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. 2023 Jan 1;19(1):45-54.
doi: 10.5664/jcsm.10262.

Validation of STOP, STOP-BANG, STOP-BAG, STOP-B28, and GOAL screening tools for identification of obstructive sleep apnea in patients with Parkinson disease

Teresa Gomes  1   2 , Andrea Benedetti  3   4 , Anne-Louise Lafontaine  5 , Richard John Kimoff  6 , Ann Robinson  6 , Marta Kaminska  4   6
Affiliations

Validation of STOP, STOP-BANG, STOP-BAG, STOP-B28, and GOAL screening tools for identification of obstructive sleep apnea in patients with Parkinson disease

Teresa Gomes et al. J Clin Sleep Med. .

Abstract

Study objectives: Obstructive sleep apnea (OSA) is common in Parkinson disease (PD). Questionnaires can be used as screening tools and have been used as a surrogate definition of OSA in large-scale research. This study aimed to validate the performance of STOP, STOP-BANG, STOP-BAG, STOP-B28, and GOAL and OSA predictors as tools to identify OSA in PD.

Methods: Data were analyzed from a PD cohort study in which OSA was diagnosed using laboratory polysomnography. We calculated sensitivity and specificity of each questionnaire for OSA using different definitions and performed receiver operating characteristics curve analysis. Linear regression was used to assess adjusted associations between questionnaires and outcomes: Montreal Cognitive Assessment, Epworth Sleepiness Scale, and Movement Disorder Society revision of the Unified Parkinson Disease Rating Scale.

Results: Questionnaire data were available for 68 PD patients (61.8% male, mean age 64.5 [standard deviation 9.9] years, and Hoehn and Yahr score 2.1 [0.8]). OSA (apnea-hypopnea index ≥ 15 events/h) occurred in 69.4% of participants. STOP-B28 ≥ 2 presented a higher sensitivity for OSA than STOP ≥ 2 (0.76 vs 0.65, respectively) and slightly lower specificity (0.65 vs 0.70, respectively). GOAL ≥ 2 had the highest sensitivity but poor specificity. Loud snoring had sensitivity 0.63 and specificity 0.65. STOP and snoring were significantly associated with Montreal Cognitive Assessment, Epworth Sleepiness Scale, and Movement Disorder Society revision of the Unified Parkinson Disease Rating Scale (total, motor, and nonmotor); STOP-BANG, STOP-BAG, and STOP-B28 showed associations with most outcomes, but the GOAL showed none.

Conclusions: The STOP-B28 followed by STOP and presence of loud snoring alone seem to have the best overall properties to identify PD patients with OSA, whose clinical characteristics differ from the general population with OSA.

Citation: Gomes T, Benedetti A, Lafontaine A-L, Kimoff RJ Robinson A, Kaminska M. Validation of STOP, STOP-BANG, STOP-BAG, STOP-B28, and GOAL screening tools for identification of obstructive sleep apnea in patients with Parkinson disease. J Clin Sleep Med. 2023;19(1):45-54.

Keywords: Parkinson; aging; obstructive sleep apnea; questionnaire; screening; validation.

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Conflict of interest statement

All authors have seen and approved the manuscript. The work was performed at the McGill University Health Centre. The study was funded by the Research Institute of the McGill University Health Centre (MUHC), the Department of Medicine of the MUHC and the American Thoracic Society Foundation, with support from the Canadian Sleep and Circadian Network. Andrea Benedetti reports research grants from the Canadian Institutes of Health Research and salary support from Fonds de Recherche du Québec–Santé chercheur boursier, served on Advisory Boards (Abbvie, Sunovion, and Paladin). Richard John Kimoff reports research grants from the Canadian Institutes of Health Research, The Multiple Sclerosis Society of Canada, Fonds de Recherche du Quebec–Santé, Philips-Respironics Inc., ResMed Inc., and VitalAire Inc. Marta Kaminska reports research grants and in-kind support from Philips, VitalAire Inc., the American Thoracic Society Foundation, Canadian Institutes for Health Research, and Weston Brain Institute; Advisory Committee for Biron Soins du Sommeil; Advisory Board for Jazz Pharmaceuticals. The other authors report no conflicts of interest.

Figures

Figure 1
Figure 1. The receiver operating characteristic curve and the areas under the curves of different sleep questionnaires based on AHI ≥ 15 events/h.
Figure 2
Figure 2. The receiver operating characteristic curve and the areas under the curves of different OSA predictors based on AHI ≥ 15.
See this image and copyright information in PMC

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