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Objectives: Obstructive sleep apnea syndrome (OSA) is a cause of high morbidity and mortality so diagnosis and treatment is essential. Questionnaires and oximetry have been used for OSA screening. Aim: To evaluate the clinical utility of different sleep questionnaires (Stop Bang (S-B), Berlin (BQ), Epworth Sleepiness Scale (ESS)) in deciding on treatment with Continuous Positive Airway Pressure (CPAP) and to examine whether the combination of the questionnaires alone or with oximetry improves their predictive value for CPAP initiation. Methods: Patients visiting a Sleep Clinic were prospectively studied. They completed the questionnaires. Home oximetry and in laboratory polysomnography (PSG) were performed within 3–20 days. Patients received CPAP if they were symptomatic with AHI ≥ 5 or had AHI > 15. Results: 204 patients were studied (77.5%males, mean age 51.8 ± 13.8 years, BMI 32.8 ± 6.2 kg/m2). There was a good correlation between Oxygen Desaturation Index of oximetry (ODIox) and ODI of PSG (r = 0.95, p

Objective/Background: Varenicline (VAR) is used for smoking cessation as it inhibits nicotine for binding on its receptors reducing nicotine dependence. VAR administration has been reported to affect sleep. The aim of this study was to evaluate possible changes in polysomnography (PSG) during VAR treatment (SmokeFreeBrain) in healthy smokers and smokers with obstructive sleep apnea (OSA). Patients/Methods: Thirty smokers (21 men) with 15.3 ± 10.2 PY, aged 32.8 ± 4.5 years, with BMI 28.6 ± 4 kg/m2, 16 without and 14 with OSA (92% males) were studied with PSG (Embletta MPR-Master) before treatment with VAR while smoking and 20–30 days during VAR administration and smoking cessation for at least 5 days. Results: No significant differences were observed in sleep macro architecture (N1, N2, N3, REM, Sleep Efficiency, Total Sleep Time) during VAR treatment apart from prolongation of sleep latency, N2 and N3 latency in both smokers with and without OSA. Apnea hypopnea index (AHI) was reduced in OSA smokers and especially during REM with a borderline increase of arousal index (ArI) and reduction of sleep efficiency (SE). Conclusion: VAR treatment worsened sleep quality as a prolongation of sleep latency, N2 and N3 latency was observed. A marginal reduction of AHI was found in OSA patients, more significantly during REM. Due to the small sample size, further studies are needed to distinguish between the adverse reactions of VAR treatment and smoking cessation effects and to evaluate whether VAR may play a role in OSA treatment.

The connection between smoking and Obstructive sleep apnea (OSA) is not yet clear. There are studies that have confirmed the effect of smoking on sleep disordered breathing, whereas others did not. Nicotine affects sleep, as smokers have prolonged total sleep and REM latency, reduced sleep efficiency, total sleep time, and slow wave sleep. Smoking cessation has been related with impaired sleep. The health consequences of cigarette smoking are well documented, but the effect of smoking cessation on OSA has not been extensively studied. Smoking cessation should improve OSA as upper airway oedema may reduce, but there is limited data to support this hypothesis. The impact of smoking cessation pharmacotherapy on OSA has been studied, especially for nicotine replacement therapy (NRT). However, there are limited data on other smoking cessation medications as bupropion, varenicline, nortriptyline, clonidine, and cytisine. The aim of this review was to explore the current evidence on the association between smoking and OSA, to evaluate if smoking cessation affects OSA, and to investigate the possible effects of different pharmacologic strategies offered for smoking cessation on OSA.

Background Several tools have been used to screen for obstructive sleep apnea (OSA). Evaluation of the predictive performance of different questionnaires is essential in patients with type 2 diabetes mellitus (T2DM) because the prevalence of OSA in this population is high. The aim of this study was to evaluate different sleep questionnaires to identify T2DM patients with OSA, and to compare the predictive values of these questionnaires with a matched sample of non-diabetic patients. Methods The study was a retrospective study of two patients groups (n = 350 with T2DM, n = 350 without T2DM) visiting a sleep clinic and matched by age, gender, body mass index, and the apnea-hypopnea index (AHI). Symptoms of OSA and Epworth Sleepiness Scale (ESS), STOP-Bang, Berlin questionnaire, and Athens insomnia scale (AIS) scores were compared, and sleep studies were performed. Results Diabetic patients with OSA complained more frequently of nocturia (P = 0.025), morning headaches (P = 0.04), restless sleep (P = 0.002), and leg movements (P = 0.01) than non-diabetic patients with OSA. Most predictive values of the sleep questionnaires did not differ significantly between the two groups; however, the AIS was higher only in T2DM women (P = 0.01). In both groups, the Berlin and STOP-Bang questionnaires had the highest sensitivity. The ESS had the highest specificity in T2DM patients and the STOP and S-B questionnaires had the highest specificity in non-diabetics. Conclusions The predictive performance of the questionnaires was similar in both groups, especially in the case of moderate and severe OSA.

