Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-25 @ 2:41 AM
Ignite Modification Date:
2025-12-25 @ 2:41 AM
NCT ID:
NCT03526133
Brief Summary:
Obstructive sleep apnea (OSA) is common and largely underdiagnosed disease. The standard method for the diagnosis of OSA is a complete night polysomnography (PSG). Simple methods for OSA diagnosis are necessary. The overnight oximetry with the oxygen desaturation index (ODI) has been largely investigated as a diagnostic test for OSA but its accuracy remains undefined. The aim of our study is to evaluate if an wireless polygraph (Oxistar) is accurate to diagnosis OSA in patients referred to a Sleep Lab.
Detailed Description:
Consecutive patients referred to the sleep laboratory with suspected diagnosis of OSA underwent in-laboratory polysomnography (PSG) and simultaneously wireless polygraph. The PSG oximeter and the wireless polygraph were worn on different fingers of the same hand. All sleep studies were reviewed by one blind investigator according the 2017 American Academy of Sleep Medicine recommendations. The number of desaturations from wireless polygraph at the 3 predefined threshold levels (of ODI-2%, ODI-3%, or ODI-4%) was derived automatically using proprietary algorithm. Moderate to severe OSA was defined as AHI ≥ 15 events/h. The diagnostic accuracy of ODI-2%, 3%, and 4% for the diagnosis of moderate-severe OSA were calculated for cut-off values from 1 to 20 desaturation events/h. The sleep actimetry was compared with the sleep stages from PSG, most of the statistical metrics applied for diagnosis were used to evaluate the applicability of this proposed method. Finally, the snoring events computed by the smartphone application were compared with the events heard by a specialist and the statistical comparison metrics were evaluated.
Study:
NCT03526133
Study Brief:
Protocol Section:
NCT03526133