polysomnograph. Cardiovascular health variables were abstracted from medical records. Apnea was defined as cessation of inspiratory airflow lasting 10 seconds or longer. Hypopnea was defined as a reduction of tidal volume of at least 30% from baseline tidal volume, lasting 10 seconds or more. A computer algorithm (PM-A) was developed to automatically detect SDB from the pacemaker impedance sensor data. The performance of automated SDB detection was compared against PSG.ResultsSixty patients (aged 69 +/- 12 years, 45 males) were studied. Advanced SDB (moderate or severe) was diagnosed in 40 patients. Severe SDB (apnea-hypopnea index [AHI]> or = 30) was diagnosed in 32 patients (53%), but only 5 patients had prior diagnosis of the disease. Moderate SDB (30 > AHI > 15) was diagnosed in 8 patients of whom only two were previously diagnosed. Cardiovascular health variables did not predict the presence of advanced SDB. PM-A derived AHI correlated with that of the PSG (r = 0.80, P < 0.01). The algorithm identified patients with advanced SDB with 82% sensitivity and 88% specificity.ConclusionsIt is feasible to automatically measure SDB severity using a pacemaker trans-thoracic impedance sensor. Advanced SDB was frequently undiagnosed in this cohort of pacemaker patients.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

What will the 'Medical Journal of You' look like?

Start your free 21 day trial now.

We guarantee your privacy. Your email address will not be shared.