Background and aims: Fever is a response to stimuli leading to the deregulation of the central thermostatic control. It is well-known that hyperthermia is a significant seizure-inducing factor, but it is unusual to be observed in the post-ictal period. Methods: We present the case of a 41-year-old man, admitted to our Department due to multiple generalized convulsions since the early hours on the day of admission. He had a 20-year history of epileptic seizures, after sustaining head trauma in a car accident. He was taking valproate long-term, with poor adherence, and carbamazepine for 6 months. On admission the patient had full consciousness, and the neurological examination, blood pressure and blood glucose test were normal. His body temperature was 38.8C. Results: An infectious cause of fever was investigated. A complete laboratory and imaging examination (WBC, ESR, CRP, liver biochemical tests, blood and urine cultures, PCR for SARS-CoV-2, CXR) was performed. Tests returned normal or negative, ruling out an infection. Brain CT revealed a porencephalic lesion on the left occipital lobe and signs of a craniotomy on the right temporal side. EEG showed slow theta activity in the left temporo-occipital area. The fever resolved spontaneously in about 12 h. Conclusions: Fever is a well-known seizure-inducing factor, but an infrequent condition in post-ictal period. It is hypothesized that this symptom is a consequence of peri-ictal repetitive muscular contractions and disturbance of homeostasis in generalized convulsive seizures. It also seems possible that the upregulation of the hypothalamic thermoregulatory center can produce it. The investigation for infectious causes is necessary.

Several tools have been used to screen for obstructive sleep apnea (OSA). Evaluation of the predictive performance of different questionnaires is essential in patients with type 2 diabetes mellitus (T2DM) because the prevalence of OSA in this population is high. The aim of this study was to evaluate different sleep questionnaires to identify T2DM patients with OSA, and to compare the predictive values of these questionnaires with a matched sample of non-diabetic patients.The study was a retrospective study of two patients groups (n = 350 with T2DM, n = 350 without T2DM) visiting a sleep clinic and matched by age, gender, body mass index, and the apnea-hypopnea index (AHI). Symptoms of OSA and Epworth Sleepiness Scale (ESS), STOP-Bang, Berlin questionnaire, and Athens insomnia scale (AIS) scores were compared, and sleep studies were performed.Diabetic patients with OSA complained more frequently of nocturia (P = 0.025), morning headaches (P = 0.04), restless sleep (P = 0.002), and leg movements (P = 0.01) than non-diabetic patients with OSA. Most predictive values of the sleep questionnaires did not differ significantly between the two groups; however, the AIS was higher only in T2DM women (P = 0.01). In both groups, the Berlin and STOP-Bang questionnaires had the highest sensitivity. The ESS had the highest specificity in T2DM patients and the STOP and S-B questionnaires had the highest specificity in non-diabetics.The predictive performance of the questionnaires was similar in both groups, especially in the case of moderate and severe OSA.

Background: Different questionnaires have been used to evaluate patients with Obstructive sleep apnea/hypopnea syndrome (OSAHS). The 4-Variable screening tool (4-V) was developed and validated in Asian population for identifying moderate to severe OSAHS. Aims and Objectives: To evaluate the ability of 4-V to identify patients at high risk for OSAHS in a European Population visiting a Sleep Clinic. Methods: 1057 (73.8% males), 52±14 years, BMI 33±7kg/m 2 , Epworth Sleepiness Scale (ESS) 11.5±5.4 and Apnea Hypopnea Index (AHI) 32.7±26.5 were included. All patients had an in laboratory sleep study and 4-V was calculated. Results: The mean 4-V score was 13.3±2.5. Sensitivities of 4-V≥11 for AHI ≥5, ≥15 and ≥30 were 78%, 79% and 81%, respectively; specificities 40.8%, 36%, 32%; positive predictive values (PPV) 84.3%, 71%, 52%; negative predictive values (NPV) 31% , 46.5%, 65% and area under the ROC curve at AHI≥ 15 was 0.58. For 4-V ≥14, sensitivities for AHI ≥5, ≥15 and ≥30 were 50.7%, 55% and 61%, respectively; specificities 78%, 74.4%, 69%; PPV 90.3%, 81%, 64%; NPV 27.9%, 45%, 66% and area under the ROC curve at AHI≥ 15 was 0.68. The 4-V differed significantly between no and mild and between moderate and severe OSAHS, but not between mild and moderate OSAHS in both genders. Sensitivity was better in men, but specificity was higher in women. Conclusion: In Caucasians the 4-V≥14 had low sensitivity and NPV, rather good specificity and PPV. For a cut-off ≥11, sensitivity was better but specificity was low. However the predictive values differed between genders. Asian Journal of Medical Sciences Vol.7(2) 2015 21-27

