Type III home sleep testing versus pulse oximetry: is the respiratory disturbance index better than the oxygen desaturation index to predict the apnoea-hypopnoea index measured during laboratory polysomnography?

OBJECTIVES: In its guidelines on the use of portable monitors to diagnose obstructive sleep apnoea, the American Academy of Sleep Medicine endorses home polygraphy with type III devices recording at a minimum airflow the respiratory effort and pulse oximetry, but advises against simple pulse oximetry. However, oximetry is widely available and simple to use in the home. This study was designed to compare the ability of the oxygen desaturation index (ODI) based on oximetry alone with a stand-alone pulse oximeter (SPO) and from the oximetry channel of the ApneaLink Plus (ALP), with the respiratory disturbance index (RDI) based on four channels from the ALP to predict the apnoea-hypopnoea index (AHI) from laboratory polysomnography. DESIGN: Cross-sectional diagnostic accuracy study. SETTING: Sleep medicine practice of a multispecialty clinic. PARTICIPANTS: Patients referred for laboratory polysomnography with suspected sleep apnoea. We enrolled 135 participants with 123 attempting the home sleep testing and 73 having at least 4 hours of satisfactory data from SPO and ALP. INTERVENTIONS: Participants had home testing performed simultaneously with both a SPO and an ALP. The 2 oximeter probes were worn on different fingers of the same hand. The ODI for the SPO was calculated using Profox software (ODI(SOX)). For the ALP, RDI and ODI were calculated using both technician scoring (RDI(MAN) and ODI(MAN)) and the ALP computer scoring (RDI(RAW) and ODI(RAW)). RESULTS: The receiver-operator characteristic areas under the curve for AHI ≥ 5 were RDI(MAN) 0.88 (95% confidence limits 0.81-0.96), RDI(RAW) 0.86 (0.76-0.94), ODI(MAN) 0.86 (0.77-0.95), ODI(RAW) 0.84 (0.75-0.93) and ODI(SOX) 0.83 (0.73-0.93). CONCLUSIONS: We conclude that the RDI and the ODI, measured at home on the same night, give similar predictions of the laboratory AHI, measured on a different night. The differences between the two methods are small compared with the reported night-to-night variation of the AHI.

Genetic variants associated with sleep disorders.

OBJECTIVE: The diagnostic boundaries of sleep disorders are under considerable debate. The main sleep disorders are partly heritable; therefore, defining heritable pathophysiologic mechanisms could delineate diagnoses and suggest treatment. We collected clinical data and DNA from consenting patients scheduled to undergo clinical polysomnograms, to expand our understanding of the polymorphisms associated with the phenotypes of particular sleep disorders. METHODS: Patients at least 21 years of age were recruited to contribute research questionnaires, and to provide access to their medical records, saliva for deoxyribonucleic acid (DNA), and polysomnographic data. From these complex data, 38 partly overlapping phenotypes were derived indicating complaints, subjective and objective sleep timing, and polysomnographic disturbances. A custom chip was used to genotype 768 single-nucleotide polymorphisms (SNPs). Additional assays derived ancestry-informative markers (eg, 751 participants of European ancestry). Linear regressions controlling for age, gender, and ancestry were used to assess the associations of each phenotype with each of the SNPs, highlighting those with Bonferroni-corrected significance. RESULTS: In peroxisome proliferator-activated receptor gamma, coactivator 1 beta (PPARGC1B), rs6888451 was associated with several markers of obstructive sleep apnea. In aryl hydrocarbon receptor nuclear translocator-like (ARNTL), rs10766071 was associated with decreased polysomnographic sleep duration. The association of rs3923809 in BTBD9 with periodic limb movements in sleep was confirmed. SNPs in casein kinase 1 delta (CSNK1D rs11552085), cryptochrome 1 (CRY1 rs4964515), and retinoic acid receptor-related orphan receptor A (RORA rs11071547) were less persuasively associated with sleep latency and time of falling asleep. CONCLUSIONS: SNPs associated with several sleep phenotypes were suggested, but due to risks of false discovery, independent replications are needed before the importance of these associations can be assessed, followed by investigation of molecular mechanisms.

