DKPNet41: Directed knight pattern network-based cough sound classification model for automatic disease diagnosis.

PROBLEM: Cough-based disease detection is a hot research topic for machine learning, and much research has been published on the automatic detection of Covid-19. However, these studies are useful for the diagnosis of different diseases. AIM: In this work, we collected a new and large (n=642 subjects) cough sound dataset comprising four diagnostic categories: 'Covid-19', 'heart failure', 'acute asthma', and 'healthy', and used it to train, validate, and test a novel model designed for automatic detection. METHOD: The model consists of four main components: novel feature generation based on a specifically directed knight pattern (DKP), signal decomposition using four pooling methods, feature selection using iterative neighborhood analysis (INCA), and classification using the k-nearest neighbor (kNN) classifier with ten-fold cross-validation. Multilevel multiple pooling decomposition combined with DKP yielded 41 feature vectors (40 extracted plus one original cough sound). From these, the ten best feature vectors were selected. Based on each vector's misclassification rate, redundant feature vectors were eliminated and then merged. The merged vector's most informative features automatically selected using INCA were input to a standard kNN classifier. RESULTS: The model, called DKPNet41, attained a high accuracy of 99.39% for cough sound-based multiclass classification of the four categories. CONCLUSIONS: The results obtained in the study showed that the DKPNet41 model automatically and efficiently classifies cough sounds for disease diagnosis.

Using artificial intelligence to improve the diagnostic efficiency of pulmonologists in differentiating COVID-19 pneumonia from community-acquired pneumonia.

Coronavirus disease 2019 (COVID-19) has quickly turned into a global health problem. Computed tomography (CT) findings of COVID-19 pneumonia and community-acquired pneumonia (CAP) may be similar. Artificial intelligence (AI) is a popular topic among medical imaging techniques and has caused significant developments in diagnostic techniques. This retrospective study aims to analyze the contribution of AI to the diagnostic performance of pulmonologists in distinguishing COVID-19 pneumonia from CAP using CT scans. A deep learning-based AI model was created to be utilized in the detection of COVID-19, which extracted visual data from volumetric CT scans. The final data set covered a total of 2496 scans (887 patients), which included 1428 (57.2%) from the COVID-19 group and 1068 (42.8%) from the CAP group. CT slices were classified into training, validation, and test datasets in an 8:1:1. The independent test data set was analyzed by comparing the performance of four pulmonologists in differentiating COVID-19 pneumonia both with and without the help of the AI. The accuracy, sensitivity, and specificity values of the proposed AI model for determining COVID-19 in the independent test data set were 93.2%, 85.8%, and 99.3%, respectively, with the area under the receiver operating characteristic curve of 0.984. With the assistance of the AI, the pulmonologists accomplished a higher mean accuracy (88.9% vs. 79.9%, p < 0.001), sensitivity (79.1% vs. 70%, p < 0.001), and specificity (96.5% vs. 87.5%, p < 0.001). AI support significantly increases the diagnostic efficiency of pulmonologists in the diagnosis of COVID-19 via CT. Studies in the future should focus on real-time applications of AI to fight the COVID-19 infection.

COVID-19: vaccination vs. hospitalization.

OBJECTIVE: Vaccination is the most efficient way to control the coronavirus disease 2019 (COVID-19) pandemic, but vaccination rates remain below the target level in most countries. This multicenter study aimed to evaluate the vaccination status of hospitalized patients and compare two different booster vaccine protocols. SETTING: Inoculation in Turkey began in mid-January 2021. Sinovac was the only available vaccine until April 2021, when BioNTech was added. At the beginning of July 2021, the government offered a third booster dose to healthcare workers and people aged > 50 years who had received the two doses of Sinovac. Of the participants who received a booster, most chose BioNTech as the third dose. METHODS: We collected data from 25 hospitals in 16 cities. Patients hospitalized between August 1 and 10, 2021, were included and categorized into eight groups according to their vaccination status. RESULTS: We identified 1401 patients, of which 529 (37.7%) were admitted to intensive care units. Nearly half (47.8%) of the patients were not vaccinated, and those with two doses of Sinovac formed the second largest group (32.9%). Hospitalizations were lower in the group which received 2 doses of Sinovac and a booster dose of BioNTech than in the group which received 3 doses of Sinovac. CONCLUSION: Effective vaccinations decreased COVID-19-related hospitalizations. The efficacy after two doses of Sinovac may decrease over time; however, it may be enhanced by adding a booster dose. Moreover, unvaccinated patients may be persuaded to undergo vaccination.

