The relationship between obstructive sleep apnea and asthma severity and vice versa: a systematic review and meta-analysis.

BACKGROUND: There is a great association between the prevalence of obstructive sleep apnea (OSA) and asthma. Nonetheless, whether OSA impacts lung function, symptoms, and control in asthma and whether asthma increases the respiratory events in OSA are unknown. This meta-analysis aimed to examine the relationship between obstructive sleep apnea and asthma severity and vice versa. METHODS: We carried out a systematic search of PubMed, EMBASE, and Scopus from inception to September 2022. Primary outcomes were lung function, parameters of polysomnography, the risk of OSA in more severe or difficult-to-control asthmatic patients, and the risk of asthma in patients with more severe OSA. Heterogeneity was examined with the Q test and I2 statistics. We also performed subgroup analysis, Meta-regression, and Egger's test for bias analysis. RESULTS: 34 studies with 27,912 subjects were totally included. The results showed that the comorbidity of OSA aggravated lung function in asthmatic patients with a consequent decreased forced expiratory volume in one second %predicted (%FEV1) and the effect was particularly evident in children. %FEV1 tended to decrease in adult asthma patients complicated with OSA, but did not reach statistical significance. Interestingly, the risk of asthma seemed to be slightly lower in patients with more severe OSA (OR = 0.87, 95%CI 0.763-0.998). Asthma had no significant effect on polysomnography, but increased daytime sleepiness assessed by the Epworth Sleepiness Scale in OSA patients (WMD = 0.60, 95%CI 0.16-1.04). More severe asthma or difficult-to-control asthma was independently associated with OSA (odds ratio (OR) = 4.36, 95%CI 2.49-7.64). CONCLUSION: OSA was associated with more severe or difficult-to-control asthma with decreased %FEV1 in children. The effect of OSA on lung function in adult patients should be further confirmed. Asthma increased daytime sleepiness in OSA patients. More studies are warranted to investigate the effect of asthma on OSA severity and the impact of different OSA severity on the prevalence of asthma. It is strongly recommended that people with moderate-to-severe or difficult-to-control asthma screen for OSA and get the appropriate treatment.

Association Between Smoking Behavior and Obstructive Sleep Apnea: A Systematic Review and Meta-Analysis.

INTRODUCTION: To systematically review the association between smoking behavior and obstructive sleep apnea (OSA). AIMS AND METHODS: PubMed, Medline, the Cochrane Library, EMBASE, and Scopus databases were used to conduct this review. The two researchers independently screened the literatures, conducted the quality assessment, and data extraction according to the inclusion and exclusion criteria. The RevMan 5.3 was used to analysis the apnea hypopnea index (AHI) index, min saturation of oxyhemoglobin (SaO2), Epworth Sleepiness Scale (ESS) score, and oxygen desaturation index (DOI) and publication bias analysis to assess the effect of smoking on OSA patients. Furthermore, we performed subgroup of the severity of OSA, different countries of sample origin (western countries or eastern countries), and pack-years (PYs < 10 or PYs ≥ 20) to analyze the heterogeneity. RESULTS: Thirteen studies were included in this analysis that conformed to inclusion criteria and exclusion criteria. Totally 3654 smokers and 9796 non-smokers have participated. The meta-analysis of 13 studies demonstrated that AHI levels were significantly higher in smoker group compared with non-smoker, ESS scores were also significantly higher in smoker group compared with non-smoker, min SaO2 levels were obviously lower in smoker group compared with non-smoker, however, DOI levels hadn't significantly different between two groups. The subgroup analysis showed that there was an association between severe OSA, eastern countries, pack-years, and smoking. CONCLUSIONS: Smoking behavior is a significant association with OSA. Heavy smokers with histories of more than 20 PYs were at a higher risk of OSA. Moreover, patient with severe OSA exhibited a significantly association with smoking compared with patients with mild or moderate OSA. IMPLICATIONS: The relationship between smoking and OSA was controversial, especially, whether smoking increase or aggravate the risk of OSA. In our review and meta-analysis, we demonstrated that smoking behavior is a significant association with OSA. Heavy smokers with histories of more than 20 PYs were at a higher risk of OSA. Moreover, patient with severe OSA exhibited a significant association with smoking compared with patients with mild or moderate OSA. More prospective long-term follow-up studies about effect of quit smoking on OSA are recommended to establish the further relationship.

Application value of joint NoSAS score and Epworth Sleepiness Scale for assessment of obstructive sleep apnea hypopnea syndrome.