Genotyping sleep disorders patients.

OBJECTIVE: The genetic susceptibility factors underlying sleep disorders might help us predict prognoses and responses to treatment. Several candidate polymorphisms for sleep disorders have been proposed, but there has as yet inadequate replication or validation that the candidates may be useful in the clinical setting. METHODS: To assess the validity of several candidate associations, we obtained saliva deoxyribonucleic acid (DNA) samples and clinical information from 360 consenting research participants who were undergoing clinical polysomnograms. Ten single nucleotide polymorphisms (SNPs) were genotyped. These were thought to be related to depression, circadian sleep disorders, sleep apnea, restless legs syndrome (RLS), excessive sleepiness, or to slow waves in sleep. RESULTS: With multivariate generalized linear models, the association of TEF rs738499 with depressive symptoms was confirmed. Equivocal statistical evidence of association of rs1801260 (the C3111T SNP in the CLOCK gene) with morningness/eveningness and an association of Apolipoprotein E (APOE) rs429358 with the Epworth Sleepiness Scale (ESS) were obtained, but these associations were not strong enough to be of clinical value by themselves. Predicted association of SNPs with sleep apnea, RLS, and slow wave sleep were not confirmed. CONCLUSION: The SNPs tested would not, by themselves, be of use for clinical genotyping in a sleep clinic.

Meta-analyses of hypnotics and infections: eszopiclone, ramelteon, zaleplon, and zolpidem.

STUDY OBJECTIVES: Recent meta-analyses raising concern about risks of hypnotics suggest a need for more clarification of these risks. METHODS: Because of preliminary suggestions that eszopiclone causes infections, we studied US Food and Drug Administration files on the 4 most-recently approved hypnotics, combined with published studies, to compile the risk ratios of infections for groups randomly assigned to receive hypnotics versus those assigned to receive placebos in controlled trials. Parallel controlled clinical trials of eszopiclone, ramelteon, zaleplon, and zolpidem were included when data on subjects, duration of exposure, and adverse effects were available. Results of trials were combined by meta-analyses. RESULTS: Of 8828 participants assigned to the 4 hypnotics and 4383 participants who randomly received placebos, 606 in the hypnotics groups and 200 in the placebo groups were reported to develop some kind of infection (risk ratio = 1.44, 95% confidence interval 1.25-1.64, p < 0.00001). Most infections were apparently mild and did not lead to dropouts. Subanalyses for individual drugs indicated that eszopiclone and zolpidem individually were associated with reported infections. There were insufficient data concerning individual studies of zaleplon and ramelteon for valid secondary meta-analyses of zaleplon or ramelteon by themselves. CONCLUSIONS: Research is needed to objectively determine whether the use of hypnotics increases the risk of infections. Immune compromise or esophageal reflux and aspiration should be studied as possible mechanisms.

CPAP therapy of obstructive sleep apnea in type 2 diabetics improves glycemic control during sleep.

BACKGROUND: Type 2 diabetes and obstructive sleep apnea (OSA) are frequently comorbid conditions. OSA is associated with increased insulin resistance, but studies of continuous positive airway pressure (CPAP) have shown inconsistent effects on glycemic control. However, endpoints such as hemoglobin A1c and insulin sensitivity might not reflect short-term changes in glycemic control during sleep. METHODS: We used a continuous glucose-monitoring system to measure interstitial glucose every 5 minutes during polysomnography in 20 patients with type 2 diabetes and newly diagnosed OSA. The measurements were repeated after an average of 41 days of CPAP (range 26-96 days). All patients were on a stable diet and medications. Each 30-second epoch of the polysomnogram was matched with a continuous glucose-monitoring system reading, and the sleeping glucose level was calculated as the average for all epochs scored as sleeping. RESULTS: The mean sleeping glucose decreased from untreated (122.0 +/- 61.7 mg/dL) to treated (102.9 +/- 39.4 mg/dL; p = 0.03 by Wilcoxon paired rank test). The sleeping glucose was more stable after treatment, with the median SD decreasing from 20.0 to 13.0 mg/dL (p = 0.005) and the mean difference between maximum and minimum values decreasing from 88 to 57 mg/dL (p= 0.003). The change in the mean hemoglobin A1c from 7.1% to 7.2% was not significant. CONCLUSIONS: Our study is limited by the lack of a control group, but the results suggest that sleeping glucose levels decrease and are more stable after patients with type 2 diabetes and OSA are treated with CPAP.

