Obstructive sleep apnoea How to identify?
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1 Obstructive sleep apnoea How to identify? Walter McNicholas MD Newman Professor in Medicine, St. Vincent s University Hospital, University College Dublin, Ireland.
2 Potential conflict of interest None
3 Obstructive sleep apnoea syndrome Recurring apnoeas during sleep, usually due to obstruction of the oropharynx. One of the most prevalent chronic respiratory disorders: most common among males years. Usually defined in terms of frequency of breathing disturbances during sleep (> 5/hour), associated with daytime symptoms, particularly sleepiness. Substantial genetic basis (~ 40% of variability in population studies); typically brought to the surface by the development of obesity. Although most patients with sleep apnoea snore, only a small proportion of snorers have sleep apnoea. OSAS is an important risk factor for cardiovascular disease, particularly hypertension (~ 50%).
4 Mechanisms of obstructive apnoea
5 Balance of forces affecting upper airway patency Negative intrapharyngeal pressure Patency UA dilating muscles
6 Balance of forces affecting upper airway patency Obstruction Negative intrapharyngeal pressure UA dilating muscles
7 Continuous Positive Airway Pressure (CPAP)
8 Balance of forces affecting upper airway patency Obstruction Negative intrapharyngeal pressure UA dilating muscles Narrowing of UA
9 Pharyngeal narrowing in OSA (right hand image)
10 Oropharyngeal narrowing in OSAS Abnormalities of the upper airway can be categorised using the Mallampati score originally devised for anaesthetic practice
11 Prevalence of OSAS Measured by evaluating cessation/reduction of breathing during sleep Apnoea/Hypopnoea Index (AHI) Normal <5 events/hour of sleep The clinical syndrome (OSAS) combines clinical features with AHI Approx 25% adult males have AHI >5 Approx 4-9% of adult males have AHI > 5 and symptoms of OSAS AHI >15 Intimate relationship with obesity Should not be viewed as the cause of OSAS (No more than obesity as a cause of Type 2 Diabetes)
12
13 Epworth sleepiness scale Scale of 0-3 for likelihood of falling asleep in following situations sitting and reading watching TV sitting, inactive in a public place as a passenger in a car lying down to rest in the afternoon sitting talking to someone sitting quietly after a lunch without alcohol in a car, while stopped in traffic Scale: 0 24; > 8/9 regarded as excessive daytime sleepiness
14 Polysomnography vs Self-reported Measures in Patients With OSA. Weaver, Arch Otolaryngol Head Neck Surg, Similar findings from Kingshott (Edinburgh) in 103 patients (Thorax 1995) Addition of partner input did not improve relationship
15 Correlation of AHI with clinical features Probability AHI Clinical probability of OSAS based on history and examination compared with AHI obtained from full overnight PSG studies in 250 consecutive patients referred to SVUH with suspected OSA. Deegan ERJ 1996.
16 Did he have sleep apnoea?
17 ASDA/ATS/ERS Recommendations for Diagnosis of OSAS (Sleep,1999) 1. Excessive daytime sleepiness unexplained by other factors and/or 2. Two or more of the following symptoms: loud snoring, choking/gasping during sleep, recurrent nocturnal awakening, unrefreshing sleep, daytime fatigue, impaired concentration and 3. Overnight monitoring demonstrates five or more apnoeas plus hypopnoeas plus respiratory-effortrelated arousals (RERAs) per hour of sleep.
18 Current Solution for Sleep Assessment: Polysomnography (PSG) in Sleep Labs Benefits Produces gold standard data Clinical acceptance Regulatory acceptance Shortcomings Expensive - costs on average $1,000 - $2,000 per user per night Limited availability due to hospital/clinic setting User intrusiveness has implications for patient recruitment, data quality Thus, PSG is expensive and cumbersome: 90% of people with SDB are undiagnosed
19 Obstructive Apnoea Upper and lower panels represent a continuous recorder tracing showing the development of obstructive apnoea during REM sleep, which is terminated by an arousal with hyperventilation
20 Diagnostic Challenges in OSAS Current diagnostic criteria pose major resource problems related to overnight investigation, particularly given the high prevalence of OSAS. Not practical to perform PSG (or even in-lab monitoring) in every suspected case. Long waiting lists and most patients remain undiagnosed (estimates of 85% in some reports) Need to establish most cost efficient modalities of investigation - will likely involve home monitoring for most patients.
