Due to its moderate specifi city (56%, 43%, and 37% for predicting mild to severe OSA, moderate-severe OSA, and severe OSA, respectively), the STOP-Bang questionnaire may result in false positives leading to unnecessary referrals for sleep studies.The predictive analysis at different cutoff values shows that a STOP-Bang score 0-2 essentially excludes patients with moderate-severe OSA, whereas a STOP-Bang score 5 or greater was highly specifi c for sleep apnea (~80%). 10 The specifi city of STOP-Bang questionnaire can also be improved by combining a STOP-Bang score with an elevated serum bicarbonate. 11The predictive values of each individual item in the STOPBang questionnaire appear different.2,12 The objective of this study was to explore the predictive performance of the different Background: Obstructive sleep apnea (OSA) is common among surgical patients. The STOP-Bang questionnaire is a validated screening tool with a high sensitivity. However, its moderate specifi city may yield fairly high false positive rate. We hypothesized that the specifi c combinations of predicting factors in the STOP-Bang questionnaire would improve its specifi city. Methods: After research ethics approval, consented patients were asked to complete the STOP-Bang questionnaire and then underwent sleep studies. The predictive performance of the STOP-Bang alternative scoring models was evaluated. Five hundred sixteen patients with complete data on the STOPBang questionnaire and polysomnography were reported. Results: When the STOP-Bang score was ≥ 3 (any 3 positive items), the sensitivity and specifi city for identifying moderate-severe OSA was 87% and 31%, respectively. The specifi city for any 2 positive items from the 4 STOP questions plus BMI > 35 kg/m 2 , male gender, or neck circumference > 40 cm for identifying moderate-severe OSA was 85%, 77%, and 79%, respectively. Compared with STOP-Bang score ≥ 3, the predicted probability for severe OSA of the specifi c combinations of STOP score ≥ 2 + male and STOP score ≥ 2 + BMI increased by 36% and 42%, respectively. For severe OSA, the specifi c combination of STOP score ≥ 2 + BMI + male demonstrated a specifi city of 97% and 86% increase in predicted probability versus any 4 positive items of STOPBang questionnaire. Conclusions:The specifi c constellations of predictive factors improved the specifi city of STOP-Bang questionnaire. For patients with STOP score ≥ 2, male gender, and BMI > 35 kg/m 2 were more predictive than age ≥ 50 and neck circumference > 40 cm. Keywords: obstructive sleep apnea, polysomnography, perioperative care, preoperative screening, sleep apnea questionnaire Citation: Chung F, Yang Y, Brown R, Liao P. Alternative scoring models of STOP-Bang questionnaire improve specifi city to detect undiagnosed obstructive sleep apnea. J Clin Sleep Med 2014;10(9):951-958. S C I E N T I F I C I N V E S T I G A T I O N ST he current estimated prevalence of moderate-severe obstructive sleep apnea (OSA, defi ned by an apnea-hypopnea index [AHI] > 15 events/h) is 17% among 50 to 7...

No abstract

The brain has been recognized as a prominent site of peptide biosynthesis for more than 30 years, and many neuropeptides are now known to be common to gut and brain. With these precedents in mind it is remarkable that adipose-derived peptides like leptin have attracted minimal attention as brain-derived putative neuromodulators of energy balance. This review outlines the evidence that several adipose-specific genes are also expressed in the central nervous system and pituitary gland. We, and others, confirmed that the genes for leptin, resistin, adiponectin, FIAF (fasting-induced adipose factor) and adiponutrin are expressed and regulated in these tissues. For example, leptin mRNA was readily detectable in human, rat, sheep and pig brain, but not in the mouse. Leptin expression in rat brain and pituitary was regulated through development, by food restriction, and following traumatic brain injury. In contrast, hypothalamic resistin mRNA was unaffected by age or by fasting, but was significantly depleted by food restriction in mouse pituitary gland. Similar results were seen in the ob/ob mouse, and we noted a marked reduction in resistin-positive hypothalamic nerve fibres. Resistin and fiaf mRNA were also upregulated in hypoxic/ischaemic mouse brain. Our studies on the regulation of neuronal adipokines were greatly aided by the availability of clonal hypothalamic neuronal cell lines. One of these, N-1, expresses both rstn and fiaf together with several other neuropeptides and receptors involved in energy homeostasis. Selective silencing of rstn revealed an autocrine/paracrine regulatory system, mediated through socs-3 expression that may influence the feedback effects of insulin and leptin in vivo. A similar convergence of signals in the pituitary gland could also influence anterior pituitary hormone secretion. In conclusion, the evidence is suggestive that brain and pituitary-derived adipokines represent a local regulatory circuit that may fine tune the feedback effects of adipose hormones in the control of energy balance.