Diagnostic Value of Galectin-3 in Exacerbations of Chronic Obstructive Pulmonary Disease.

Background and Objectives: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease characterized by acute exacerbations. Systemic inflammation and oxidative stress play an important role in the pathogenesis of COPD. Exacerbations in COPD reduce the quality of life and are associated with rapid disease progression. Galectin-3 is a beta-galactoside-binding lectin of approximately 30 kDa with pro-inflammatory and pro-fibrotic properties. This study aims to analyze the efficacy of serum galectin-3 in predicting exacerbations in COPD patients. Materials and Methods: Baseline demographic and clinical characteristics of all patients were recorded and blood samples were collected. A total of 58 consecutive COPD patients, including 28 patients (19 male and 9 female) with stable COPD and 30 patients (23 male and 7 female) with acute exacerbation of COPD (AECOPD), were included in the study. Results: Serum galectin-3 levels were significantly higher in the AECOPD group compared to the stable COPD group. A logistic regression analysis revealed that increased galectin-3 levels and disease duration were independent predictors of COPD exacerbation (OR = 5.322, 95% CI: 1.178-24.052, p = 0.03; and OR = 1.297, 95% CI: 1.028-1.635, p = 0.028; respectively). Conclusions: The results of our study demonstrated that Galectin-3 was a strong and independent predictor of exacerbations in COPD patients.

The effects of disease severity and comorbidity on oxidative stress biomarkers in obstructive sleep apnea.

PURPOSE: Ischemia-modified albumin (IMA), total oxidant status (TOS), and total antioxidant status (TAS) are biomarkers used to evaluate oxidative stress status in various diseases including obstructive sleep apnea (OSA). In this study, we investigated the effects of disease severity and comorbidity on IMA, TOS and TAS levels in OSA. METHODS: Patients with severe OSA (no-comorbidity, one comorbidity, and multiple comorbidities) and mild-moderate OSA (no-comorbidity, one and multiple comorbidities), and healthy controls were included in the study. Polysomnography was applied to all cases and blood samples were taken from each participant at the same time of day. ELISA was used to measure IMA levels in serum samples and colorimetric commercial kits were used to perform TOS and TAS analyses. In addition, routine biochemical analyses were performed on all serum samples. RESULTS: A total of 74 patients and 14 healthy controls were enrolled. There was no statistically significant difference between the disease groups according to gender, smoking status, age, body mass index (BMI), HDL, T3, T4, TSH, and B12 (p > 0.05). As the severity of OSA and comorbidities increased, IMA, TOS, apnea-hypopnea index (AHI), desaturation index (T90), cholesterol, LDL, triglyceride, AST, and CRP values increased significantly (p < 0.05). On the other hand, TAS, minimum desaturation, and mean desaturation values decreased significantly (p < 0.05). CONCLUSIONS: We concluded that IMA, TOS, and TAS levels may indicate OSA-related oxidative stress, but as the severity of OSA increases and with the presence of comorbidity, IMA and TOS levels may increase and TAS levels decrease. These findings suggest that disease severity and presence/absence of comorbidity should be considered in studies on OSA.

Efficacy of serum apelin and galectin-3 as potential predictors of mortality in severe COVID-19 patients.

