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Quality Control of the Ambulatory Polygraphy Using Automatic Analysis

Francisco José Ruiz-López, MD*; Beatriz Fernández-Suárez, PhD; Julia Guardiola-Martínez, PhD; Inés Vergara-LaHuerta, PhD; Juan Latour-Pérez, PhD; Manuel Lorenzo-Cruz, PhD
Author and Funding Information

*From the Pneumology Department (Drs. Ruiz-López, Fernández-Suárez, Guardiola-Martínez, Latour-Pérez, and Lorenzo-Cruz), Arrixaca Hospital, Murcia, Spain; and Vitalaire SLU (Dr. Vergara-LaHuerta), Valencia, Spain.

Correspondence to: Francisco José Ruiz-López, Servicio de Neumología. Hospital Virgen de la Arrixaca, Post Code 30120, (El Palmar) Murcia, Spain; e-mail: med500181@saludalia.com

*HIGES = hypopnea index according to the definition of the GES; HIAASM = hypopnea index according to the definition of the AASM. AI = apnea index; DI3% = Desaturation index ≥ 3% per hour of registry. DI4% = Desaturation index ≥ 4% per hour of registry. Values for RDIGES, RDIAASM, HIGES, and HIAASM obtained automatically are the same.

*The concordance indices were calculated for the initial sample (n = 189) and also for the sum of the initial sample and the validation sample (n = 237).

The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestjournal.org/misc/reprints.shtml).


The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestjournal.org/misc/reprints.shtml).

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestjournal.org/misc/reprints.shtml).


Chest. 2009;135(1):194-200. doi:10.1378/chest.08-0165
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It is necessary to ensure the quality of sleep studies conducted at home given that there can be potential variations. Automatic analysis is simple and could help in an audit. The objective is to find a predictive model of visual reading using an automatic analysis of saturation and respiratory signal in order to establish a reading standard with a polygraph used at home on patients who have sleep apnea-hypopnea clinical symptoms. The analysis was carried out using the following two definitions of hypopnea: an event with a duration of ≥ 10 s with a decrease of > 30% of the respiratory signal; and an event associated either with a desaturation of ≥ 3% or with a desaturation of ≥ 4%. A total of 189 studies were selected from a representative sample of 218 patients. Two pneumologists carried out the readings together. The agreement between the visual respiratory disturbance index (RDI) [ie, apneas plus hypopneas] for both definitions and the automatic respiratory signal analysis (ie, automatic RDI [RDIa]) or the automatic desaturation index of 3% (DI3%a) and of 4% (DI4%a) showed limits from a Bland-Altman plot that were too large. However, a multiple linear regression analysis with RDIa and DI3%a or RDIa and DI4%a presented an acceptable level of agreement with RDI for both definitions (p < 0.001; r2 = 96.2% and 97%, respectively). The 95% confidence interval for the differences between the RDI and the model was ± 10.1 or ± 8.8 events per hour, so a study should be revised outside of these limits. A predictive multiple regression model that uses the automatic analysis of the oximetry and respiratory signal could establish a standard for the visual reading of polygraphy at home.

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