To the Editor, We compared the obtained values of the expected percentage of FEV1 by applying the European Coal and Steel Community (ECSC) prediction equation and the Global Lung Function Initiative (GLI) prediction equation and evaluated the impact on the obtained scoring on the criterion designated as pulmonary disease on the hematopoietic cell transplant specific comorbidity index (HCT‐CI) score. Several risk scores have been developed which are able to support the clinician when considering the risks and benefits of transplant of hematopoietic cells (HCT) in an individualized and systematic way. HCT‐CI is an efficient and valid score that has become a widely used tool in the evaluation of the pretransplant patient of hematopoietic cells. The presence and/or severeness of the pulmonary disease are criteria that are included in this score evaluated according to values of the expected percentage of capacity of the alveolocapillary diffusing capacity of the carbon monoxide (%DLCO) and/or the maximum air volume exhaled in the first second (%FEV1) to that individual, transplant candidate, or the intensity of the dyspnea or the need of additional oxygen therapy in the previous 4 weeks of the intense chemotherapy regimen (pretransplant conditioning of hematopoietic cells). It is classified as a severe pulmonary disease with values of the expected percentage of DLCO or FEV1≤ 65%, or dyspnea at rest or the need of oxygen therapy, and moderate pulmonary disease with values of the expected percentage of DLCO or FEV1 between 66% and 80% or dyspnea in mild activities. The reference equation which should be used for the eventual application of this score is not currently defined. The choice of the used predicted equations, ECSC and GLI, is related to its wide usage in all Europe and by being the last equation recommended by the American Thoracic Society and European Respiratory Society since 2019 (although not yet used in many hospitals), respectively. In the United States, ethnically appropriate National Health and Nutrition Examination Survey (NHANES) III reference equations are recommended for those aged 8–80 years. We enrolled 154 patients (Table 1) and found, as expected, that there was a statistically significant association between the values of the expected percentage of FEV1 according to the ECSC equation and the values of the expected percentage of FEV1 according to the GLI equation, evaluated by the Pearson correlation coefficient as very high (r = 0.890; p < 0.001), suggesting the existence of a linear association between the results of both equations. Meanwhile, the values of the expected percentage of the FEV1, according to the ECSC equation, were on average higher levels (M = 97.25%; SD = 19.89), in comparison to the values of the expected percentage of the FEV1, according to the GLI equation (M = 92.49; SD = 15.58), statistical significance, t(149) = 6.40 (p < 0.001) (Table 2). Moreover, by applying the HCT‐CI score, namely the designated criterion of presence and/or severeness of the pulmonary disease, according to the obtained values of the expected FEV1, the prevalence of patients without a pulmonary disease in our sample was of 80.5%, through the ECSC equation and 77.3% through the GLI equation. The moderate pulmonary disease obtained a prevalence of 9.1% through the ECSC equation and 13.6% through the GLI equation. Finally, the severe pulmonary disease represented 7.8% of the distribution through the ECSC equation and 8.4% of the distribution through the GLI equation. Applying the GLI equation, the frequency of lung disease is higher (in both subgroups: moderate lung disease and severe lung disease) (Table 3). Thus, our data support that the choice of the used equation might affect the obtained scoring in the designated criterion of pulmonary disease and, consequently, have an impact on the obtained HCT‐CI score, and finally influence the clinical decision. The authors suggest that the laboratory should present the value of the expected percentage of the FEV1 obtained according to both equations every time it is verified that the scoring obtained will be different in the criterion of presence and/or severeness of the pulmonary disease of the HCT‐CI score. This way the used equation won't influence this support tool in the clinical decision. Finally, the authors highlight the need for more study cases to determine the best equation to use in this group of patients and standardize the obtained value by the HCT‐CI score.

