Blood pressure, heart rate, sympathetic nerve activity, and polysomnography were recorded during wakefulness and sleep in 10 patients with obstructive sleep apnea. Measurements were also obtained after treatment with continuous positive airway pressure (CPAP) in four patients. Awake sympathetic activity was also measured in 10 age-and sexmatched control subjects and in 5 obese subjects without a history of sleep apnea.Patients with sleep apnea had high levels of nerve activity even when awake (P < 0.001). Blood pressure and sympathetic nerve activity did not fall during any stage of sleep. Mean blood pressure was 92±4.5 mmHg when awake and reached peak levels of 116±5 and 127±7 mmHg during stage II sleep (n = 10) and rapid eye movement (REM) sleep (n = 5), respectively (P < 0.001). Sympathetic activity increased during sleep (P = 0.01) especially during stage II (133+9% above wakefulness; P = 0.006) and REM (141±13%; P = 0.007). Peak sympathetic activity (measured over the last 10 s of each apneic event) increased to 299+96% during stage H sleep and to 246±36% during REM sleep (both P < 0.001). CPAP decreased sympathetic activity and blood pressure during sleep (P < 0.03).We conclude that patients with obstructive sleep apnea have high sympathetic activity when awake, with further increases in blood pressure and sympathetic activity during sleep. These increases are attenuated by treatment with CPAP. (J. Clin. Invest. 1995. 96:1897-1904 Key words: sympathetic nerve activity * blood pressure -hypertension hypoxia

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Background: Body mass index (BMI) is the most widely used measure to diagnose obesity. However, the accuracy of BMI in detecting excess body adiposity in the adult general population is largely unknown. Methods: A cross-sectional design of 13 601 subjects (age 20-79.9 years; 49% men) from the Third National Health and Nutrition Examination Survey. Bioelectrical impedance analysis was used to estimate body fat percent (BF%). We assessed the diagnostic performance of BMI using the World Health Organization reference standard for obesity of BF%425% in men and435% in women. We tested the correlation between BMI and both BF% and lean mass by sex and age groups adjusted for race. Results: BMI-defined obesity (X30 kg m À2 ) was present in 19.1% of men and 24.7% of women, while BF%-defined obesity was present in 43.9% of men and 52.3% of women. A BMIX30 had a high specificity (men ¼ 95%, 95% confidence interval (CI), 94-96 and women ¼ 99%, 95% CI, 98-100), but a poor sensitivity (men ¼ 36%, 95% CI, 35-37 and women ¼ 49%, 95% CI, 48-50) to detect BF%-defined obesity. The diagnostic performance of BMI diminished as age increased. In men, BMI had a better correlation with lean mass than with BF%, while in women BMI correlated better with BF% than with lean mass. However, in the intermediate range of BMI (25-29.9 kg m À2 ), BMI failed to discriminate between BF% and lean mass in both sexes. Conclusions: The accuracy of BMI in diagnosing obesity is limited, particularly for individuals in the intermediate BMI ranges, in men and in the elderly. A BMI cutoff ofX30 kg m À2 has good specificity but misses more than half of people with excess fat. These results may help to explain the unexpected better survival in overweight/mild obese patients.

REM sleep is associated with profound sympathetic activation in normal subjects, possibly linked to changes in muscle tone. The hemodynamic and sympathetic changes during REM sleep could play a part in triggering ischemic events in patients with vascular disease.