Can copeptin predict the severity of coronavirus disease 2019 infection?

OBJETIVE: Coronavirus disease 2019 (COVID-19) has quickly turned into a health problem globally. Early and effective predictors of disease severity are needed to improve the management of the patients affected with COVID-19. Copeptin, a 39-amino acid glycopeptide, is known as a C-terminal unit of the precursor pre-provasopressin (pre-proAVP). Activation of AVP system stimulates copeptin secretion in equimolar amounts with AVP. This study aimed to determine serum copeptin levels in the patients with COVID-19 and to examine the relationship between serum copeptin levels and the severity of the disease. METHODS: The study included 90 patients with COVID-19. The patients with COVID-19 were divided into two groups according to disease severity as mild/moderate disease (n=35) and severe disease (n=55). All basic demographic and clinical data of the patients were recorded and blood samples were collected. RESULTS: Copeptin levels were significantly higher in the patients with severe COVID-19 compared with the patients with mild/moderate COVID-19 (p<0.001). Copeptin levels were correlated with ferritin and fibrinogen levels positively (r=0.32, p=0.002 and r=0.25, p=0.019, respectively), and correlated with oxygen saturation negatively (r=-0.37, p<0.001). In the multivariate logistic regression analysis, it was revealed that copeptin (OR: 2.647, 95%CI 1.272-5.510; p=0.009) was an independent predictor of severe COVID-19 disease. A cutoff value of 7.84 ng/mL for copeptin predicted severe COVID-19 with a sensitivity of 78% and a specificity of 80% (AUC: 0.869, 95%CI 0.797-0.940; p<0.001). CONCLUSION: Copeptin could be used as a favorable prognostic biomarker while determining the disease severity in COVID-19.

Automatic COVID-19 Detection Using Exemplar Hybrid Deep Features with X-ray Images.

COVID-19 and pneumonia detection using medical images is a topic of immense interest in medical and healthcare research. Various advanced medical imaging and machine learning techniques have been presented to detect these respiratory disorders accurately. In this work, we have proposed a novel COVID-19 detection system using an exemplar and hybrid fused deep feature generator with X-ray images. The proposed Exemplar COVID-19FclNet9 comprises three basic steps: exemplar deep feature generation, iterative feature selection and classification. The novelty of this work is the feature extraction using three pre-trained convolutional neural networks (CNNs) in the presented feature extraction phase. The common aspects of these pre-trained CNNs are that they have three fully connected layers, and these networks are AlexNet, VGG16 and VGG19. The fully connected layer of these networks is used to generate deep features using an exemplar structure, and a nine-feature generation method is obtained. The loss values of these feature extractors are computed, and the best three extractors are selected. The features of the top three fully connected features are merged. An iterative selector is used to select the most informative features. The chosen features are classified using a support vector machine (SVM) classifier. The proposed COVID-19FclNet9 applied nine deep feature extraction methods by using three deep networks together. The most appropriate deep feature generation model selection and iterative feature selection have been employed to utilise their advantages together. By using these techniques, the image classification ability of the used three deep networks has been improved. The presented model is developed using four X-ray image corpora (DB1, DB2, DB3 and DB4) with two, three and four classes. The proposed Exemplar COVID-19FclNet9 achieved a classification accuracy of 97.60%, 89.96%, 98.84% and 99.64% using the SVM classifier with 10-fold cross-validation for four datasets, respectively. Our developed Exemplar COVID-19FclNet9 model has achieved high classification accuracy for all four databases and may be deployed for clinical application.

Can copeptin predict the severity of coronavirus disease 2019 infection?

