Obstructive sleep apnea hypopnea syndrome is characterized by irregular and abnormal respiratory patterns during sleep. It is characterized by fatigue/tiredness, daytime sleepiness, poor concentration, signs of disturbed/irregular sleep such as snoring, restlessness and resuscitative breath spells after brief apneic episodes (1). It is defined as an apnea hypopnea index (AHI) greater than five episodes/events per hour on polysomnography (2).
It is estimated that 26% of all adults in US are at risk for obstructive sleep apnea hypopnea syndrome (3). It is estimated that the incidence and prevalence of obstructive sleep apnea (OSA) increases between ages 18 – 45 years (4). Obstructive sleep apnea is more prevalent in African-Americans when compared to Caucasians in the middle age groups (5). Obesity is the most common documented risk factor for OSA.
Other risk factors include craniofacial abnormalities, upper airway soft tissue abnormalities, smoking, etc. (6). Snoring and daytime sleepiness are the most common features of OSA. Severe OSA is associated with uncontrolled systemic hypertension, corpulmonale, cardiac arrhythmias, cerebrovascular accidents, increased errors in regular activities, accidents, polycythemia, increased risk of mortality of all causes by 3-6 fold when compared to general population (6).
Purpose of the study:
Screening for OSA is based on subjective assessment of symptoms such as reported snoring, day time sleepiness, fatigue, loss of concentration, etc. Most utilized instrument is Epworth Sleepiness Scale – questioner based on self-reported symptoms. By the time patient realizes that he has these symptoms, he or she is already at risk of the complications associated with OSA.
The purpose of the study was to look for statistically significant correlation between the physical findings during an exam and patient’s self-reported symptoms. The potential benefits would include improved screening by early identification of patients with OSA in sub-clinical/asymptomatic stage.
Adult patients at the Family Medicine Center at the Brooklyn Hospital Center presenting for their usual visits were asked to volunteer in the study by completing the questionnaire regarding their symptoms that might suggest presence of OSA. It was followed by brief physical exam done by research personnel. Physical exam specifically focused on tonsillar grading and Mallampati scale basically assessing upper airway anatomy. Both tonsillar grading and Mallampati scale routinely utilized in pre-anesthesia assessment to gauge the ease of intubation for general anesthesia purposes.
Statistical analysis was done utilizing SPSS software. Cross tabulation were used to draw associations between different self-reported symptoms and physical exam findings.
Total participants: 87
Total number of subjects already diagnosed with OSA: 16
Total number of subject on sleep medications: 20
Out of all the participants, more than 60% were overweight. 52% reported frequent snoring. 55% reported day time sleepiness and 59% reported tiredness in am. 45% reported poor concentration and 47% reported daytime sleeping. 37% reported waking up from sleep.
37% of participant had uncontrolled hypertension, 61 % had collar size above 17 (which in some studies reported to be an independent risk factor for OSA).
On physical exam, 47% of participants had tonsillar grading above 2 and 87% had Mallmpati score above 2 (less than full visibility of tonsils, uvula and soft palate).
We could not find any linear correlations between the subjective symptoms and the physical examinations. The correlation graph showed neither positive nor negative correlations.
Thus, at present time, self-reported symptoms remain the only method for screening for OSA.
Bias present in our study:
Sampling bias: as all the subjects were from the patient population in our hospital, there was a significant sampling bias.
Clinical susceptibility bias: obesity predisposes the patient for OSA. This bias was present in the entire study and could not have been eliminated due to our patient population unique characteristics.
Attrition bias: all of the subjects who reported taking sleeping medications were excluded from the study irrespective of their reported symptoms.