Interstitial lung diseases (ILD) are chronic and restrictive lung diseases with poor survival and quality of life. The aim of this study was to investigate the frequency of sleep disorders in idiopathic pulmonary fibrosis (IPF) and sarcoidosis and to assess patients’ quality of life in relation to these disorders. Forty patients, 19 with IPF, and 21 with sarcoidosis stage II/III were included. They were compared with 15 healthy subjects. All patients performed all-night polysomnography (PSG) and completed the Epworth, Berlin, and Stop-Bang questionnaires. In order to evaluate the quality of life, all patients completed the Short-Form 36 (SF-36) questionnaire. Of the IPF patients, 68% were diagnosed with mild obstructive sleep apnea (OSA), 5.2% with moderate to severe, 5.2% with severe OSA, and 21% with no OSA. Of patients with sarcoidosis, 52.4% were diagnosed with mild OSA and 4.8% with moderate severity OSA. The remaining 42.8% did not have OSA. The health-related quality of life in both patients with IPF and patients with sarcoidosis was impaired especially in the domains concerning physical health and the level of independence, compared to the control group. In this sample of patients with IPF and sarcoidosis, obstructive sleep apnea is common at least in a mild degree of severity. The SF-36 questionnaire may be a useful tool for the evaluation of the quality of life in these patients.

Background: Gender affects the clinical presentation of obstructive sleep apnea (OSA). The classic OSA symptoms, such as sleepiness, snoring, and apnea, are not so frequent in women. Objectives: To evaluate possible gender differences in questionnaires used for OSA prediction, such as the Epworth Sleepiness Scale (ESS), STOP, STOP Bang (SB), Berlin Questionnaire (BQ), Athens Insomnia Scale (AIS), and Fatigue Scale (FS). Methods: 350 males were matched with 350 women referred to a sleep clinic, according to OSA severity. All responded to the questionnaires and underwent a sleep study. Cardiovascular disease (CVD) patients were separately analyzed. Results: ESS did not differ between genders. SB was higher in males, whereas STOP, BQ, AIS, and FS were higher in females. BQ presented the highest sensitivity in both genders, whereas STOP exhibited the highest specificity in males and ESS in females. AIS and FS were more sensitive and SB more specific in females, whereas BQ was more specific in males. For severe OSA, the predictive values of SB and BQ were almost similar for both genders, however AIS and FS were higher in women. CVD patients presented higher scores, independent of gender, except for AIS, which was higher in females. Conclusion: Gender-specific evaluation of questionnaires is necessary to prevent OSA under-diagnosis.

Background Obstructive sleep apnea/hypopnea syndrome (OSAHS) is a major cause of morbidity and mortality. Different clinical models and questionnaires have been used to evaluate patients with the highest OSAHS probability. Objectives To evaluate the clinical utility of five different questionnaires – STOP, STOPBang (SB), Berlin Questionnaire (BQ), Epworth Sleepiness Scale (ESS), and 4-Variable Screening Tool (4-V) – in a sleep clinic in order to identify patients at risk for OSAHS and to assess the best possible combination of these tools. Methods 1853 (74.4% males) patients (mean age 52±14years; mean body mass index 32.8±7kg/m 2 ) visiting a sleep clinic were studied retrospectively. Results SB had the highest sensitivity (97.6%), the largest area under the receiver operating characteristics curve (AUC) (0.73; 95% CI, 0.7–0.76) and best OR (5.9; 95% CI, 3.6–9.5), but the lowest specificity (12.7%) for AHI ⩾15. The 4-V ⩾14 had the highest specificity (74.4%) followed by ESS (67%). BQ had good sensitivity (87%), worse specificity (33%) than 4-V and ESS but better than STOP (13%) and SB (12.7%). The combination of questionnaires did not improve their predictive value. Conclusions SB had the highest sensitivity, OR, and AUC, but rather low specificity, and 4-V the highest specificity. The combination of different questionnaires did not improve their predictive value.