Apelin is a cardioprotective biomarker while galectin-3 is a pro-inflammatory and profibrotic biomarker. Endothelial dysfunction, hyperinflammation, and pulmonary fibrosis are key mechanisms that contribute to the development of adverse outcomes in Coronavirus disease 2019 (COVID-19) infection. This study aims to analyze the prognostic value of serum apelin and galectin-3 levels to early predict patients at high risk of mortality in patients hospitalized for severe COVID-19 pneumonia. The study included 78 severe COVID-19 patients and 40 healthy controls. The COVID-19 patients were divided into two groups, survivors and nonsurvivors, according to their in-hospital mortality status. Basic demographic and clinical data of all patients were collected, and blood samples were taken before treatment. In our study, serum apelin levels were determined to be significantly lower in both nonsurvivor and survivor COVID-19 patients compared to the control subjects (for both groups, p < 0.001). However, serum apelin levels were similar in survivor and nonsurvivor COVID-19 patients (p > 0.05). Serum galectin-3 levels were determined to be higher in a statistically significant way in nonsurvivors compared to survivors and controls (for both groups; p < 0.001). Additionally, serum galectin-3 levels were significantly higher in the survivor patients compared to the control subjects (p < 0.001). Positive correlations were observed between galectin-3 and age, ferritin, CK-MB and NT-proBNP variables (r = 0.32, p = 0.004; r = 0.24, p = 0.04; r = 0.24, p = 0.03; and r = 0.33, p = 0.003, respectively) while a negative correlation was observed between galectin-3 and albumin (r = -0.31, p = 0.006). Multiple logistic regression analysis revealed that galectin-3 was an independent predictor of mortality in COVID-19 patients (odds ratio [OR] = 2.272, 95% confidence interval [CI] = 1.106-4.667; p = 0.025). When the threshold value for galectin-3 was regarded as 2.8 ng/ml, it was discovered to predict mortality with 80% sensitivity and 57% specificity (area under the curve = 0.738, 95% CI = 0.611-0.866, p = 0.002). Galectin-3 might be a simple, useful, and prognostic biomarker that can be utilized to predict patients who are at high risk of mortality in severe COVID-19 patients.

Carbonic Anhydrase IX as a Marker of Disease Severity in Obstructive Sleep Apnea.

Background and Objectives: Carbonic anhydrase (CA) enzymes are a family of metalloenzymes that contain a zinc ion in their active sites. CA enzymes have been implied in important situations such as CO2 transport, pH regulation, and oncogenesis. CA-IX is a transmembrane glycoprotein and stimulates the expression of hypoxia-inducible factor-1 (HIF-1) CA-IX. This study aimed to determine serum CA-IX levels in OSA patients in whom intermittent hypoxia is important and to investigate the relationship between serum CA-IX levels and disease severity. Materials and Methods: The study included 88 people who applied to Malatya Turgut Özal University Training and Research Hospital Sleep Disorders Center without a history of respiratory disease, malignancy, and smoking. Patients were divided into three groups: control (AHI < 5, n = 31), mild−moderate OSA (AHI = 5−30, n = 27) and severe OSA (AHI > 30, n = 30). The analysis of the data included in the research was carried out with the SPSS (IBM Statistics 25, NY, USA). The Shapiro−Wilk Test was used to check whether the data included in the study had a normal distribution. Comparisons were made with ANOVA in multivariate groups and the t-test in bivariate groups. ANCOVA was applied to determine the effect of the CA-IX parameter for OSA by controlling the effect of independent variables. The differentiation in CA-IX and OSA groups was analyzed regardless of BMI, age, gender, and laboratory variables. ROC analysis was applied to determine the parameter cut-off point. Sensitivity, specificity, and cut-off were calculated, and the area under the curve (AUC) value was calculated. Results: Serum CA-IX levels were 126.3 ± 24.5 pg/mL in the control group, 184.6 ± 59.1 pg/mL in the mild−moderate OSA group, and 332.0 ± 39.7 pg/mL in the severe OSA group. Serum CA-IX levels were found to be higher in the severe OSA group compared to the mild−moderate OSA group and control group and higher in the mild−moderate OSA group compared to the control group (p < 0.001, p < 0.001, p < 0.001, respectively). In addition, a negative correlation between CA-IX and minimum SaO2 and mean SaO2 (r = −0.371, p = 0.004; r = −0.319, p = 0.017, respectively). A positive correlation between CA-IX and desaturation index (CT90) was found (r = 0.369, p = 0.005). A positive correlation was found between CA-IX and CRP (r = 0.340, p = 0.010). When evaluated by ROC curve analysis, the area under the curve (AUC) value was determined as 0.940 (95% CI 0.322−0.557; p < 0.001). When the cut-off value for CA-IX was taken as 254.5 pg/mL, it was found to have 96.7% sensitivity and 94.8% specificity in demonstrating severe OSA. Conclusions: Our study found that serum CA-IX value was higher in OSA patients than in control patients, and this elevation was associated with hypoxemia and inflammation. CA-IX value can be a fast, precise, and useful biomarker to predict OSA.

Is There a Relationship between Voice Quality and Obstructive Sleep Apnea Severity and Cumulative Percentage of Time Spent at Saturations below Ninety Percent: Voice Analysis in Obstructive Sleep Apnea Patients.

