Dataset Information

Validation of an obstructive sleep apnea symptom inventory in persons with multiple sclerosis.

ABSTRACT:

Background

Improved screening for obstructive sleep apnea (OSA) could enhance multiple sclerosis (MS) clinical care; yet the utility of current screening tools for OSA have yet to be evaluated in persons with multiple sclerosis (PwMS).

Objectives

The STOP-Bang Questionnnaire is an 8-item screening tool for OSA that is commonly used in non-MS samples. The aim of this study was to assess the validity of the STOP-Bang in PwMS.

Methods

STOP-Bang and polysomnography data were analyzed from n = 200 PwMS. Sensitivity, specificity, positive-, and negative-predictive value (PPV and NPV) were calculated, with receiving operating characteristic (ROC) curves, for each STOP-Bang threshold score, against polysomnography-confirmed OSA diagnosis at three apnea severity thresholds (mild, moderate, and severe).

Results

Nearly 70% had a STOP-Bang score of ⩾3% and 78% had OSA. The STOP-Bang at a threshold score of 3 provided sensitivities of 87% and 91% to detect moderate and severe OSA, respectively; and NPV of 84% and 95% to identify PwMS without moderate or severe OSA, respectively. Sensitivity to detect milder forms of OSA was 76%. The NPV to identify persons without milder forms of OSA was 40%.

Conclusion

The STOP-Bang Questionnaire is an effective tool to screen for moderate and severe OSA in PwMS, but may be insufficient to exclude mild OSA.

SUBMITTER: Singh M

PROVIDER: S-EPMC8627523 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Rationale: Symptom subtypes have been described in clinical and population samples of patients with obstructive sleep apnea (OSA). It is unclear whether these subtypes have different cardiovascular consequences.Objectives: To characterize OSA symptom subtypes and assess their association with prevalent and incident cardiovascular disease in the Sleep Heart Health Study.Methods: Data from 1,207 patients with OSA (apnea-hypopnea index ≥ 15 events/h) were used to evaluate the existence of symptom subtypes using latent class analysis. Associations between subtypes and prevalence of overall cardiovascular disease and its components (coronary heart disease, heart failure, and stroke) were assessed using logistic regression. Kaplan-Meier survival analysis and Cox proportional hazards models were used to evaluate whether subtypes were associated with incident events, including cardiovascular mortality.Measurements and Main Results: Four symptom subtypes were identified (disturbed sleep [12.2%], minimally symptomatic [32.6%], excessively sleepy [16.7%], and moderately sleepy [38.5%]), similar to prior studies. In adjusted models, although no significant associations with prevalent cardiovascular disease were found, the excessively sleepy subtype was associated with more than threefold increased risk of prevalent heart failure compared with each of the other subtypes. Symptom subtype was also associated with incident cardiovascular disease (P < 0.001), coronary heart disease (P = 0.015), and heart failure (P = 0.018), with the excessively sleepy again demonstrating increased risk (hazard ratios, 1.7-2.4) compared with other subtypes. When compared with individuals without OSA (apnea-hypopnea index < 5), significantly increased risk for prevalent and incident cardiovascular events was observed mostly for patients in the excessively sleepy subtype.Conclusions: OSA symptom subtypes are reproducible and associated with cardiovascular risk, providing important evidence of their clinical relevance.