SUMMARY OBJETIVE Coronavirus disease 2019 (COVID-19) has quickly turned into a health problem globally. Early and effective predictors of disease severity are needed to improve the management of the patients affected with COVID-19. Copeptin, a 39-amino acid glycopeptide, is known as a C-terminal unit of the precursor pre-provasopressin (pre-proAVP). Activation of AVP system stimulates copeptin secretion in equimolar amounts with AVP. This study aimed to determine serum copeptin levels in the patients with COVID-19 and to examine the relationship between serum copeptin levels and the severity of the disease. METHODS The study included 90 patients with COVID-19. The patients with COVID-19 were divided into two groups according to disease severity as mild/moderate disease (n=35) and severe disease (n=55). All basic demographic and clinical data of the patients were recorded and blood samples were collected. RESULTS Copeptin levels were significantly higher in the patients with severe COVID-19 compared with the patients with mild/moderate COVID-19 (p<0.001). Copeptin levels were correlated with ferritin and fibrinogen levels positively (r=0.32, p=0.002 and r=0.25, p=0.019, respectively), and correlated with oxygen saturation negatively (r=-0.37, p<0.001). In the multivariate logistic regression analysis, it was revealed that copeptin (OR: 2.647, 95%CI 1.272-5.510; p=0.009) was an independent predictor of severe COVID-19 disease. A cutoff value of 7.84 ng/mL for copeptin predicted severe COVID-19 with a sensitivity of 78% and a specificity of 80% (AUC: 0.869, 95%CI 0.797-0.940; p<0.001). CONCLUSION Copeptin could be used as a favorable prognostic biomarker while determining the disease severity in COVID-19.

The effect of radiological distribution on the COVID-19 disease.

INTRODUCTION: The aim of the study was to investigate the effects of radiological distribution on COVID-19 clinic and prognosis and to determine the relationship between laboratory parameters and thorax CT findings. MATERIALS AND METHODS: Patients with COVID-19 were evaluated retrospectively. Laboratory parameters were obtained from medical records. Ground-glass opacities (GGO) and consolidation were evaluated on thorax CT. The presence of a single lobe lesion was considered as limited while multiple lobe lesions were considered as diffuse involvement for both GGO and consolidation. RESULT: A total 200 patients with COVID-19 were evaluated. 178 of them (89%) were discharged, 17 patients (8.5%) were transferred to the ICU and five patients died (2.5%). The ratios of mortality and transfer to the ICU in patients with diffused GGO were significantly higher compared to patients with limited GGOs. It was observed that troponin ≥0.06 µg/L, platelet <140 and fibrinogen ≥350 mg/dl were independent predictors of the presences of diffused GGOs in thorax CT. CONCLUSIONS: Diffused GGOs on thorax CT are correlated with the rate of mortality and transfer to the ICU in patients with COVID-19. Also, troponin, fibrinogen, and platelet levels can be used while predicting extensive parenchymal disease on thorax CT.

The role of endobronchial ultrasound-guided transbronchial needle aspiration in the differential diagnosis of isolated mediastinal and/or hilar lymphadenopathy.

INTRODUCTION: Isolated mediastinal and/or hilar lymphadenopathy (IMHL) has become an increasingly common finding as a result of the increased use of thoracic imaging modalities. Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is accepted as the first step diagnostic method in the differential diagnosis of IMHL. OBJECTIVE: To determine the diagnostic yield of the procedure and to analyze clinical and sonographic findings that can be used to differentiate the etiology of lymph node pathologies. METHODS: Patients who underwent EBUS-TBNA procedure between March 2017 and March 2020 were included in this retrospective study. Demographic data, symptoms, comorbid diseases, and EBUS findings were obtained from the records of the patients. RESULTS: EBUS-TBNA provided a diagnosis in 88 patients out of 120 patients (granulomatous diseases n = 54, malignant diseases n = 21, and anthracotic lymph nodes n = 13), and 32 patients had a negative EBUS-TBNA. 22/32 negative EBUS-TBNA samples were true negatives (reactive lymphadenopathy). The sensitivity of the procedure was 89.8% while negative predict value was 68.7%, diagnostic yield of 91.6%. Patients with reactive lymph nodes had significantly more comorbidities (77.3%-19.4%, p < .001) and a lower number of lymph node stations (1.6 ± 0.8-2.7 ± 0.9, p < .001). Patients with anthracotic lymph nodes were older and mostly consisted of females (11/13, p < .001). CONCLUSION: EBUS-TBNA has high-diagnostic efficiency in the differential diagnosis of IMHL. The number and size of lymph node stations can provide useful information for differential diagnosis. Clinical follow-up can be a more beneficial approach in patients with reactive and anthracotic lymph nodes before invasive sampling.

The Glasgow Prognostic Score and fibrinogen to albumin ratio as prognostic factors in hospitalized patients with COVID-19.

