Clinical professionals in South Africa are generally unaware of the impact of obstructive sleep apnea (OS A). Hooper, director of the Berea Sleep Laboratory, Durban, South Africa, for granting permission to conduct this research.
INTRODUCTION 1.1. Overview
- Purpose of current study
- Conceptual framework
- Research questions
- Organisation of chapters
Within the clinical health psychology model suggested by Schlebusch, (1990), this study explores the value of using the BQ as a diagnostic tool for OS A in primary health care settings in South Africa. The aim of this study is to investigate the construct validity of the BQ (Appendix A) as a diagnostic measure for sleep apnea syndrome in the field of clinical health psychology, comparing the BQ with objective data recorded in patients tested in a sleep laboratory in Durban, South Africa (Netzer et al. 1999; Schwartz, 2005).
THE PHENOMENON OF OBSTRUCTIVE SLEEP APNOEA SYNDROME (OSA)
Introduction
Common health information and risk factors
The risk of developing OSA increases with age and is strongly correlated with obesity and male gender (Chokrovery Wolk et al. 2003). A recent development is the recognition that OSA patients have elevated plasma levels of leptin (a neurohormone that regulates body fat mass and exerts important effects on the cardiovascular system) above those seen in obese patients (Wolk et al. 2003). .
The impact of OSA on Public health
Families often tolerate the symptoms of OSA as a known hallmark of golden family moments. Snoring and obesity are certainly part of the social discourse, alienating and distressing patients (Veale et al. 2002).
Diagnosis and treatment of OSA
A diagnosis of OSA is made when devices that record respiratory measurements show complete occlusion of the airway, known as apnea, or partial occlusion, which is defined as a >. Side effects such as allergies, sores on the bridge of the nose, and mask leaks are a constant challenge to adherence to this treatment device (Chokroverty, 1999; Stevens, 2004; Personal communication, Dr. D. Hooper, Sleep Laboratory, Durban, South Africa, June, 2006; Veale et al. al. 2002).
Economic implications of OSA
An example is that of a patient with OSA and a persistently high blood pressure that is not controlled by standard hypertensives. With increased awareness of OSA for clinicians, it seems pertinent to investigate practical ways to address this condition by first-line primary health care clinicians.
OSA and clinical health psychology
The clinical health psychology model is patient-centered and focuses on health promotion rather than disease prevention within the social structure of a primary care medical setting (Schlebusch, 1990). Objective surveys such as the PSG provide this extension, but questionnaires are often the basic assessment that can be used in primary care (Netzer et al. 1999).
PSYCHOMETRIC AND DIAGNOSTIC PROPERTIES OF THE BQ AND HYPNOPTT™
Introduction
Reliability suggests that the test is relatively error-free and that the associations between items are consistently accurate. Convergent evidence will be obtained if the measurements of the selected instrument correlate well with the BQ.
Persistent symptoms
The HypnoPTT™ as a diagnostic tool
The HypnoPTT™, as described, is one of the screening systems available in South Africa to doctors working in sleep medicine, at a cost of approximately R200,000. The ENT department at Albert Luthuli Hospital has started using portable screening equipment, with the assistance of the nursing staff (Personal communication, Dr.D. Hooper, Berea Sleep Laboratory, Durban, South Africa, November 2006). EEG waveforms are one of the most important markers of sleep pathology in scientific laboratories and are the backbone of PSG for documenting and analyzing sleep pathology.
However, the face validity of such a system is therefore strong, according to Olsen et al. 2003) report that the construct validity of the HypnoPTT™ system is reasonable and should be viewed with caution. The perception that screening equipment is invalid is rapidly changing given the clear advantage of doing home studies and the similarity of the raw data recorded and analyzed by digital software (Pitson and Stradling 1998; Personal communication, Dr. D. Hooper, Berea Sleep Laboratory, Durban, South Africa, June 2006; Stevens, 2004; Swartz, 2005).
METHODOLOGY 4.1. Design
- Hypotheses
- Patients
- Ethics and consent
- Procedure
- Data analysis
- Categorv 1 Snoring - 3 Questions
- Categorv 2 Sleepiness - 3 Questions
- Categorv 3 High blood pressure &
Patients completed the BQ after clinical evaluation before receiving instructions on how to use the HypnoPTT™. The doctor explained the facts about the nature of the BQ and the research project in detail to patients. He emphasized the fact that he is in no way dependent on the BQ responses to diagnose OS A. The BQ has no influence on the diagnostic procedure and is not part of it.
Second, the patient was informed about the BQ and consent was obtained to complete the questionnaire. The doctor reported that patients made very few inquiries; and found the BQ questionnaire generally user-friendly.
RESULTS
Patients and demographics
The following results are derived from the BQ questions (height and weight are verified by the doctor).
BQ data - Prevalence of symptoms
In response to the question of others observing breath-holding events during sleep, breathing pauses were noted almost every day (Figure 5-5). These patients were unaccompanied by a partner and/or slept alone – they simply did not know if they were holding their breath during sleep. In response to questions about not feeling refreshed after sleep, patients complained of sleepiness upon awakening (Figures 5-6).
On the question about daytime sleepiness (EDS respondents reported feeling sleepy almost every day (Figure 5-7). When reporting a history of high blood pressure, patients reported a known history of high blood pressure, and 66 (55%) said that this was also the case had no history or did not know that they had suffered from high blood pressure (Figure 5.10).