Background: Peak Expiratory Flow (PEF) and Maximal Expiratory Pressure (MEP) are both measured in a maximal expiratory peak after an initial inspiration. Ohm’s law of fluid flow states that pressure difference is directly proportional to flow and resistance. Objective: Assessment of a possible correlation between PEF and MEP values, and between Forced Inspiratory Flow at 50% of vital capacity (FIF50%) and Maximal Inspiratory Pressure (MIP) values. Methods: Comparison of 306 lung function tests with concomitant spirometry and maximum inspiratory and expiratory pressure tests. The most frequent previous diagnoses in our sample were Amyotrophic lateral sclerosis (13.7%), Systemic sclerosis (10.8%), Dermatomyositis (7.9%) and Obstructive Sleep Apnea Syndrome (5.9%). Results: Moderate positive linear correlation between PEF and MEP values (r(304)=0.596303, p<.00001), and between FIF50% and MIP values r(304)=0.602241, p<.00001). Conclusions: A spirometry test with decreased PEF and FIF50%, might be an important sign of loss of maximum respiratory pressures capacity which relate to diaphragmatic impairment, especially in patients with a previous suspicious diagnosis.

Background: Chronic Obstructive Pulmonary Disease (COPD) results of the interaction between genetic and environmental factors. The influence of the gender is still controverse. Aim: Assess gender differences regarding proportion and predicted factors for COPD diagnosis. Methods: We included individuals aged ≥40 years with smoking habits ≥10 pack year (PY), who performed spirometry in a Lung Function Laboratory of Hospital da Luz Lisbon for 4 months. Individuals with respiratory disease, under bronchodilator and respiratory symptoms (RS) unknown were excluded. Standardized and non-standardized coefficients logistic regression models for COPD diagnosis for both genders were determined using as predictors age, body mass index (BMI), smoking status, PY and presence of RS. A global logistic regression model was also obtained. Results: We included 241 individuals, 134 were male. The COPD diagnosis was 20.9% within male group and 13.1% within female group, without differences (p=0.156). Age was a risk factor for COPD (male:OR 1.052; CI95% 1.002-1.109.female: OR 1.108; CI95% 1.021-1.216) as well as the presence of RS (male:OR 4.990; CI95% 1.863-14.544.female: OR 3.818; CI95% 1.014-17.662). Current smoker status had a significantly greater risk among female (OR 7.5834; CI95% 1.545–62.870 vs OR 0.9317; CI95% 0.316-2.728). The presence of RS had the highest absolute coefficient for the male and the current smoker status for the female model. Interaction between gender and current smoker status was statistically significant (p=0.048). Conclusion: We did not find differences in COPD prevalence between gender. Different factors could be related with different risk for COPD according the gender. Current smoker seems to have higher risk among female.

ABSTRACT Objective: The identification of persistent airway obstruction is key to making a diagnosis of COPD. The GOLD guidelines suggest a fixed criterion-a post-bronchodilator FEV1/FVC ratio < 70%-to define obstruction, although other guidelines suggest that a post-bronchodilator FEV1/FVC ratio < the lower limit of normal (LLN) is the most accurate criterion. Methods: This was an observational study of individuals ≥ 40 years of age with risk factors for COPD who were referred to our pulmonary function laboratory for spirometry. Respiratory symptoms were also recorded. We calculated the prevalence of airway obstruction and of no airway obstruction, according to the GOLD criterion (GOLD+ and GOLD−, respectively) and according to the LLN criterion (LLN+ and LLN−, respectively). We also evaluated the level of agreement between the two criteria. Results: A total of 241 individuals were included. Airway obstruction was identified according to the GOLD criterion in 42 individuals (17.4%) and according to the LLN criterion in 23 (9.5%). The overall level of agreement between the two criteria was good (k = 0.67; 95% CI: 0.52-0.81), although it was lower among the individuals ≥ 70 years of age (k = 0.42; 95% CI: 0.12-0.72). The proportion of obese individuals was lower in the GOLD+/LLN+ category than in the GOLD+/LLN− category (p = 0.03), as was the median DLCO (p = 0.04). Conclusions: The use of the GOLD criterion appears to be associated with a higher prevalence of COPD. The agreement between the GOLD and LLN criteria also appears to be good, albeit weaker in older individuals. The use of different criteria to define airway obstruction seems to identify individuals with different characteristics. It is essential to understand the clinical meaning of discordance between such criteria. Until more data are available, we recommend a holistic, individualized approach to, as well as close follow-up of, patients with discordant results for airway obstruction.