OBJECTIVE: By comparing the predictive value of the NoSAS (Neck circumference, Obesity, Snoring, Age and Sex) score combined with the Epworth Sleepiness Scale (ESS), STOP-Bang Questionnaire (STOP-Bang), STOP Questionnaire (STOP) and Berlin Questionnaire (Berlin), the application value of the NoSAS score combined with ESS in screening Obstructive sleep apnea hypopnea syndrome (OSAHS) in the population is evaluated. METHOD: 2560 suspected OSAHS patients visited the Sleep Medical Center of the First Hospital of Guangzhou Medical University between September 1, 2016 and October 31, 2020, and were monitored with a polysomnogram (PSG) after completing the NoSAS score, ESS, STOP-Bang, STOP and Berlin. The sensitivity, specificity, positive predictive value, negative predictive value and receiver operating characteristic (ROC) curve of each scale were calculated, and the accuracy in predicting OSAHS of the NoSAS score combined with ESS and each scale was analyzed. RESULTS: The areas under the ROC curve scored by Berlin were higher than those of the other four questionnaires with Apnea Hypopnea Index (AHI) cutoffs of ≥5 and ≥ 10 events/h, while the area under the ROC curve scored by the NoSAS score was the highest with AHI cutoffs of ≥15, ≥20, ≥25 and ≥ 30 events/h. Among the five scales, the diagnostic odds ratio (DOR) of the NoSAS score was the highest. When a NoSAS score of ≥7 was used as the cutoff point for diagnostic NoSAS, it had higher sensitivity and specificity with a NoSAS score of ≥8 as the cutoff point for diagnostic NoSAS. A NoSAS score of ≥7 combined with ESS significantly improved its specificity for predicted OSAHS patients. CONCLUSION: The NoSAS score is a simple and effective new tool for screening patients for OSAHS, while a NoSAS score of ≥7 combined with ESS can further improve its specificity. Thus, we suggest further screening with ESS after a NoSAS score of ≥7 in suspected populations.

Development and validation of a clinical model to predict hypertension in consecutive patients with obstructive sleep apnea hypopnea syndrome: a hospital-based study and nomogram analysis.

BACKGROUND: To screen for risk predictors of hypertension in patients with Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) and develop and validate a clinical model for individualized prediction of hypertension in consecutive patients with OSAHS. METHODS: 114 consecutive patients with OSAHS confirmed by PSG monitoring participated in this study. Those individuals were divided into two sets at a ratio of 7:3, using computer-generated random numbers: 82 individuals were assigned to the training set and 32 to the validation set. Important risk predictors of hypertension in individuals with OSAHS were confirmed using the LASSO method and a clinical nomogram constructed. The predictive accuracy was assessed by unadjusted concordance index (C-index) and calibration plot. RESULTS: Univariate and multivariate regression analysis identified BMI, REM-AHI, REM-MSpO2 and T90% as predictive risk factors of OSAHS. Those risk factors were used to construct a clinical predictive nomogram. The calibration curves for hypertension in patients with OSAHS risk revealed excellent accuracy of the predictive nomogram model, internally and externally. The unadjusted concordance index (C-index) for the training and validation set was 0.897 [95% CI 0.795-0.912] and 0.894 [95% CI 0.788-0.820] respectively. The AUC of the training and validation set was 0.8175882 and 0.8031522, respectively. Decision curve analysis showed that the predictive model could be applied clinically when the threshold probability was 20 to 80%. CONCLUSION: We constructed and validated a clinical nomogram to individually predict the occurrence of hypertension in patients with OSAHS. We determined that BMI, REM-AHI, REM-MSpO2 and T90% were independent risk predictors for hypertension in patients with OSAHS. This practical prognostic nomogram may help improve clinical decision making.

The effect of non-benzodiazepine sedative hypnotics on CPAP adherence in patients with OSA: a systematic review and meta-analysis.

STUDY OBJECTIVES: This meta-analysis aimed to explore the effect of non-benzodiazepine sedative hypnotics (NBSH) on continuous positive airway pressure (CPAP) adherence in patients with obstructive sleep apnea (OSA). METHODS: We conducted a systematic search through PubMed, Medline, the Cochrane Library, EMBASE, Scopus and ClinicalTrials (all searched from inception to August 15, 2020). Publications were limited to articles, clinical conferences and letters, including randomized controlled trials and retrospective studies. We used a random-effects model to calculate the odds ratio (OR) and mean difference (MD) with corresponding confidence interval (CI). Subgroup analyses were conducted to analyze the sources of heterogeneity. RESULTS: Eight studies fulfilled the inclusion and exclusion criteria for patients newly diagnosed with obstructive sleep apnea. Overall, the use of NBSH was associated with increased use of CPAP per night (MD = 0.62 h; 95% CI = 0.26-0.98) and use for more nights (MD = 12.08%; 95% CI = 5.27-18.88). When a study seriously affecting heterogeneity was removed, more patients adhered well with CPAP use (pooled OR = 2.48; 95% CI = 1.75-3.52) with good adherence defined as CPAP use for >4 h/night on >70% of nights. Among prescribed NBSHs, eszopiclone showed the most significant effect on CPAP adherence. CONCLUSION: CPAP adherence may increase in OSA patients treated with non-benzodiazepine sedative hypnotics especially eszopiclone. The effect of zolpidem and zaleplon on CPAP adherence requires further investigation by larger scale, randomized, controlled trials.