Background and Objectives: Apnea hypopnea index is the most important criterion in determining the severity of obstructive sleep apnea (OSA), while the percentage of the total number of times which oxygen saturation is measured below 90% during polysomnography (CT90%) is important in determining the severity of hypoxemia. As hypoxemia increases, inflammation will also increase in OSA. Inflammation in the respiratory tract may affect phonation. We aimed to determine the effects of the degree of OSA and CT90% on phonation. Materials and Methods: The patients were between the ages of 18−60 years and were divided into four groups: normal, mild, moderate, and severe OSA. Patients were asked to say the vowels /α:/ and /i:/ for 5 s for voice recording. Maximum phonation time (MPT) was recorded. Using the Praat voice analysis program, Jitter%, Shimmer%, harmonics-to-noise ratio (HNR), and f0 values were obtained. Results: Seventy-two patients were included. Vowel sound /α:/; there was a significant difference for Jitter%, Shimmer%, and HNR measurements between the 1st and the 4th group (p < 0.001, p < 0.001, and p < 0.001, respectively) and a correlation between CT90% and Shimmer% and HNR values (p < 0.001 and p < 0.021, respectively). Vowel sound /i:/; there was a significant difference in f0 values between the 1st group and 2nd and 4th groups (p < 0.028 and p < 0.015, respectively), and for Jitter%, Shimmer%, and HNR measurements between the 1st and 4th group (p < 0.04, p < 0.000, and p < 0.000, respectively), and a correlation between CT90% and Shimmer% and HNR values (p < 0.016 and p < 0.003, respectively). The difference was significant in MPT between the 1st group and 3rd and 4th groups (p < 0.03 and p < 0.003, respectively). Conclusions: Glottic phonation can be affected, especially in patients whose AHI scores are ≥15. Voice quality can decrease as the degree of OSA increases. The increase in CT90% can be associated with the worsening of voice and can be used as a predictor in the evaluation of voice disorders in the future.

MTU-COVNet: A hybrid methodology for diagnosing the COVID-19 pneumonia with optimized features from multi-net.

PURPOSE: The aim of this study was to establish and evaluate a fully automatic deep learning system for the diagnosis of COVID-19 using thoracic computed tomography (CT). MATERIALS AND METHODS: In this retrospective study, a novel hybrid model (MTU-COVNet) was developed to extract visual features from volumetric thoracic CT scans for the detection of COVID-19. The collected dataset consisted of 3210 CT scans from 953 patients. Of the total 3210 scans in the final dataset, 1327 (41%) were obtained from the COVID-19 group, 929 (29%) from the CAP group, and 954 (30%) from the Normal CT group. Diagnostic performance was assessed with the area under the receiver operating characteristic (ROC) curve, sensitivity, and specificity. RESULTS: The proposed approach with the optimized features from concatenated layers reached an overall accuracy of 97.7% for the CT-MTU dataset. The rest of the total performance metrics, such as; specificity, sensitivity, precision, F1 score, and Matthew Correlation Coefficient were 98.8%, 97.6%, 97.8%, 97.7%, and 96.5%, respectively. This model showed high diagnostic performance in detecting COVID-19 pneumonia (specificity: 98.0% and sensitivity: 98.2%) and CAP (specificity: 99.1% and sensitivity: 97.1%). The areas under the ROC curves for COVID-19 and CAP were 0.997 and 0.996, respectively. CONCLUSION: A deep learning-based AI system built on the CT imaging can detect COVID-19 pneumonia with high diagnostic efficiency and distinguish it from CAP and normal CT. AI applications can have beneficial effects in the fight against COVID-19.

May viral load detected in saliva in the early stages of infection be a prognostic indicator in COVID-19 patients?