Background: The evaluation of the response to bronchodilator in pulmonary obstructive pathologies is crucial for the diagnosis and clinical follow-up of the individuals. β-adrenergic agonists and anticholinergics are the most frequently used. Objectives: To characterize the response of bronchodilation according to the drug used; to identify differences in response of bronchodilation according to the pathology; to determine the agreement of the response to bronchodilator considering Salbutamol (Sb) or Ipratropium Bromide (IB). Methodology: Cross-sectional study. 141 individuals with airway obstruction were included (39 asthmatics and 102 COPD) and underwent two spirometry tests with an 8-day interval. In half of the sample Sb was used on the first visit and IB on the second, and in the other half the order was reversed. An increase of ≥12% and ≥200mL in FVC and/or FEV1 was considered a positive bronchodilation. Results: The analysis of the means of study variables didn’t revealed significant differences (p>0.05) between Sb and IB. The average of the differences between the parameters was 60mL and 1.92% for FVC and 40mL and 1.53% for FEV1. Bronchodilation was positive in 17.7% of the sample (Sb), 19.1% (IB) and 26.2% (Sb+IB). In COPD group, a positive response was observed in 15.7% (Sb), 18.6% (IB) and 30.4% (Sb+IB) and in the asthma group 23.1% (Sb), 20.6% (IB) and 15.4% (Sb+IB). The Kappa agreement coefficient revealed that the response to bronchodilator is different depending of the used drug (Kappa=0.254; p=0.003). Conclusion: The characterization of the response to the bronchodilator showed to be different according to the drug used, and it was found that asthmatic individuals respond mostly to Sb and COPD to the IB.

Introduction: Peripheral airway obstruction (PAO) is characterized by a concomitant decrease in FVC and FEV1 with normal FEV1/FVC and TLC and an increase in RV (classic criteria). However, several authors suggest the valuation of other parameters for its detection. Objectives: To verify the presence of PAO through the criteria: 1) RV/TLC≥40%, 2) FEF’s<65% and 3) RV/TLC≥40%+FEF’s<65% in individuals with and without PAO by classic criteria; to identify the existence of agreement between the classic criteria and the proposed criteria: 1, 2, 3; to determine the sensitivity and specificity of the proposed criteria. Methods: Cross-sectional study. 140 individuals were studied for the presence of PAO using the classic and the proposed criteria. Two groups were established: 70 subjects with classical criteria and 70 without. Results: In the sample with PAO by the classic criteria, the RV/TLC criterion≥40% detected PAO in 97.1% of the subjects, the FEF’s<65% in 48.6% and the RV/TLC+FEF’s in 48.6% and in those without classic PAO criteria in 37.1%, 7.1% and 5.7%, respectively. There was a statistically significant agreement (p<0.001) between the classic and the proposed criteria, with the RV/TLC≥40% parameter being the most consistent (K=0.600;p<0.001). For RV/TLC criterion≥40%, a sensitivity of 97.1% and a specificity of 62.8% were obtained, for FEF’s<65%, 48.5% and 92.8% and for RV/TLC+FEF 48.5% and 94.2%, respectively. Conclusion: The RV/TLC criterion≥40% revealed a high capacity for detecting PAO in individuals without the presence of the classic criteria and a high agreement with the latter, so its valorization represents an added value, reducing the occurrence of false negatives.