Aim: This study aims to determine the prognostic value of the Glasgow Prognostic Score (GPS) and fibrinogen to albumin ratio (FAR) in patients with COVID-19.Methods: Electronic database records of 400 patients with COVID-19 were retrospectively analyzed and the initial levels of CRP, albumin, fibrinogen values were recorded. The ground-glass opacities (GGO) and consolidations were evaluated on thorax CT. Hospital mortality and the need for intensive care unit (ICU) transfer were determined as adverse outcomes.Results: It was determined that 345 patients (86.25%) were discharged while 31 patients (7.75%) were transferred to ICU in addition to 24 patients who died (6%). The rates of deaths and transfers to ICU were significantly increased in GPS 2 group compared to both GPS 0 and 1 groups. Additionally, increased FAR was observed in patients who died and transferred to ICU compared to the discharged patients. The FAR was significantly increased in patients with diffuse GGO. Logistic regression analysis indicated that FAR ≥144.59 and the presence of GPS 2 were independent predictors of the adverse outcomes in COVID-19 patients.Conclusion: Our results demonstrated that the GPS and FAR could possess a predictive value for adverse outcomes in patients with COVID-19.

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.

Endocan as a potential biomarker of disease severity and exacerbations in COPD.

INTRODUCTION: Endocan is a proteoglycan that is regarded as a novel marker of endothelial dysfunction. Endothelial dysfunction in pulmonary vascular bed is known to play an important role for the pathogenesis of COPD. OBJECTIVE: This study aimed to determine serum endocan levels in patients with stable COPD and acute exacerbation of COPD (AECOPD) and to test the relationship between serum endocan levels and exacerbations. METHODS: This study enrolled a total of 55 COPD patients, 24 of which had AECOPD and 31 had stable COPD. All patients' basic demographic and clinical data were recorded and blood samples were collected. RESULTS: Serum endocan levels were significantly higher in the AECOPD group compared to the stable COPD and control groups (for both p < 0.001) and stable COPD group had higher levels than the control group (p < 0.005). Additionally, serum endocan levels were negatively correlated with FVC, FEV1, partial oxygen pressure and oxygen saturation (r = -0.30, p = 0.03; r = -0.34, p = 0.01; r = -0.34, p = 0.01 and r = -0.36, p = 0.007 respectively), and positively correlated with disease duration and systolic pulmonary artery pressure (r = 0.47, p < 0.001; r = 0.31, p = 0.02 respectively). A cut-off value of 434.29 pg/ml for endocan predicted exacerbation with a sensitivity of 79% and a specificity of 84% (AUC: 0.778, 95% Cl 0.648-0.909; p < 0.001). Logistic regression analysis revealed that increased endocan levels was independent predictor of COPD exacerbation (OR = 9.32, 95%CI, 1.64-52.95; p = 0.01). CONCLUSION: Endocan may be a novel biomarker for detection of endothelial dysfunction and prediction of exacerbations in patients with COPD.

MR-proADM and MR-proANP levels in patients with acute pulmonary embolism.

BACKGROUND: The aim of this study was to determine levels of Mid-regional Pro-adrenomedullin (MR-proADM) and Mid-regional Pro-atrial Natriuretic Peptide (MR-proANP) in patients with acute pulmonary embolism (PE), the relationship between these parameters and the risk classification in addition to determining the relationship between 1and 3month mortality. METHODS: 82 PE patients and 50 healthy control subjects were included in the study. Blood samples for Mr-proANP and Mr-proADM were obtained from the subjects prior to the treatment. Risk stratification was determined according to sPESI (Simplified Pulmonary Embolism Severity Index). Following these initial measurements, cases with PE were assessed in terms of all causative and PE related mortalities. RESULTS: The mean serum Mr-proANP and Mr-proADM levels in acute PE patients were found to be statistically higher compared to the control group (p < 0.001, p < 0.01; respectively) and statistically significantly higher in high-risk patients than low-risk patients (p < 0.01, p < 0.05; respectively). No statistical difference was determined in high-risk patients in case of sPESI compared to low-risk patients while hospital mortality rates were higher. It was determined that the hospital mortality rate in cases with Mr-proANP ≥ 123.30 pmol/L and the total 3-month mortality rate in cases with Mr-proADM ≥ 152.2 pg/mL showed a statistically significant increase. CONCLUSIONS: This study showed that Mr-proANP and MRproADM may be an important biochemical marker for determining high-risk cases and predicting the mortality in PE patients and we believe that these results should be supported by further and extensive studies.

