Diagnostic accuracy and suitability of instruments that screen for obstructive sleep apnoea, insomnia and sleep quality in cardiac patients: a meta-analysis

Identifying Obstructive Sleep Apnea Risk Using the STOP-BANG Questionnaire in a Cardiology Clinic

ABSTRACT

Untreated obstructive sleep apnea (OSA) is associated with increased cardiovascular morbidity and mortality, warranting enhanced awareness, screening, and action among healthcare providers to optimize patient outcomes. Attempting to address the potential under detection of OSA, this quality improvement project implemented the STOP-Bang Sleep Apnea Questionnaire at a cardiology clinic, with the goals to stratify risk for OSA in 100% of patients and increase provider referral of high risk patients for sleep studies. The setting was an outpatient cardiology clinic in Pensacola, Florida. The sample included new and existing patients 18 years or older who had one or more of the following diagnoses: hypertension, heart failure, coronary artery disease, atrial fibrillation, or arrhythmia. Methods involved collecting and comparing preintervention sleep study referral rate data with 6-week STOP-Bang questionnaire implementation data. Results demonstrated a 65% (279 of 428 patients seen) screening implementation rate and a modest but statistically significant increase in the overall referral rate from 2.6% preintervention to 5.1% postintervention ( p = .040). Overall, standard use of the STOP-Bang questionnaire may enable higher detection and referral of OSA.

Barriers and enablers to screening, management and referral of sleep disorders in patients attending cardiac rehabilitation: A qualitative descriptive study

AIMS

To examine healthcare professional's knowledge about assessment and management of sleep disorders for cardiac patients and to describe the barriers to screening and management in cardiac rehabilitation settings.

DESIGN

A qualitative descriptive study. Data were collected via semi-structured interviews.

METHODS

In March 2022, a total of seven focus groups and two interviews were conducted with healthcare professionals who currently work in cardiac rehabilitation settings. Participants included 17 healthcare professionals who had undertaken cardiac rehabilitation training within the past 5 years. The study adheres to the consolidated criteria for reporting qualitative research guidelines. An inductive thematic analysis approach was utilized.

RESULTS

Six themes and 20 sub-themes were identified. Non-validated approaches to identify sleep disorders (such as asking questions) were often used in preference to validated instruments. However, participants reported positive attitudes regarding screening tools provided they did not adversely affect the therapeutic relationship with patients and benefit to patients could be demonstrated. Participants indicated minimal training in sleep issues, and limited knowledge of professional guidelines and recommended that more patient educational materials are needed.

CONCLUSION

Introduction of screening for sleep disorders in cardiac rehabilitation settings requires consideration of resources, the therapeutic relationship with patients and the demonstrated clinical benefit of extra screening. Awareness and familiarity of professional guidelines may improve confidence for nurses in the management of sleep disorders for patients with cardiac illness.

IMPACTS

The findings from this study address healthcare professionals' concerns regarding introduction of screening for sleep disorders for patients with cardiovascular disease. The results indicate concern for therapeutic relationships and patient management and have implications for nursing in settings such as cardiac rehabilitation and post-cardiac event counselling.

REPORTING METHOD

Adherence to COREQ guidelines was maintained.

PATIENT OR PUBLIC CONTRIBUTION

No Patient or Public Contribution as this study explored health professionals' experiences only.

Self-reported Sleep Quality Before and After Atrial Fibrillation Ablation

BACKGROUND

Poor sleep quality is highly prevalent in atrial fibrillation (AF) with reported links between worse sleep quality and higher AF severity. Little research has examined whether sleep quality changes after AF ablation despite it being a routinely performed procedure.

OBJECTIVE

The aim of this study was to evaluate self-reported sleep quality before and after AF ablation and to examine whether sleep quality differs by AF severity or sex.

METHODS

This longitudinal pilot study assessed sleep using the Pittsburgh Sleep Quality Index at preablation and at 1, 3, and 6 months after ablation. Atrial fibrillation disease severity was assessed by the Canadian Cardiology Society Severity of AF scale. Outcomes were analyzed using descriptive statistics, Spearman ρ correlations, and multilevel longitudinal models.

RESULTS

The sample (N = 20) was 55% female with a mean age of 65 (±7) years. Poor sleep quality (mean Pittsburgh Sleep Quality Index scores > 5) was evident at all time points. Improvement was noted at 3 months (moderate effect size d = 0.49); and negligible further improvement, from 3 to 6 months post ablation. Improvement was seen primarily in male subjects (large effect size d = 0.89 at 3 months), with smaller improvements for female subjects. Although Severity of AF scale scores were not correlated with sleep quality, Severity of AF scale severity scores did significantly improve over time.

CONCLUSIONS

Patients with AF have poor sleep quality that improves for the first 3 months after AF ablation, with men showing more improvement than women. A more accurate understanding of the sleep challenges after AF ablation could lead to development of more realistic patient education and improve patient self-management.

The Future of Sleep Measurements: A Review and Perspective

This article provides an overview of the current use, limitations, and future directions of the variety of subjective and objective sleep assessments available. This article argues for various ways and sources of collecting, combining, and using data to enlighten clinical practice and the sleep research of the future. It highlights the prospects of digital management platforms to store and present the data, and the importance of codesign when developing such platforms and other new instruments. It also discusses the abundance of opportunities that data science and machine learning open for the analysis of data.