Background: Obstructive sleep apnea (OSA) is frequently associated with excessive daytime sleepiness (EDS). Alas, it is not known why some patients with severe OSA (sOSA) do not develop EDS despite significant sleep fragmentation. Methods: We included a total of 59 sOSA patients (respiratory disturbance index ≥30/h diagnosed by polysomnography [PSG]). EDS was defined as an Epworth Sleepiness Scale ≥ 10. A binominal logistic regression analysis was run to ascertain the effect of apnea hypopnea index (AHI), oxygen desaturation index (ODI), arousal-index (AI), sleep efficiency and total sleep time (TST) on the presence of EDS. Additionally the groups were compared by calculating the effect size by Cohen´s d (d). Results: We detected 20 sOSA patients with EDS. The independent samples Mann Whithey U test did not reveal any significant difference in either anthropometric or PSG variables. The logistic regression analysis including TST, sleep efficiency, AI, ODI and AHI revealed a statistic significant result with χ2(5):=11.3; p=0.046 explaining 24.5% of the variance in sleepiness. Only TST (B: 0.022; p=0.037) and ODI (B: 0.13; p=0.038) reached statistical significance. The total model reached in the ROC curve analysis an acceptable discrimination with the AUC of 0.73 (SE: 0.07). The effect size was 0.59 for TST, 0.01 for sleep efficiency, 0.25 for AI, 0.22 for AHI and 0.45 for ODI. Conclusions: We can show that in sOSA patients that the prevalence of EDS is best explained by TST and intermittent desaturation. Especially TST revealed a moderate effect size and should be considered in home sleep apnea testing.

Introduction Obstructive sleep apnea (OSA) has been associated with non-dipping blood pressure (BP). The precise mechanism is still under investigation, but repetitive oxygen desaturation and arousal induced sleep fragmentation are considered the main contributors. Methods We analyzed beat-to-beat measurements of hemodynamic parameters (HPs) during a 25-min period of wake–sleep transition. Differences in the mean HP values for heart rate (HR), systolic BP (SBP), and stroke volume (SV) during wake and sleep and their standard deviations (SDs) were compared between 34 controls (C) and 22 OSA patients. The Student’s t-test for independent samples and the effect size by Cohen’s d (d) were calculated. HP evolution was investigated by plotting the measured HP values against each consecutive pulse wave. After a simple regression analysis, the calculated coefficient beta (SCB) was used to indicate the HP evolution. We furthermore explored by a hierarchical block regression which variables increased the prediction for the SCB: model 1 BMI and age, model 2 + apnea/hypopnea index (AHI), and model 3 + arousal index (AI). Results Between the two groups, the SBP increased in OSA and decreased in C resulting in a significant difference (p = 0.001; d = 0.92). The SV demonstrated a similar development (p = 0.047; d = 0.56). The wake/sleep variation of the HP measured by the SD was higher in the OSA group—HR: p < 0.001; d = 1.2; SBP: p = 0.001; d = 0.94; and SV: p = 0.005; d = 0.82. The hierarchical regression analysis of the SCB demonstrated in SBP that the addition of AI to AHI resulted in ΔR2: +0.163 and ΔF + 13.257 (p = 0.001) and for SV ΔR2: +0.07 and ΔF 4.83 (p = 0.003). The AI but not the AHI remained statistically significant in the regression analysis model 3—SBP: β = 0.717, p = 0.001; SV: β = 0.469, p = 0.033. Conclusion In this study, we demonstrated that in OSA, the physiological dipping in SBP and SV decreased, and the variation of all investigated parameters increased. Hierarchical regression analysis indicates that the addition of the AI to BMI, age, and AHI increases the prediction of the HP evolution following sleep onset for both SBP and SV and may be the most important variable.

INTRODUCTION: Currently, the bronchodilator reversibility is not recommended to differentiate asthma from chronic obstructive pulmonary disease (COPD); however, physiopathological specificities of each disease contribute to the differences in response to the drug. OBJECTIVES: The objective of this study is to evaluate the differences in bronchodilator response between asthmatic and COPD patients and to determine which of the bronchodilation criteria have the best ability to detect the positive response in these patients. MATERIALS AND METHODS: This was a cross-sectional study. The sample included 104 patients with asthma or COPD who performed lung function tests between January and March 2018. The whole sample was analyzed according to postbronchodilator variation (Δ) of lung function parameters, and the postbronchodilator reversibility was characterized using a multiple bronchodilation criteria. The drug used in reversibility test was salbutamol. RESULTS: In this study, Δ forced-expiratory volume in the 1st s (ΔFEV1) and a Δ Raw was statistically higher in the group with asthma compared with the group with COPD. In the asthma group, the criteria ↓ functional residual capacity (FRC) ≥10%, ↓Raw ≥ 35%, ↑ forced expiratory flow between 25% and 75% of vital capacity (FEF25%–75%) ≥20% and ↑ FEV1 and / or ↑ forced vital capacity ≥12% and 200 mL were those that presented a greater capacity of detecting a positive response to bronchodilator. The criteria ↑ FEF25%–75%≥20% and ↓ FRC ≥ 10% were those that had the greater ability of detecting airway reversibility in COPD group. CONCLUSION: The analysis of postbronchodilator FEV1 and raw modifications as well as the using of a combination of multiple bronchodilation criteria contribute to a deeper characterization of bronchodilator reversibility in asthma and COPD.