The Glasgow prognostic score can be a predictor of mortality in acute exacerbation of chronic obstructive pulmonary disease.

Aim: To determine the prognostic value of Glasgow Prognostic Score (GPS) in acute exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD) requiring hospitalization.Methods: Hospital electronic database of 129 patients with AECOPD was retrospectively searched and CRP levels, complete blood count, arterial blood gas (ABG) values and pulmonary function test (PFT) parameters of patients were recorded. Hospital mortality and need for ICU transfer were determined as adverse outcomes from files of cases.Results: 106 of 129 patients were male (82.2%) and rest of them were female (17.8%). GPS 0 was not observed in any patient, GPS 1 was observed in 101 patients, and GPS 2 was observed in 28 patients. The rate of adverse outcomes (ICU/Ex) was significantly increased in the GPS 2 group when compared to the GPS 1 group (X2:7.631, p < 0.01). Logistic regression analysis indicated that pH≤7.35 (p < 0.05, OR: 5.65, CI: 1.35-23.58%) and GPS 2 score (p < 0.05, OR: 5.52, CI: 1.45-20.97%) were independent predictors for adverse outcomes for AECOPD.Conclusion: Our results demonstrate that the GPS may have predictive value for adverse outcomes in patients with AECOPD.

Endocan as a marker of disease severity in pulmonary thromboembolism.

INTRODUCTION: The aim of this study is to determine the serum endocan levels in patients with pulmonary thromboembolism (PTE) and investigate whether a relationship exists between serum endocan levels and the disease severity. MATERIALS AND METHODS: The study included 85 patients with acute PTE and 40 healthy control subjects. The patients with PTE were divided into three groups at admission as "high-risk", "intermediate-risk" and "low-risk", considering the guidelines of the European Society of Cardiology. Serum endocan levels in all participants' blood samples were measured. RESULTS: The mean serum endocan levels were significantly higher in the PTE group, compared to the control subjects (P < 0.001). Serum endocan levels were significantly higher in the "high-risk" group when compared with patients in the "low-risk" and "intermediate-risk" groups (P < 0.001 and P < 0.01 respectively). Similarly, serum endocan levels were higher in the "intermediate-risk" group compared to those in the "low-risk" group (P < 0.001). There was a negative correlation between serum endocan levels and partial oxygen pressure (r = -0.262, P = 0.016), whereas a positive correlation was found between the serum endocan levels and systolic pulmonary arterial pressure (r = 0.296, P = 0.006). Additionally, endocan had an area under the curve in the receiver operating characteristic curve of 0.837 (0.768-0.907; 95% CI; P < 0.001) and cut-off value was 194.5 pg/mL (sensitivity 80%, specificity 72.5%). CONCLUSION: Serum endocan levels were higher and related to the severity of the disease in PTE patients. Additionally, endocan could be an indicator to be used in the diagnosis of PTE and in the prediction of the disease severity.

Prognostic value of copeptin in patients with acute pulmonary thromboembolism.

BACKGROUND AND AIMS: The aim of this study was to determine the level of copeptin, which is one of the new cardiac markers in acute pulmonary thromboembolism (PE) cases, and to determine the relationship between the severity of the disease, risk classification and hospital, first month, third month and 3-month total mortality. METHODS: The study included 100 cases with PE and 60 healthy control subjects. Copeptin was measured in control group. The risk grade of the cases was determined according to the sPESI index. Patients survival data at the first and third months were determined. This study was performed in patients with strict exclusion criteria for comorbidities known to be associated with increased risk of PE. RESULTS: sPESI was ≥1 in 68 (68%) of patients with acute PE. Mean serum copeptin levels were found statistically higher in patients with high risk compared to low-risk cases and controls (9.18 ± 3.29, 6.47 ± 2.29, and 5.26 ± 2.15, P < 0.0001, respectively). When the cut-off value of copeptin was taken as ≥7.87 with ROC analysis for predicting high sPESI score, the sensitivity of the copeptin was 78% and the specificity was 62% (AUC = 0.74, 95% CI = 0.63-0.85, P < <0.0001). When cases divided in the groups according to the cut-off value as 7.87, first month hospital mortality and 3-month total mortality rate was found statistically higher in patients with copeptin ≥7.87 (χ2 = 5.33 P < 0.05, χ2 = 3.88, P < 0.05 and χ2 = 4.26, P < 0.05 respectively). CONCLUSIONS: The results of our study showed that increased serum copeptin levels might predict the severity of PE as well as a promising marker of early mortality in high-risk cases according to sPESI.