Background: Obstructive sleep apnea (OSA) is a highly prevalent disease with different clinical presentations. Diabetes and OSA may coexist. Objectives: To evaluate the possible different clinical presentations of OSA in diabetic patients. Methods: Retrospective analysis of the data of patients visiting a Sleep Clinic. Antropometric data, Epworth Sleepiness Scale (ESS), STOP BANG(SB), Athens Insomnia Scale (AIS) were completed and sleep studies were performed. Results: From 1248 included, 27(2%) had type 1 diabetes and 176(14%) type 2 with no gender difference. Diabetic patients were older (61±10 vs 52.2±14 p 2 =0.002). Significant differences were found in ESS (10.25 ± 5 vs 9.4 ±4.6, P=0.02), SB (5.5 ±1.5 vs 4.4 ±1.6, p Conclusions: Diabetic OSA patients were older, more obese, and sleepier,with more insomnia symptoms and arousals than non diabetic.

Background: Athens Insomnia Scale (AIS) is an instrument that has been used to assess insomnia. Insomnia type disorders has been recognized in patients with Obstructive Sleep Apnea Syndrome (OSA). Objectives: To examine the factor structure of the AIS in OSA, the prevalence of insomnia type disorders evaluated with AIS in OSA patients, and its associations with demographic characteristics. Methods: Retrospective analysis of the data of patients visiting a Sleep Clinic. Antropometric data, Epworth Sleepines Scale (ESS), STOP BANG(SB), Athens Insomnia Scale (AIS) were completed and sleep studies were performed.Exploratory factor analysis was used to examine the factor structure of the AIS and multiple regression analysis models to determine the associations between AIS and demographic characteristics. Results: 951 patients (70.5% male, 52.9±13.6 years, 32.4±9 kg/m2) answered the AIS (8.9±5.3) with ESS 9.4 ±4.7, SB 4.4±1.6 and Apnea Hypopnea Index (AHI) 28.8±26. AIS >6 was found in 62.5% (66.8% with severe OSA). Significant correlations were found between AIS –ESS, AIS –BMI, AIS-AHI (p Conclusions: OSA patients have insomnia-like problems as estimated by the AIS.

Background: Oximetry has been used as a cheap indicator of obstructive sleep apnea/hypopnea syndrome (OSAHS). Several questionnaires have been used in order to identify OSAHS. Objectives: To evaluate the clinical utility of the combination of home oximetry and 4 different questionnaires: Stop, Stop Bang(S-B), Berlin questionnaire (BQ) and Epworth Sleepiness Scale (ESS) in order to identify OSAHS compared with in-laboratory PSG. Methods: Patients visiting a Sleep Clinic were prospectively studied. They completed the questionnaires. Home oximetry and PSG were performed. Results: 204 patients participated (77.5%males, 51.8±13.8years, BMI 32.8±6.2 kg/m 2 ). Using AHI>15 for OSAHS diagnosis, Oxygen Desaturation Index of oximetry (ODIox)≥5 had the best sensitivity(se)(99%) and negative predictive value (NPV)(97.6%), whereas ODIox≥15 had the best specificity(sp)(94%),positive predictive value (PPV)(96.5%) and area under the curve (AUC)(0.882). The predictive values of ODIox improved as the severity of OSAHS worsened (mild: se 4%, sp32.5%, severe: se97.5%, sp72.6%). S-B had the highest se(97.5%) and NPV(62.5%) but the lowest sp (9%), whereas ESS had the best sp(75%) and PPV(81.4%). The questionnaires had better predictive value than oximetry in mild OSAHS (AUC 0.18 oximetry vs. 0.51 S-B, 0.4BQ). The combination of the questionnaires with oximetry improved oximetry9s sensitivity, especially in mild and moderate OSAHS, but not specificity. Conclusion: Oximetry is a useful tool for OSAHS identification especially in severe disease. Combining oximetry with questionnaires did not significantly improve the predictive value. For patients with concerns of misdiagnosis, PSG remains the test of choice.