BO - Gender, culture and risk factor considerations
HypnoPTT™ data - Prevalence of symptoms and behaviour
This information was obtained from the physician's final report sent back to the referring physician. In addition, snoring rate, oxygen saturation trough value, and total snoring value are consistently reliable variables (Stevens, 2004; AASM Task Force Report, 1999). Correlations showing the relationship between physician scores and HypnoPTT™ variables used globally to assess OSA severity.
The majority of patients fell within the >14 range, which international criteria suggest falls within the abnormal range. The number of arousals during the night varied between 15 and 140, and the majority of subjects experienced it.
Construct validity - Comparison of objective and subjective data
While a brief discussion of validity measures will be explored, the primary focus of this study is construct validity. There is current empirical evidence in other populations that the BQ represents robust clinical measures consistent with OSA symptoms, risk factors, and outcomes. At first glance, the questions clearly address factors that consistently focus on common symptoms such as sleep apnea, risk factors such as gender, history of high blood pressure and BMI, and behaviors such as snoring and sleepiness. day and while driving.
In questions about high blood pressure and BMI (category 3) with Cronbach's a at 0.18, are not reliable. Additional statistical information is available in Appendix G). A "total BQ" score was created as a variable against which the clinician's score was tabulated.
Risk factor category analysis
It was considered that the use of separate high-risk category analysis may be a more sensitive AHI predictor. Summary: The overall significance of the AHI/Category analysis model is a far more reliable measure of the sensitivity of the AHI classifications to predict the high-risk patient for OSA. Classification table showing predicted high-risk cases for OSA using the AHI classifications and the high-risk categories - snoring, sleepiness and BP/BMI.
Parameter estimates and case classification show that in this model the BQ high-risk symptom categories are able to identify 54% of cases in the normal 0-5 range, which is effectively the low-risk group. This model identified no cases in the moderate range, but identified 26% of the severe AHI range - >30 high-risk cases (Table 5-3) (Appendix K).
DISCUSSION
Demographics and BO findings
A BMI >30 kg/m2 and a history of high blood pressure were reported by 57% of subjects. From the final analysis of the HypnoPTT™ objective, the mean heart was not used for analysis. The physician score was found to be a reliable indicator of severity levels from the HypnoPTT™ data.
The group studied in this study is clearly at risk in terms of experienced deep sleep fragmentation and the subsequent consequences that may arise from it. Productivity is also affected, impacting the social and occupational aspects of the patient's life (Rosekind, 2005).
Validity and reliability findings
Second, they may not have spent enough time thinking about reactions in the presence of the doctor. A look at the bar graph rating of frequencies of breath-hold events and the AHI, which is effectively the objective measurement for this parameter, visually illustrates the inability of the patients to categorically rate breath-hold events (Appendix K). However, these validity measures cannot be extrapolated based on individual demand for the BQ, as no consistent correlations were found between the physician's result and any single BQ parameters.
However, the construct validity of the BQ is supported by the correlation of the BQ total score and the objective data. A moderate and significant correlation was observed between BQ score and nadir oxygen saturation (r = -.42, p <0.01).
Risk factor analysis findings
Implication of findings
Limitations of the current study and recommendations for future research
Portable sleep studies are increasingly proving to be reliable, cost-effective and convenient devices for diagnosing sleep apnea and may certainly prove to be the way forward in primary health care facilities in South Africa where resources are limited and health promotion strategies need to be refined (Personal communication, Dr. D. Hooper, Berea Sleep Laboratory, January 2006; Stradling et al. 2002; Stradling and Davies, 2004; Petersen Foster et al. 1997; Keleher, 2001; Naidoo and Wills, 2000). In defense, however, the AHI scores were classified into mild, moderate, and severe for most of the statistical analyses, and other researchers consistently find readings to fall within these categories (Stevens, 2004). Grants in the future should focus on helping researchers investigating sleep disorders, especially - OS A.
The researcher of this study attempted to work with patients in a primary care setting, but was unsuccessful. We considered this study as a pilot study for the future to further investigate the validity of the BQ and to conduct epidemiological studies.
Conclusion and recommendations
Sleep on the cheap: the role of overnight oximetry in the diagnosis of sleep apnea hypopnea syndrome. Value of beat-to-beat blood pressure changes, detected by pulse transit time, in the management of obstructive sleep. Validity of the modified Berlin Questionnaire to identify patients at risk for obstructive sleep apnea syndrome.
Identifying quality of life problems with obstructive sleep apnea at the time of initiation of continuous positive airway pressure: A discourse analysis. You have been asked to participate in a research study to determine whether a basic obstructive sleep apnea (OSA) questionnaire can be used to diagnose OSA.
RESULTS FOR CATEGORY 3 BO DATA - BLOOD PRESSURE AND BMI
- Snoring Valid
- Sleepiness Valid
- Case BQ & AHI Ratings (Unstable)
- BQ Categories & AHI Ratings (Stable)
Holding your breath during sleep How often are you tired or fatigued according to your sleep BQ data. Results of multiple regression coefficients using the lowest oxygen saturation value as the dependent variable against BQ questions 3-10. Multiple regression analysis showing the results of using total snoring as the dependent variable against BQ questions 3-10.
Multinomial regression analysis using AHI estimates as dependent variable and BQCase (high-risk group) as independent variable. VISUAL COMPARISON OF OBJECTIVE RECORDING OF AHI AND SUBJECTIVE BREATH CALCULATION-.