The relationship between platelet-to-lymphocyte ratio and pulmonary embolism severity in acute pulmonary embolism.

BACKGROUND: The aim of this study was to determine the level of platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) in patients with acute pulmonary embolism (APE) according to high and low risk for early mortality based on simplified Pulmonary Embolism Severity Index (sPESI). In addition, it was investigated the relationship between PLR and NLR with systolic pulmonary artery pressure (sPAP), cardiac markers, disease severity and hospital, 1th month, 3th month and 3-month total mortality. METHODS: Our hospital's electronic patient database was searched for the patients with APE during last year and eighty-two patients retrospectively evaluated. Plasma D-dimer, troponin I (TnI), brain natriuretic peptide (BNP), hemogram values, sPAP from echocardiographic findings were recorded from database system. Hospital mortality was determined from files of cases and 1th, 3th month mortality and survival information were determined by phone calls with the patient and/or relatives. RESULTS: A percentage of 67.1% (55) of APE cases had sPESI≥1. There was no significant difference for age and sex between high and low risk patients according to sPESI (P>0.05). The mean serum BNP, TnI, sPAP, neutrophil counts, platelet counts, PLR and NLR was statistically increased and lymphocyte counts was statistically decreased in high risk patients according to sPESI compared with low risk patients (P<0.01 for BNP, PLR and NLR; P<0.05 for TnI, sPAP, neutrophil and platelet; P<0.01 for lymphocyte). There was no significantly difference for hospital and total 3-month mortality between high and low risk patients (P>0.05). When the cut-off value of PLO was taken as ≥156 by ROC analysis for the predicting of high sPESI, PLR had an area under the curve (AUC) in the receiver operating characteristic (ROC) curve of 0.704 (0.591-0.816; 95% CI; P<0.01) and the cut-off value of NLR was taken as ≥3.56 by ROC analysis for the predicting of high sPESI, NLR had an area under the curve (AUC) in the receiver operating characteristic (ROC) curve of 0.675 (0.556-0.794; 95% CI; P<0.05). An NLR level of 3.56 was taken as the cut-off between high and low risk patients according to sPESI, NLR had a sensitivity of 66% and specificity of 53%. When the cases were evaluated as two groups according to the cut-off value of 156; total 3-month mortality was statistically increased (χ2=6.896, P<0.01) and when the cases were evaluated as two groups according to the based NLR cut-off value of 3.56; hospital mortality, 3th month mortality and total 3-month mortality was statistically increased (χ2=4.771, P<0.05; χ2=4.383, P<0.05; χ2=9.101, P<0.01 respectively). CONCLUSIONS: PLR and NLR increased in patients with high risk, and PLR may have predicting value for 3-month mortality while NLR may have predicting value for hospital mortality, 3th month mortality and total 3-month mortality in patients with APE.

Serum Cystatin C Levels in COPD: Potential Diagnostic Value and Relation between Respiratory Functions.

BACKGROUND: The aim of this study was to determine the level of serum cystatin C (CysC) in patients with Chronic Obstructive Pulmonary Disease (COPD) during exacerbation and stable periods and to investigate its potential diagnostic value and the relationship between CysC levels and the pulmonary function test (PFT). METHODS: One hundred twenty-six patients with COPD (68 in stable periods, 58 during exacerbation periods) and 50 healthy subjects were included in the study. PFT, body mass index (BMI), white blood cell counts, C-reactive protein (CRP), serum urea and creatinine levels were evaluated in both groups of patients. CysC levels were measured in all participants. RESULTS: Serum CysC levels were statistically higher in both COPD groups than the control group (p<0.001 for both) although there was no statistically significant difference between COPD groups (p>0.05). CysC levels showed negative correlation with forced expiratory volume in 1 second (FEV1) and a positive correlation with C-reactive protein (CRP) levels in patients with stable COPD. There was a positive correlation between serum CysC levels and serum urea, creatinine, CRP levels in patients with COPD exacerbation (r=0.333, p=0.011; r=0.260, p=0.049; r=0.414, p<0.01 respectively). When stable COPD and control groups were evaluated, serum CysC had an area under the curve (AUC) in the receiver operating characteristic (ROC) curve of 0.951 (0.909-0.994 95% CI: p<0.001). CONCLUSIONS: Our results showed that CysC levels increased in both COPD groups. Increased CysC levels may be related with lung function decline and inflammation in COPD patients. In addition, CysC levels may be a potential indicator for the diagnosis of COPD.