Background: To perform pulmonary function tests (PFT’s), the correct determination of the height is extremely important to obtain the reference equations and affects the interpretation of the results. Commonly this measure is made by a stadiometer, although in some individuals with certain pathologies and/or advanced age, has to be replaced by the determination of arm-span. Objectives: to identify if there are ventilatory pattern changes using height or arm-span and to verify if there are differences in the degree of severity using height or arm-span. Methodology: The sample was composed by 107 individuals of both genders. The height and the arm-span was measured, and the PFT’s were performed using the height in first place and then replacing to arm-span in the computer software. Results: There was a strong and positive correlation between height and arm-span in both genders (r= 0.751; p= 0.000). Regarding respiratory functional variables under study, there was a very strong positive correlation between the two measures: [FVC (r= 0.807; p= 0.001); FEV1 (r=0.798; p=0.000); TLC (r=0.815; p= 0.002): RV (r= 0.912; p=0.000)]. Even though, it was verified that in 21% of the patients the ventilatory pattern changed and in 28% of them, the degree of severity increased one degree. Conclusion: Although no significant differences were found between the two measurements, in a considerable percentage of the patients the ventilatory pattern and/or the degree of severity has changed, so the use of arm span seems to be relevant.

Background: In the last few years an increase in obstructive airway diseases has been reported. Studies showing the effect of bronchodilation in the alveolar-capillary diffusing capacity of carbon monoxide (DLCO) have been rare, and with different conclusions. Objective: To evaluate if there’s a change in DLCO and in diffusing capacity corrected to alveolar volume (DLCO/VA) before and after the administration of Salbutamol. Methodology: A sample of 89 subjects was studied. Spirometric measurements and diffusing capacity of DLCO and DLCO/VA were obtained before and after Salbutamol inhalation. These measurements were evaluated in relation to age, gender, underlying pathology and degree of severity of the obstructive disease. Results: The results of this study suggest that there are no statistically significant differences in the value of DLCO (p=0.057) and DLCO/VA (p=0.098) after administration of salbutamol related to pretests, except in patients with severe obstructive pathology: in the DLCO (p=0.034) and DLCO/VA (p=0.037). Conclusion: In patients with severe obstructive lung diseases, significant differences were found in DLCO and DLCO/VA, after administration of Salbutamol related to pretests. Concerning the other study variables no differences were found. It suggests that DLCO test may be performed after the administration of Salbulamol in the latter.

Introduction: Vital capacity (VC) can be determined through expiratory (EVC) or inspiratory maneuvers (IVC). It is fundamental for determination of lung volumes and its incomplete mobilization has repercussions on the detection of air trapping or pulmonary hyperinflation. VC is also essential for detection of airway obstruction through the FEV1/VC ratio. Aims: To determine the differences between EVC and IVC (EVC-IVC) according to ventilatory pattern; to characterize the FEV1/EVC and FEV1/IVC ratios; to study the effects of EVC or IVC on the detection of air trapping or pulmonary hyperinflation. Methods: The sample included 388 subjects of both genders. In half of the sample the VC was determined first by the EVC and then by the IVC and in the other half in the reverse order. The sample was divided into 3 groups: without ventilatory changes (normal), airway obstruction and pulmonary restriction. Results: The EVC-IVC parameter was greater than 200 mL in 34.8% of the normal group, 28.4% of the airway obstruction group and 22.4% of the pulmonary restriction group. The ratio FEV1/EVC<0.70 detected airway obstruction in 44.8% of the whole sample and the ratio FEV1/IVC<0.70 in 39.4%. In the airway obstruction group, lung volumes determined through the EVC, verified the presence of air trapping in 21.6% of the subjects and pulmonary hyperinflation in 9.5%, and when determined through the IVC, air trapping was observed in 18.2% of the subjects and pulmonary hyperinflation in 10.8%. Conclusions: The EVC and IVC maneuvers shouldn’t be considered interchangeable due to differences in the volume obtained for each of them. These differences consequently influence the interpretation of lung function results.