OBJECTIVE: This study aimed to investigate the prognostic value of viral load detected in the saliva of COVID-19 patients in the early stage of infection. STUDY DESIGN: Oro-nasopharyngeal swab and saliva samples were collected from all patients simultaneously in the early stage of COVID-19. Viral loads were determined by extracting viral RNAs from saliva samples of patients whose ONP swabs were positive for SARS-CoV-2 by RT-qPCR. The demographic information, comorbidities, cycle threshold values, and one-month clinical courses were recorded and compared. RESULTS: The patients' clinical course was evaluated for one month; 56 % of patients had mild disease, 26.4 % had moderate disease, 9.6 % had severe disease, and 8% had a critical/mortal disease. The average cycle threshold values of SARS-CoV-2 in saliva and ONP samples were measured as 22.28 and 24.19, respectively. Cycle threshold value of saliva was found to be significant in predicting disease severity (Eta coefficient 0.979). A statistically significant relationship was found between the disease's severity and the mean of ONP samples' Ct-values (p < 0.05). Gender, age, body mass index, and co-morbidities were compared with the severity of the disease; no statistically significant difference was found. CONCLUSION: Viral load detected in saliva in the early period of COVID-19 infection may have a prognostic value in showing the disease's course in patients over 45-year-old. Saliva is an easily obtainable, reliable material for COVID-19 screening.

Efficacy of copeptin in distinguishing COVID-19 pneumonia from community-acquired pneumonia.

The clinical symptoms of community-acquired pneumonia (CAP) and coronavirus disease 2019 (COVID-19)-associated pneumonia are similar. Effective predictive markers are needed to differentiate COVID-19 pneumonia from CAP in the current pandemic conditions. Copeptin, a 39-aminoacid glycopeptide, is a C-terminal part of the precursor pre-provasopressin (pre-proAVP). The activation of the AVP system stimulates copeptin secretion in equimolar amounts with AVP. This study aims to determine serum copeptin levels in patients with CAP and COVID-19 pneumonia and to analyze the power of copeptin in predicting COVID-19 pneumonia. The study consists of 98 patients with COVID-19 and 44 patients with CAP. The basic demographic and clinical data of all patients were recorded, and blood samples were collected. The receiver operating characteristic (ROC) curve was generated and the area under the ROC curve (AUC) was measured to evaluate the discriminative ability. Serum copeptin levels were significantly higher in COVID-19 patients compared to CAP patients (10.2 ± 4.4 ng/ml and 7.1 ± 3.1 ng/ml; p < .001). Serum copeptin levels were positively correlated with leukocyte, neutrophil, and platelet count (r = -.21, p = .012; r = -.21, p = .013; r = -.20, p = .018; respectively). The multivariable logistic regression analysis revealed that increased copeptin (odds ratio [OR] = 1.183, 95% confidence interval [CI], 1.033-1.354; p = .015) and CK-MB (OR = 1.052, 95% CI, 1.013-1.092; p = .008) levels and decreased leukocyte count (OR = 0.829, 95% CI, 0.730-0.940; p = .004) were independent predictors of COVID-19 pneumonia. A cut-off value of 6.83 ng/ml for copeptin predicted COVID-19 with a sensitivity of 78% and a specificity of 73% (AUC: 0.764% 95 Cl: 0.671-0.856, p < .001). Copeptin could be a promising and useful biomarker to be used to distinguish COVID-19 patients from CAP patients.

The relationship between anxiety, depression, daytime sleepiness in the REM-related mild OSAS and the NREM-related mild OSAS.

INTRODUCTION: Obstructive sleep apnea syndrome (OSAS) is a common form of sleep-related respiratory disease characterized by recurrent blockages in the upper airway. Rapid eye movement (REM)-related OSAS is a condition in which apneas and hypopneas are more common during REM sleep. We investigated whether there was any difference between REM-related mild OSAS group and NREM-related mild OSAS group in terms of anxiety, depression, and daytime sleepiness. METHODS: A total of 166 patients with mild OSAS (72 patients with REM-related and 94 NREM-related OSAS) participated in the study. Hospital Anxiety-Depression Scale (HADS) and Epworth Sleepiness Scale (ESS) questionnaires were completed by both groups. RESULTS: Anxiety and depression scores were significantly higher in patients with REM-related OSAS in comparison to the NREM-related OSAS group (p = 0.01, p = 0.02 respectively). There was no statistically significant difference between the two groups in terms of ESS scores (p = 0.60). CONCLUSION: The results of our study suggest that patients with REM-related OSAS have higher rates of depression and anxiety compared to non-REM-related OSAS patients and this may adversely affect quality of life. It may be possible to prevent psychiatric complications, such as depression and anxiety, by administering treatments that reduce REM sleep duration and intensity in patients with REM-related OSAS.