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Obstructive sleep apnea (OSA) occurs frequently in people with Down syndrome (DS) with reported prevalences ranging between 55% and 97%, compared to 1–4% in the neurotypical pediatric population. Sleep studies are often uncomfortable, costly, and poorly tolerated by individuals with DS. The objective of this study was to construct a tool to identify individuals with DS unlikely to have moderate or severe sleep OSA and in whom sleep studies might offer little benefit. An observational, prospective cohort study was performed in an outpatient clinic and overnight sleep study center with 130 DS patients, ages 3–24 years. Exclusion criteria included previous adenoid and/or tonsil removal, a sleep study within the past 6 months, or being treated for apnea with continuous positive airway pressure. This study involved a physical examination/medical history, lateral cephalogram, 3D photograph, validated sleep questionnaires, an overnight polysomnogram, and urine samples. The main outcome measure was the apnea-hypopnea index. Using a Logic Learning Machine, the best model had a cross-validated negative predictive value of 73% for mild obstructive sleep apnea and 90% for moderate or severe obstructive sleep apnea; positive predictive values were 55% and 25%, respectively. The model included variables from survey questions, medication history, anthropometric measurements, vital signs, patient’s age, and physical examination findings. With simple procedures that can be collected at minimal cost, the proposed model could predict which patients with DS were unlikely to have moderate to severe obstructive sleep apnea and thus may not need a diagnostic sleep study.

Objective The objective of the present study is to examine the craniofacial development of patients with Down syndrome (DS) and compare them with a neurotypical population. Methods This study is a cross-sectional analysis of lateral cephalometric radiographs of participants with DS. The study population consisted of children and young adults with DS aged 3–25 years. Cephalometric data were summarized by age and sex. Raw and normalized z-scores were computed. One-sample t tests were used to test whether mean z-scores differed from zero. The demographic characteristics between those with or without lateral cephalograms among all study participants were compared by Fisher’s exact tests. Results The study sample comprised of 27 participants with DS. Study subjects demonstrated a class III skeletal pattern. This was more pronounced in the older age groups as compared to younger age groups. Subjects also had an increased proportionate lower anterior face height to total facial height compared to normative standards. Gonial angles, mandibular plane angles, and airway measurements increased with age. Conclusions Patients with Down syndrome present typically with class III skeletal pattern and long lower anterior facial heights. In patients with Down syndrome, comprehensive phase of orthodontic treatment may be best initiated following cessation of growth.

Mining of scalable patterns hidden in financial time series is a challenging pattern recognition task in nature. Patterns of price movements in financial time series are highly scalable and highly dimensional, making pattern recognition in time series a computational complex data mining effort. Thus, data representation plays a very crucial role in ensuring the effectiveness of time series pattern recognition algorithm. A robust data representation technique not only reduces the dimensionality of the original time series data, but also retains the critical features of the original time series. This study proposes a dynamic time interval data representation approach that adapts to the nature of price movement in financial time series. Since the interval is determined by the price movement magnitude, the proposed data representation approach is more responsive in capturing the major price movements, yet maintaining its agenda in reducing the dimensionality of the raw financial time series data.

Purpose: To measure the intracompartmental pressures surrounding tibial fractures not exhibiting any clinical evidence of compartment syndrome. Our hypothesis was that pressures often exceed the recommended threshold of fasciotomy despite the absence of compartment syndrome, and hence diagnosis based on pressure measurements alone is unreliable. Methods: Thirteen consecutive patients with closed tibial shaft fractures without clinical suspicion of compartment syndrome, and who were planned for intramedullary nailing, were prospectively enrolled. Compartment pressures ( P ) in all four compartments of the affected leg were measured at the start of surgery and immediately after tibial reaming, and differential pressures (delta P ) were calculated based on the diastolic blood pressure prior to induction of anaesthesia. Results: No patients required reoperation in the post-operative period, as a result of an undiagnosed compartment syndrome. Using commonly quoted threshold pressure criteria, 62% (using P > 30 mmHg) and 23% of patients (using delta P < 30 mmHg) have been incorrectly diagnosed with compartment syndrome. Conclusions: We conclude that raised compartment pressures are frequently seen in patients with tibial shaft fractures; but in most cases, it does not equate to the presence of compartment syndrome. Diagnosis of compartment syndrome based on intracompartmental pressure measurements alone may result in unnecessary fasciotomies in a sizeable number of patients. Compartment syndrome remains a clinical diagnosis, and one which always needs to be considered when managing tibial fractures.