Introduction: Individuals with respiratory disease are at risk of hypoxaemia during air travel. Several methods have been used, however, the hypoxic challenge testing (HCT) is nowadays the preferred method to predict it. The relation between air travel hypoxaemia, baseline lung function tests (LFT) and arterial oxygenation has been studied with discrepant data. Aim: Assess the correlation between PaO2 on HCT and LFT, resting sea level PaO2 and SpO2. Methods: Included all respiratory patients who performed LFT and HCT between January 2016 and December 2017 at Hospital da Luz Lisboa (private hospital). HCT was performed and analyzed according to British Thoracic Society recommendations (2011). Median (me) was shown. Pearson correlation (r) was used. P value ≤0.05 was considered significant. Results: Fifteen respiratory patients were included: 5 chronic obstructive pulmonary disease, 2 asthma, 2 pneumectomy, 2 obstructive sleep apnea and 4 other respiratory diseases. Seven patients (46.7%) had a positive HCT. Correlation between PaO2 on HCT (mmHg) (me=55.0) and FEV1 (%) (me=76.5; r=0.390, p=0.150), FEV1 (mL) (me=1485.0; r=0.503, p=0.096), FVC (%) (me=97.7; r=0.407, p=0.148), FVC (mL) (me=2465.0; r=0.559, p=0.059), DLCO (%) (me=66.9; r=0.444, p=0.097) and resting sea level PaO2 (mmHg) (me=69.0; r=0.562, p=0.072) was not significant. A positive correlation was observed between PaO2 on HCT and sea level SpO2 (%) (me=95.0; r=0.674, p=0.006). Conclusions: In this sample of respiratory patients, there is a moderate correlation between baseline SpO2 and PaO2 on HTC. LFT did not predict PaO2 on HTC. HTC remains an essential tool to evaluate if respiratory patients need in-flight oxygen.

Background: Obstructive sleep apnea (OSA) is a disease with a high impact on quality of life, morbidity and mortality. The relationship between obesity and OSA is well established. Aim: In our study we analyzed the effect of bariatric surgery (BC) on an OSA population of obese patients and at what weight loss a control sleep study should be scheduled. Methods: A total of 51 obese (BMIu003e 30Kg/m2) patients proposed for BC with an apneia/hipopneia index (AHI) u003e 5/h were included between 2015 and 2017. All performed a level 3 home sleep recording (HSR) before and after BC. The test statistics software used was SPSS 19.0 (t test for pared samples and multiple linear regression, significant level α = 0.05). Results: From the 51 patients evaluated 62.7% (32) were female, with a mean age of 49.61±11.88 years old. The average of weight lost that results in an improvement of IAH in this study population is 24 kg [age (p = 0.014); AHI (p = 0.05); R = 0.504 (p = 0.001)]. Conclusion: We concluded that BC can be an effective treatment for obese OSA patients with a significant impact in AHI, BMI, P90 as well as in OSA severity. Also, the ideal time to access therapy success by performing an HSR, based on a regression model for this study population, is after a loss of ≈ 24 kg after surgery.

Introduction: When the first GOLD report was released, the recommendation for severity assessment relied on a spirometric grading system alone. In 2011, a major revision was made and the ABCD assessment tool was introduced. The ABCD assessment tool was again modified in the most recent review of the GOLD document (2017). In the current version, unlike the previous classifications, the spirometric grades are separated from the ABCD groups and are only to be used for prognostication and treatment with non-pharmacologic therapies. Aim: The aim of this study was to compare the three severity classifications in the same population of patients. Methods: We analyzed 758 spirometries from smokers/former smokers with a ratio FVC/FEV1 pos-bronchodilator < 0,7 in addition to the mMRC scale and the reported exacerbations in the previous year. We classified the patients according with the 2001, 2011 and 2017 classifications. Results: 35%of the patients were smokers and 71% male. Using the 2001 classification 49.9% were class 1 (mild disease); 41.9% class 2 (moderade disease); 7,4% severe and 0,8% very severe. With the GOLD 2011 classification 77,4% of the patients were in the group A, 5% in group B, 13,2% in group C and 4,4% in group D. Using the gold 2017 classification, 82,7% of the patients were in group A, 6,5% in group B, 7,9% in group C and 2,9% n group D. Discussion: The major difference emerging from the comparison of the three classifications is that in the most recent the same patients fall into a less severe category, a trend that is more significant in the 2017 grades. The major consequence is that more patients are using less pharmacological therapies.

