In a cohort of 6,441 volunteers followed over an average of 8.2 years, Naresh Punjabi and colleagues find sleep-disordered breathing to be independently associated with mortality and identify predictive characteristics.

Kushida CA; Nichols DA; Holmes TH; Quan SF; Walsh JK; Gottlieb DJ; Simon RD; Guilleminault C; White DP; Goodwin JL; Schweitzer PK; Leary EB; Hyde PR; Hirshkowitz M; Green S; McEvoy LK; Chan C; Gevins A; Kay GG; Bloch DA; Crabtree T; Demen WC. Effects of continuous positive airway pressure on neurocognitive function in obstructive sleep apnea patients: the Apnea Positive Pressure Long-term Efficacy Study (APPLES). SLEEP 2012;35(12):1593-1602.

Study Objective: The Epworth Sleepiness Scale (ESS) has been used to detect patients with potential sleep disordered breathing (SDB). Recently, a 4-Variable screening tool was proposed to identify patients with SDB, in addition to the STOP and STOP-Bang questionnaires. This study evaluated the abilities of the 4-Variable screening tool, STOP, STOP-Bang, and ESS questionnaires in identifying subjects at risk for SDB. Methods: A total of 4,770 participants who completed polysomnograms in the baseline evaluation of the Sleep Heart Health Study (SHHS) were included. Subjects with RDIs ≥ 15 and ≥ 30 were considered to have moderate-to-severe or severe SDB, respectively. Variables were constructed to approximate those in the questionnaires. The risk of SDB was calculated by the 4-Variable screening tool according to Takegami et al. The STOP and STOP-Bang questionnaires were evaluated including variables for snoring, tiredness/sleepiness, observed apnea, blood pressure, body mass index, age, neck circumference, and gender. Sleepiness was evaluated using the ESS questionnaire and scores were dichotomized into < 11 and ≥ 11. Results:The STOP-Bang questionnaire had higher sensitivity to predict moderate-to-severe (87.0%) and severe (70.4%) SDB, while the 4-Variable screening tool had higher specifi city to predict moderate-to-severe and severe SDB (93.2% for both). Conclusions:In community populations such as the SHHS, high specifi cities may be more useful in excluding low-risk patients, while avoiding false positives. However, sleep clinicians may prefer to use screening tools with high sensitivities, like the STOP-Bang, in order to avoid missing cases that may lead to adverse health consequences and increased healthcare costs. S C I E N T I f I C I N V E S T I g A T I O N SP rimary care providers frequently decide whether or not patients are referred for obstructive sleep apnea evaluations. Due to fi nancial constraints, this decision must be made quickly and accurately during short patient visits. Accurate screening for sleep disordered breathing (SDB) is necessary to properly identify at-risk patients. Several tools have been proposed to rapidly identify these patients. Anecdotally, the Epworth Sleepiness Scale (ESS) has been used by primary care providers to identify patients with potential sleep disorders. However, the ESS was developed to measure propensity for sleep onset rather than the likelihood of SDB.1,2 Takegami et al. 3 proposed a 4-Variable screening tool with high sensitivity (0.93) and high specifi city (0.66) for determining SDB severity. This scale utilizes gender, blood pressure (BP), body mass index (BMI), and snoring. In addition, the STOP and STOP-Bang questionnaires, 4,5 two simple 4-and 8-item tools, also have been used to screen for SDB. However, these tools have been validated in different populations and clinical settings with differing results, leaving the clinician to wonder which tool best screens for SDB. We aimed to investigate this question by comparing the results of these 4 tools, ut...

The high quality of data collected in TuCASA demonstrates that multi-channel polysomnography data can be successfully obtained in children aged 5-12 years in an unattended setting under a research protocol.