Objective: We performed a systematic review and meta-analysis of studies that assessed the performance of body mass index (BMI) to detect body adiposity. Design: Data sources were MEDLINE, EMBASE, Cochrane, Database of Systematic Reviews, Cochrane CENTRAL, Web of Science, and SCOPUS. To be included, studies must have assessed the performance of BMI to measure body adiposity, provided standard values of diagnostic performance, and used a body composition technique as the reference standard for body fat percent (BF%) measurement. We obtained pooled summary statistics for sensitivity, specificity, positive and negative likelihood ratios (LRs), and diagnostic odds ratio (DOR). The inconsistency statistic (I2) assessed potential heterogeneity. Results: The search strategy yielded 3341 potentially relevant abstracts, and 25 articles met our predefined inclusion criteria. These studies evaluated 32 different samples totaling 31 968 patients. Commonly used BMI cutoffs to diagnose obesity showed a pooled sensitivity to detect high adiposity of 0.50 (95% confidence interval (CI): 0.43-0.57) and a pooled specificity of 0.90 (CI: 0.86-0.94). Positive LR was 5.88 (CI: 4.24-8.15), I 2 ¼ 97.8%; the negative LR was 0.43 (CI: 0.37-0.50), I 2 ¼ 98.5%; and the DOR was 17.91 (CI: 12.56-25.53), I 2 ¼ 91.7%. Analysis of studies that used BMI cutoffs X30 had a pooled sensitivity of 0.42 (CI: 0.31-0.43) and a pooled specificity of 0.97 (CI: 0.96-0.97). Cutoff values and regional origin of the studies can only partially explain the heterogeneity seen in pooled DOR estimates. Conclusion: Commonly used BMI cutoff values to diagnose obesity have high specificity, but low sensitivity to identify adiposity, as they fail to identify half of the people with excess BF%.

BACKGROUND Central sleep apnea is associated with poor prognosis and death in patients with heart failure. Adaptive servo-ventilation is a therapy that uses a noninvasive ventilator to treat central sleep apnea by delivering servo-controlled inspiratory pressure support on top of expiratory positive airway pressure. We investigated the effects of adaptive servo-ventilation in patients who had heart failure with reduced ejection fraction and predominantly central sleep apnea. METHODS We randomly assigned 1325 patients with a left ventricular ejection fraction of 45% or less, an apnea–hypopnea index (AHI) of 15 or more events (occurrences of apnea or hypopnea) per hour, and a predominance of central events to receive guideline-based medical treatment with adaptive servo-ventilation or guideline-based medical treatment alone (control). The primary end point in the time-to-event analysis was the first event of death from any cause, lifesaving cardiovascular intervention (cardiac transplantation, implantation of a ventricular assist device, resuscitation after sudden cardiac arrest, or appropriate lifesaving shock), or unplanned hospitalization for worsening heart failure. RESULTS In the adaptive servo-ventilation group, the mean AHI at 12 months was 6.6 events per hour. The incidence of the primary end point did not differ significantly between the adaptive servo-ventilation group and the control group (54.1% and 50.8%, respectively; hazard ratio, 1.13; 95% confidence interval [CI], 0.97 to 1.31; P = 0.10). All-cause mortality and cardiovascular mortality were significantly higher in the adaptive servo-ventilation group than in the control group (hazard ratio for death from any cause, 1.28; 95% CI, 1.06 to 1.55; P = 0.01; and hazard ratio for cardiovascular death, 1.34; 95% CI, 1.09 to 1.65; P = 0.006). CONCLUSIONS Adaptive servo-ventilation had no significant effect on the primary end point in patients who had heart failure with reduced ejection fraction and predominantly central sleep apnea, but all-cause and cardiovascular mortality were both increased with this therapy.

During sympathetic activation in normal humans, there is a predominance in the LF oscillation of blood pressure, RR interval, and sympathetic nerve activity. During sympathetic inhibition, the HF component of cardiovascular variability predominates. This relationship is best seen when power spectral components are normalized for total power. Synchronous changes in the LF and HF rhythms of both RR interval and MSNA during different levels of sympathetic drive are suggestive of common central mechanisms governing both parasympathetic and sympathetic cardiovascular modulation.

There is consensus among experts regarding some indicators of sleep quality among otherwise healthy individuals. Education and public health initiatives regarding good sleep quality will require sustained and collaborative efforts from multiple stakeholders. Future research should explore how sleep architecture and naps relate to sleep quality. Implications and limitations of the consensus recommendations are discussed.