Obstructive Sleep Apnea Syndrome (OSAS) is the most common sleep disorder and is prevalence increases in the overweight population. The STOP-BANG questionnaire is a validated diagnostic tool, in which a score ≥3 has a high sensitivity in OSAS detection but a relatively low specificity. The objective of this study is verify if the association between sodium bicarbonate and the STOP-BANG questionnaire increases the specificity, with minimal effect in sensitivity. Subjects included were overweight patients referred for a polygraphic sleep study, which had also an arterial blood gas analysis in the same time period. Anthropometric data, as well as the results of the STOP-BANG were collected. Of the 141 patients studied, the mean age was 51 years, 35.5% were male, with an average BMI of 39.7 kg/m 2 . According to the polysomnographic study, 60% of patients had OSAS and the mean AHI was 17.3/h. The analysis of STOP-BANG showed a 85% sensitivity and 43% specificity for an AHIu003e5/h, with an increased sensitivity to 90% for moderate/severe OSAS and 97% for severe OSAS. When adding the HCO3 − values to the analysis, the specificity was increased (98%), but with markedly decreased sensitivity (15%). With the two steps method analysis the results showed a sensitivity of 44% and a specificity of 91%. In assessing the ROC curves, it shows that the STOP-BANG has an area of 0.738. In association with HCO3 − values has an area of 0.772 and using the two steps method the area is 0.811. In conclusion, STOP-BANG questionnaire has an important value in the screening of OSAS. However, for a more effective ranking, the addiction of HCO3 − values in overweight patients who have intermediate degrees of the questionnaire is essential

Introduction: Sleep onset (SO) is associated with a decrease in heart rate (HR), systolic and diastolic blood pressure (Sys, Dia). These changes are reduced by obstructive sleep apneas (OSA). There is little evidence if obesity alone influences the hemodynamic parameters (HP) at SO. Methods: We investigated 40 patients with a BMI > 30 kg/m2 via polysomnography and Nexfin-HD® recordings. Group A: 16 patients without OSA; Group B: 24 patients with OSA. Sys, Dia, mean blood pressure (MAP), HR, stroke volume (SV) and cardiac output (CO) were analyzed 5 min before (P0) and 20 min after SO (P1). The student t-test for independent samples was applied with a significance level of p<0.05. Results: SO was not associated with any significant decrease in HP. However, variation of HP was different between the two groups. It decreased in Group A: Sys: -0,6 mmHg; Dia: -0,1 mmHg; HR: -0,6 bpm, SV: -0,7 ml and CO: -0,2 L/min. MAP increased by 0.04 mmHg. All HP increased significantly in group B with Sys: +2,3 mmHg, Dia: +0,8 mmHg, HR: +0,2, MAP: +1,4 mmHg, SV: +1,1 ml and CO: +0,2 L/min and reached signficance when compared to group A. Discussion: SO was not associated with a significant decrease in any investigated HP. Perhaps obesity alone attenuates the physiological reduction of the sympathetic activity at SO. The higher variation of hemodynamic parameters in OSA indicates its impact on the cardiovascular stability.