21 Home or Laboratory assessment? Advantages: Laboratory Greater sophistication of recordings On-line monitoring (only applies if technician in attendance) Disadvantages: Unfamiliar environment Cost factor (particularly if technician present throughout the night)
22 Home or Laboratory assessment? Advantages: Home Familiar environment Cost benefit v lab studies factor in failed studies Disadvantages: Lack of on-line monitoring of recordings Difficulty in patient set-up Thus, robust, simple and reliable recordings a priority Major area of current research.
23 Sleep oxymetry Simple way of confirming diagnosis in severe cases - good specificity Visual pattern recognition of recurring episodes of intermittent hypoxia less suited to automated analysis Less reliable in milder cases, where SDB episodes, particularly hypopnea, may be associated with little desaturation.
24 Pattern of Oxygen Desaturation in a Patient with Severe OSAS. Flemons WW. N Engl J Med 2002;347:
25 Multiple stepwise logistic regression analysis of the relationship between systemic hypertension and various independent variables (ESADA cohort study) ODI (Q2 vs Q1) ( ) Yes ODI (Q3 vs Q1) < ( ) Yes ODI (Q4 vs Q1) < ( ) Yes Age < ( ) Yes BMI < ( ) Yes Neck circumference < ( ) Yes Type 2 diabetes < ( ) Yes Hyperlipidemia < ( ) Yes ESS ( ) No COPD ( ) No AHI (Q2 vs Q1) ( ) No AHI (Q3 vs Q1) ( ) No AHI (Q4 vs Q1) ( ) No Gender (Women vs Men) ( ) No Smoking ( ) No Waist-to-hip ratio ( ) No Data on 5073 adult subjects referred for assessment of possible OSAS.
26 ECG in the diagnosis of OSAS Heart rate variability long recognised to be a feature of OSA (Guilleminault 1984) Bradycardia during apnoea with tachycardia during recovery Additional information may be obtained from fluctuations in QRS amplitude related to ribcage movements during respiration.
27 ECG (a.u.)/ EDR RESPIRATORY EFFORT (a.u.) ECG-derived respiratory signal TIME (s)
28 Holter ECG with Oxymetry v PSG Heneghan Sleep adults with suspected OSAS underwent simultaneous PSG and H-OX recordings. Automated algorithm determined AHI from H-OX. Correlation Coefficient 0.95; P < 0.001
29 Pulse transit time. Smith Thorax 1999 PTT fluctuates with changes in arterial wall stiffness has potential to identify apnoea and/or arousal.
30 Pulse transit time in the identification of apnoea and arousal. Pepin Chest 2005.
31 Sleep apnea diagnosis using Holter ECG including a nasal pressure recording. Pepin, Sleep Med unselected patients referred with symptoms suggesting sleep apnea underwent a PSG with simultaneous NP and Holter ECG recordings. Results similar when visual and automated analysis of Holter compared.
32 Watch-PAT100 has two finger sensors for peripheral arterial tonometry and pulse oximetry, both connected to an amplification unit. The unit also contains actigraphy. Peripheral arterial tonometry (PAT) determines the peripheral arterial vascular tone using a plethysmographic method on the finger. PAT is modulated by sympathetic activity, by peripheral blood pressure, and by the peripheral resistance of the vessels
33 SleepMinder TM : a no touch monitor for sleep and breathing evaluation Signals based on radiofrequency sensor (Radar)
34 SleepMinder AHI SleepMinder TM : a no touch monitor for sleep and breathing evaluation SleepMinder-PSG Signals based on radiofrequency sensor (Radar) AHI Estimation vs PSG: Correlation = 91% Bland-Altman plot PSG AHI Mean AHI (PSG-SM)
35 Why bother?
36 CPAP not as bad as you think!
37 Long-term cardiovascular effects of CPAP therapy in OSAS. Marin, Lancet 2005.
38 Summary Diagnosis of OSAS requires both clinical assessment and objective sleep monitoring While PSG is widely regarded as the gold standard for diagnosis, most patients can be reliably assessed by limited cardio-respiratory sleep studies. Oxymetry alone is clinically useful at the extremes of the clinical spectrum ie to rule in OSAS in severe cases and to rule out OSAS in cases with a low clinical probability. Addition of signals widely used in cardiology (Holter ECG) can improve diagnostic accuracy and help identify patients for further testing and treatment. The prevalence of OSAS makes ambulatory studies very desirable and recent technological advances in novel signal acquisition make this development feasible.
39 Acknowledgements Sleep Research Laboratory, St. Vincent s University Hospital, Dublin Conway Research Institute, University College Dublin
DECLARATION OF CONFLICT OF INTEREST
DECLARATION OF CONFLICT OF INTEREST Obstructive sleep apnoea How to identify? Walter McNicholas MD Newman Professor in Medicine, St. Vincent s University Hospital, University College Dublin, Ireland. Potential
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