Search Results (3)

Obstructive sleep apnea (OSA) is a common disease that is often under-diagnosed and under-treated in all ages. This is due to differences in morphology, diversity in clinical phenotypes, and differences in diagnosis and treatment of OSA in children and adults, even among individuals of the same age. Therefore, a personalized medicine approach to diagnosis and treatment of OSA is necessary for physicians in clinical practice. In children and adults without serious underlying medical conditions, polysomnography at sleep labs may be an inappropriate and inconvenient testing modality compared to home sleep apnea testing. In addition, the apnea–hypopnea index should not be considered as a single parameter for making treatment decisions. Thus, the treatment of OSA should be personalized and based on individual tolerance to sleep-quality-related parameters measured by the microarousal index, harmful effects of OSA on the cardiovascular system related to severe hypoxia, and patients’ comorbidities. The current treatment options for OSA include lifestyle modification, continuous positive airway pressure (CPAP) therapy, oral appliance, surgery, and other alternative treatments. CPAP therapy has been recommended as a cornerstone treatment for moderate-to-severe OSA in adults. However, not all patients can afford or tolerate CPAP therapy. This narrative review seeks to describe the current concepts and relevant approaches towards personalized management of patients with OSA, according to pathophysiology, cluster analysis of clinical characteristics, adequate combined therapy, and the consideration of patients’ expectations. Full article

Background: Obstructive sleep apnea (OSA) is a common disorder and can lead to many severe complications; however, the majority of patients remain undiagnosed. Although polysomnography (PSG) remains the gold standard of diagnosis, it is usually uncomfortable and costly for patients. Purpose: The study aims to assess the agreement of the AHI measured by polygraphy (PG) (Philips Alice NightOne) with that of polysomnography (Philips Alice PDx) simultaneously recorded in-lab. Methods: A total of 11 voluntary participants over 18 years old underwent one night of simultaneous PSG and PG recording in sleep laboratories. Studied parameters (AHI, OAI, CAI, MAI, and minSpO2) were analyzed and reported by the Philips Sleepware G3 software. PSG and PG results were scored by qualified staff. Results: In terms of AHI, the mean AHI derived from PG was different from that of PSG—7.78 and 2.37 events/h, respectively. A Bland–Altman analysis of the AHI on PSG versus PG showed a mean difference of 5.41; limits of agreement (equal to ±2 standard deviations) were from −6.74 to 17.56. The Bland–Altman analysis showed a slight difference between the two methods, with a mean difference of −0.12 events/h in CAI, 1.35 events/h in OAI, and 0.42 events/h in MAI. Conclusions: In the population with a low suspicion of OSA, the PG showed a low agreement with the simultaneous PSG in the sleep lab. Therefore, PG should only be used as a screening method. Further studies with sufficient sensors in the expanded populations of OSA are needed. Full article

(1) Background: Exhaled nitric oxide (NO) has been considered as a biomarker of airway inflammation. The measurement of fractional exhaled NO (FENO) is a valuable test for assessing local inflammation in subjects with allergic rhinitis (AR). (2) Objective: To evaluate (a) the correlation between nasal FENO with anthropometric characteristics, symptoms of AR and nasal peak flows in children without and with AR; and (b) the cut-off of nasal FENO for diagnosis of AR in symptomatic children. (3) Methods: The study was a descriptive and cross-sectional study in subjects with and without AR < 18 years old. All clinical and functional characteristics of the study subjects were recorded for analysis. They were divided into healthy subjects for the control group and subjects with AR who met all inclusion criteria. (4) Results: 100 subjects (14 ± 3 years) were included, including 32 control subjects and 68 patients with AR. Nasal FENO in AR patients was significantly higher than in control subjects: 985 ± 232 ppb vs. 229 ± 65 ppb (p < 0.001). In control subjects, nasal FENO was not correlated with anthropometric characteristics and nasal inspiratory or expiratory peak flows (IPF or EPF) (p > 0.05). There was a correlation between nasal FENO and AR symptoms in AR patients and nasal IPF and EPF (p = 0.001 and 0.0001, respectively). The cut-off of nasal FENO for positive AR diagnosis with the highest specificity and sensitivity was ≥794 ppb (96.7% and 92.6%, respectively). (5) Conclusion: The use of nasal FENO as a biomarker of AR provides a useful tool and additional armamentarium in the management of allergic rhinitis. Full article