Introduction: There is no clear relationship between the severity of obstructive sleep apneas (OSA) and the degree of sleepiness. We analysed if any polysomography (PSG) based parameter is related with either subjective or objective sleepiness measures by sleepiness scales and pupillographic sleepiness test (PST). Methods: We included 105 patients. Following PSG patients indicated perceived sleepiness by the Stanford Sleepiness (SSS), Epworth sleepiness (ESS) and the visual analogue scale (VAS). The PST was applied as an objective assessment of sleepiness. Beside the total pupillary unrest index (PUI) we analysed the percentage of time spend with normal (%PUI 0-6.5), marginal (%PUI 6,6-9,7) and sleepy PUI values (%PUI => 9,8). Patients were divided in sleepy or non sleepy according to an ESS value ≥ 10 or an PUI ≥ 9,8%. Results: We found an increased PUI in 32 patients (33%). 37 patients demonstrated an increased ESS and 17 an increased SSS. There was no direct correlation between the values of the PST and the subjective sleepiness scales. PSG parameters were not significantly different between the sleepy and non sleep patients. We analysed subjective and objective sleepiness in patients with an AHI <5 and ≥ 30/h. PST values and subjective sleepiness did not differ significantly between the groups. In fact, patients with an AHI ≥ 30/h demonstrated slightly lower values than controls. Conclusion: In this study we do not find any correlation between severity of OSA and sleepiness. Patients with sleep disturbances find it often difficult to distinguish between fatigue and real sleepiness, which might explain the missing correlation between subjective and objective sleepiness.

Obstructive: sleep apnea syndrome (OSAS) is a disease with high prevalence associated with an increase of cardiovascular morbidity and mortality. Screening questionnaires are used to evaluate the predisposition of having/developing OSAS. The OSA50 questionnaire is based on four items: – Obesity: Waist circumference (malesu003e102cm or Femalesu003e88cm) - 3 points – Snoring: Has your snoring ever bothered other people - 3 points – Apneas: Has anyone noticed that you stop breathing during your sleep? - 2points – 50: Are you aged 50 years or over? - 2 points Aim: To evaluate statistically the subjects’ OSA50 questionnaire with the data obtained in cardio-respiratory sleep study (CRSS). Methods: Retrospective study with a sample of 832 subjects with OSAS suggestive complaints and/or disease’s indirect signals that were evaluated through CRSS between October 2014 and September 2015. Results: A positive CRSS (AHIu003e5/h) was found in 66% of the sample – with an AHI mean of 15,23/h. The OSA50 questionnaire shows a weak positive correlation between AHI (p value = 0,001; r = 0,174), supine AHI (p value = 0,001; r = 0,130) and Desaturation Index (p value = 0.001; r = 0,180). After the categorization of AHI by severity levels it was observed a stronger correlation between OSA50 values Conclusion: The OSA50 questionnaire appears to have limited utility in a referred, sleep laboratory setting. Negative results help to identify some individuals as unlikely to have moderate-to-severe apnea, and may thereby prove useful in identification of patients who would benefit more from laboratory studies than home studies for symptom clarification.

Introduction: Spirometry plays a fundamental role in the evaluation of pulmonary function. In 2012, with the publication of the Global Lungs Initiative (GLI) reference equations, the discussion of the equations chosen by each laboratory was once again in the spotlight. Aim: The aim was to compare the FEV1 value from different reference equations available, namely the European Community for Steel and Coal (ECSC) 71|83|93, the National Health and Nutrition Examination Survey (NHANES) III and GLI. Methods: We retrospectively selected spirometries from 30 individuals (63% men), aged between 51 and 82 years, who met the criteria of acceptability and reproducibility. We calculated the percentage of the predicted forced expiratory volume in 1 second (FEV1) using all the mentioned equations. In order to standardize the sample, only patients with bronchial obstruction were chosen (FEV1/FVC ratio <0,7). Results: Only the results for GLI and ECSC 71 are not significantly different (pairwise t-tests, p<0,05), when the five equations are compared. We found that the results between ECSC 83 and 93 to be very similar, when comparing the severity of obstruction classified according to the percentage of predicted obstruction (ATS/ERS guideline 2005). However, both were statistically different from GLI (pairwise Wilcoxon tests). There was no significant differences between NHANES III and the other methodologies. Discussion: As the equations produce significantly different values for predicted FEV1, the resulting classification of the obstruction will also be different. Therefore, it is critical that all reports clearly state the equation used, until laboratories agree on the standard equation to use.