Diagnostic predictors of obesity hypoventilation syndrome in patients suspected of having sleep disordered breathing
J Clin Sleep Med.2013 9(9):879-884.
Vladimir M. Macavei, M.D.; Kristofer J. Spurling, M.Sc.; Janine Loft, B.Sc. (Hons); Himender K. Makker, M.D., FRCP
Sleep and Ventilation Unit, Department of Respiratory Medicine, North Middlesex University Hospital, London, UK
Introduction: Obesity hypoventilation syndrome (OHS) is associated with significant morbidity and mortality and requires measurement of arterial pCO2 for diagnosis.
Objective: To determine diagnostic predictors of OHS among obese patients with suspected obstructive sleep apnoea/hypopnoea syndrome (OSAHS).
Methods: Retrospective analysis of data on 525 sleep clinic patients (mean age 51.4±12.7, 65.7% males, mean BMI 34.5±8.1). All patients had sleep studies and arterialised capillary blood gases were measured in obese subjects (BMI >30kg/m2).
Results: 65.5% were obese, 37.2% were morbidly obese (BMI>40 kg/m2); 52.3% had confirmed OSAHS. Hypercapnia (pCO2 >6 kPa or 45 mmHg) was present in 20.6% obese and 22.1% OSAHS patients. Analysis of OHS predictors showed significant correlations between pCO2 and BMI, FEV1, FVC, AHI, mean and minimum nocturnal SpO2, sleep time with SpO2 <90%, pO2 and calculated HCO3 from the CBG. PO2 and HCO3 were independent predictors of OHS explaining 27.7% of pCO2 variance (p<0.0001). A calculated HCO3 cut-off of >27 mmol/L had 85.7% sensitivity and 89.5% specificity for diagnosis of OHS, with 68.1% positive and 95.9% negative predictive value.
Conclusion: We confirmed a high prevalence of OHS in obese OSAHS patients (22.1%) and raised calculated HCO3 level (>27 mmol/L) to be a sensitive and specific predictor for the diagnosis of OHS.
Obesity is now considered a global epidemic, and it is projected that by the year 2025, 36% of females and 47% of males will be obese in the UK . This rise in obesity is likely to lead to an increase in respiratory consequences such as obesity-hypoventilation syndrome (OHS), previously known as Pickwickian syndrome . It is defined as a combination of obesity (body mass index [BMI] > 30 kg/m2) and daytime hypercapnia (pCO2 > 45 mm Hg or > 6 kPa) in the absence of other known causes of alveolar hypoventilation . Obesity is also a main risk factor for obstructive sleep apnea/hypopnea syndrome (OSAHS).
The need for early detection of obesity hypoventilation syndrome (OHS) is clear because delay in the diagnosis and treatment is associated with significant morbidity and mortality. If left untreated, OHS is associated with a mortality of 23% at 18 months following discharge from hospital; adequate treatment of OHS reduces this to 3%. In addition, untreated OHS patients are likely to require invasive mechanical ventilation with longer hospital stay .
In this study we aimed to determine the prevalence of obesity-hypoventilation syndrome among obese patients with suspected sleep apnea and to ascertain the validity of previously reported predictors of OHS.
This study included a retrospective analysis of data on 525 sleep clinic patients (mean age 51.4±12.7, 65.7% males, mean BMI 34.5±8.1). A total of 344 patients (65.5%) were obese, of which 128 (37.2%) were morbidly obese with a BMI > 40 kg/m2. All patients had sleep studies and capillary blood gases (CBG) were measured in obese subjects (BMI >30kg/m2). In our study, bicarbonate level was calculated from the CBG data using arterial pH and pCO2 partial pressure in Henderson-Hasselbalch formula.
We found a high prevalence of daytime hypercapnia (OHS) of 20.6% (71/344 patients) in obese patients attending sleep clinic. Prevalence of OHS increased with BMI as shown in Figure 1 from 10.9% (14/128) in class 1 obesity, 20.5% (18/88) in class 2 obesity, to 30.4% (39/128) in morbidly obese patients. The high prevalence in OHS obese patients in our study was mainly due to high prevalence of obstructive sleep apnea in our obese and hypercapnic obese patients – 80% and 86%, respectively. Therefore overall prevalence of OHS in obese sleep apnea patients (22.1%) was similar to prevalence in obese patients (20.6%).
Analysis of OHS predictors showed significant correlations between pCO2 and BMI, FEV1, FVC, AHI, mean and minimum nocturnal SpO2, sleep time with SpO2 <90%, pO2 and calculated HCO3 from the CBG.
Following stepwise multiple regression, pO2 and calculated HCO3 were found to be independent predictors of OHS, explaining 27.7% of pCO2 variance (p < 0.0001).
Logistic regression analysis was used to determine various bicarbonate thresholds and their statistical value in detecting daytime hypercapnia. A calculated bicarbonate threshold of 27 mmol/L was the most effective in detecting obesity hypoventilation syndrome,with 85.7% sensitivity and 89.5% specificity.
In a previous study using serum bicarbonate sampling, Mokhlesi et al. found after ROC curve analysis an identical HCO3 threshold of 27 mmol/L to have a sensitivity of 92% and a specificity of 50% in identifying OHS. The authors have suggested using serum bicarbonate in conjunction with other markers of OSAHS severity such as AHI when screening for OHS .
We conclude that early identification of daytime hypercapnia using simple clinical predictors can avoid invasive arterial blood gas sampling and reduce morbidity and mortality associated with OHS. A normal HCO3 value may exclude daytime hypercapnia, while an elevated bicarbonate and/or nocturnal hypoxia should guide clinicians to look for OHS. The outcome of this study has changed our clinical practice so that we routinely measure serum bicarbonate level on all obese patients followed by the measurement of capillary blood gas pCO2 in patients with raised HCO3 > 27 mmol/L. Therefore development of commercially available bicarbonate finger strips may further help with noninvasive screening for daytime hypercapnia, allowing an earlier diagnosis of OHS, especially in primary practice.
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