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. 2008 Dec 15;4(6):543-50.

Clinical patterns of obstructive sleep apnea and its comorbid conditions: a data mining approach

Qi Rong Huang  1 , Zhenxing Qin, Shichao Zhang, Chin Moi Chow
Affiliations

Clinical patterns of obstructive sleep apnea and its comorbid conditions: a data mining approach

Qi Rong Huang et al. J Clin Sleep Med. .

Abstract

Objectives: Obstructive sleep apnea often results in a wide range of comorbid conditions. Although some conditions have been clearly identified as comorbid, a full clinical pattern of associated diseases has not been systematically documented. This research aimed to reveal the full pattern of comorbid conditions associated with OSA by employing a data mining technique.

Methods: A large data repository (the New South Wales inpatient Data Collection) collected between 1999 and 2004 was mined, and all clinical diagnoses were coded with ICD-10-AM codes.

Results: A total of 60,197 cases (4% of total records) were identified as related to OSA (72.2% males, 27.8% females). OSA occurrence showed 2 peaks at 0-4 years and 55-59 years. A strikingly low occurrence was observed for the adolescent years. Conditions comorbid with OSA in adults by descending frequency were essential hypertension, obesity, hypercholesterolemia, type 2 diabetes, past or current tobacco use, and ischemic heart conditions. Obesity and OSA showed a similar time course of onset, with a latent period of 5 years for hypertension and type 2 diabetes and 15 years for chronic ischemic heart conditions. Comorbid conditions were predominantly of the cardiovascular, endocrine/metabolic and respiratory systems. The data also indicated OSA patients are high users of health services.

Conclusions: The data mining technique confirms the prevalence of the disease, describes the age distribution patterns and time courses of disease development from obesity and OSAto comorbid conditions, and implicates possible interrelationships among these conditions and high cost of treating OSA patients.

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Figures

Figure 1
Figure 1
Age and gender distributions of OSA and total sample
Figure 2
Figure 2
Age distribution of OSA cases in males and females
Figure 3
Figure 3
Common comorbid conditions associated with OSA (% of each code is the number of count of a code over the total count of all codes in these 60,197 cases)
Figure 4
Figure 4
The age distribution of obesity and IDDM2 in OSA patients
Figure 5
Figure 5
Age distribution of hypertension and ischemic heart diseases (IHD) in OSA patients
Figure 6
Figure 6
Clusters of comorbid conditions by disease system/category. A-B: infectious and parasitic diseases; C&D: neoplasms, blood and immune system; E: endocrine – metabolic diseases; F: mental &behavioural disorders; G: nervous diseases; H: diseases of the eye, ear and mastoid process; I: circulatory diseases; J: respiratory diseases; K: digestive diseases; L: dermatological diseases; M: musculoskeletal system – connective tissue diseases; N: genitourinary diseases; Q: congenital malformations – chromosomal abnormalities; S-T: injury, poisoning – other consequence of external causes, V-X: External causes of morbidity and mortality; and Z: Factors influencing health status and contact with health services. O codes for “pregnancy, childbirth and the puerperium”, P codes for “certain condition originating in the perinatal period,” and R codes for “symptoms not elsewhere specified” were not included for this analysis.
Figure 7
Figure 7
Time courses of obesity, OSA, IDDM2, hypertension, and ischemic heart diseases (numbers on the Y axis are arbitrary, 1: onset at 1% occurrence, 10: peak occurrence)
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