Melatonin effects on luteinizing hormone in postmenopausal women: a pilot clinical trial NCT00288262.

BACKGROUND: In many mammals, the duration of the nocturnal melatonin elevation regulates seasonal changes in reproductive hormones such as luteinizing hormone (LH). Melatonin's effects on human reproductive endocrinology are uncertain. It is thought that the same hypothalamic pulse generator may both trigger the pulsatile release of GnRH and LH and also cause hot flashes. Thus, if melatonin suppressed this pulse generator in postmenopausal women, it might moderate hot flashes. This clinical trial tested the hypothesis that melatonin could suppress LH and relieve hot flashes. METHODS: Twenty postmenopausal women troubled by hot flashes underwent one week of baseline observation followed by 4 weeks of a randomized controlled trial of melatonin or matched placebo. The three randomized treatments were melatonin 0.5 mg 2.5-3 hours before bedtime, melatonin 0.5 mg upon morning awakening, or placebo capsules. Twelve of the women were admitted to the GCRC at baseline and at the end of randomized treatment for 24-hour sampling of blood for LH. Morning urine samples were collected twice weekly to measure LH excretion. Subjective responses measured throughout baseline and treatment included sleep and hot flash logs, the CESD and QIDS depression self-ratings, and the SAFTEE physical symptom inventory. RESULTS: Urinary LH tended to increase from baseline to the end of treatment. Contrasts among the 3 randomized groups were statistically marginal, but there was relative suppression combining the groups given melatonin as contrasted to the placebo group (p < 0.01 one-tailed, Mann-Whitney U = 14). Similar but not significant results were seen in blood LH. There were no significant contrasts among groups in hot flashes, sleep, depression, or side-effect measures and no significant adverse effects of any sort. CONCLUSION: The data are consistent with the hypothesis that melatonin suppresses LH in postmenopausal women. An effect related to the duration of nocturnal melatonin elevation is suggested. Effects of melatonin on reproductive endocrinology should be studied further in younger women and in men. Larger studies of melatonin effects on postmenopausal symptoms would be worthwhile.

Nasal cytology: a marker of clinically silent inflammation in patients with obstructive sleep apnea and a predictor of noncompliance with nasal CPAP therapy.

STUDY OBJECTIVES: Patients with obstructive sleep apnea treated with nasal continuous positive airway pressure (CPAP) often complain of nasal side effects. We studied patients before and after initiation of nasal CPAP to see how treatment affected nasal function and markers of nasal inflammation. We searched for pretreatment findings that might help to predict noncompliance. METHODS: Nasal symptom scores, nasal flow by anterior rhinomanometry, mediator levels (intercellular adhesion molecule-1, interleukin-6, interleukin-8 and interleukin-13), and nasal scrapes for cytology were obtained at baseline and monthly for up to 3 months of nasal CPAP therapy. Compliance was assessed from the patient's report and by recording hours of usage for up to 19 months of follow-up. RESULTS: Thirty-eight patients with newly diagnosed obstructive sleep apnea were classified as having no rhinitis (42%), allergic rhinitis (37%), or nonallergic rhinitis (21%). There was no significant difference in compliance in patients with and without rhinitis. Compliant and noncompliant patients showed no significant differences in their baseline nasal symptom scores, nasal flow, and mediator levels. Nasal neutrophil counts before treatment were greater in noncompliant than in compliant patients (p = .004) and greater in those discontinuing because of nasal symptoms than in patients who quit for other reasons (p = .05). There was a positive correlation between neutrophil counts and nasal bacterial scores, both before and after treatment with nasal CPAP. CONCLUSIONS: Patients with increased neutrophil counts in the nasal scrape before beginning nasal CPAP are at increased risk of discontinuing therapy. They appear to have subclinical nasal inflammation that cannot be identified from clinical assessment, nasal symptom scores or rhinomanometry.