Can ADMA play a role in determining pulmonary hypertension related to chronic obstructive pulmonary disease?

BACKGROUND AND AIMS: Asymmetric dimethylarginine (ADMA) decreases the levels of nitric oxide by inhibiting nitric oxide synthases. In this study, the possible role of ADMA in determining pulmonary hypertension (PH) in chronic obstructive pulmonary disease (COPD) patients was investigated. METHODS: Stable COPD patients who were admitted to pulmonology outpatient clinic were involved in the study. Forty healthy volunteers, with similar ages and sexes, were accepted as the control group. COPD patients were divided into two groups: 40 patients without PH (COPD group) and 40 COPD-related PH patients (COPD-PH group). Pulmonary function test, echocardiography and arterial blood analyses of all patients were performed. RESULTS: The mean age of patients was 69.21 ± 10.62, and 15 of these patients were females. There was no significant difference between the two COPD groups in terms of age and sex (P > .05). There was no difference in PaO2 , SaO2 , FEV1 and FEV1 /FVC values between the two COPD groups (P > .05). Serum ADMA levels were similar in the control and the COPD group (0.42 ± 0.13 vs 0.43 ± 0.15), but it was significantly higher in the COPD-PH group compared to the control and the COPD group (0.49 ± 0.14). A negative correlation was determined between serum ADMA levels and SaO2 levels (r = -.247, P = .028). A significant positive correlation observed between ADMA and systolic pulmonary artery pressure values (r = .627, P < .001) CONCLUSIONS: In conclusion, high levels of serum ADMA levels may be able to determine the presence of PH.

The Importance of Neutrophil-to-Lymphocyte Ratio in Chronic Obstructive Pulmonary Disease.

OBJECTIVES: Chronic obstructive pulmonary disease (COPD) is a common lung disease characterized by airflow limitation and systemic inflammation. Recently, neutrophil-to-lymphocyte ratio (NLR) has gathered increasing interest in the detection of inflammation in inflammatory diseases. This study aimed to investigate the role of NLR in COPD for identifying the detection of inflammation and recognition of acute exacerbation. MATERIAL AND METHODS: The laboratory results of 103 COPD patients were included into the study, of which 47 patients were in acute exacerbation and 56 patients were at stable period, and there were 40 gender and age-matched healthy controls. Complete blood count (CBC), C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were evaluated. NLR was calculated from CBC. RESULTS: NLR values of patients with COPD (both acutely exacerbated and stable) were found significantly higher than those of the controls (p< 0.001, p< 0.05; respectively). In all patients with COPD, NLR values positively correlated with serum CRP (r= 0.641, p< 0.001) and ESR (r= 0.276, p= 0.005) levels and negatively correlated with forced vital capacity (r= -0.20, p= 0.043) and forced expiratory volume in the 1st second (r= -0.288, p= 0.003). For an NLR cutoff of 3.34, sensitivity for detecting exacerbation of COPD was 78.7% and specificity was 73.2% (AUC 0.863, p< 0.001). CONCLUSION: Our results suggest that NLR may be considered as a reliable and simple indicator in the determination of increased inflammation in patients with COPD. Furthermore, NLR could be useful for the early detection of possible acute exacerbations in patients with COPD.

Serum Heat Shock Protein Levels and the Relationship of Heat Shock Proteins with Various Parameters in Chronic Obstructive Pulmonary Disease Patients.

OBJECTIVES: Chronic Obstructive Pulmonary Disease (COPD) is accompanied by increased cellular stress and inflammation. Most of the Heat Shock Proteins (HSPs) have strong cytoprotective effects. The role of HSPs in COPD pathogenesis has not determined completely. We investigated the serum level of HSPs in COPD patients, smokers without COPD and healthy non-smoking controls. Also, we evaluated the relationship of HSPs with various parameters (inflammatory, oxidative, functional status, quality of life) in COPD patients. MATERIAL AND METHODS: The levels of stress protein (HSP27, HSP70, HSP60, HSP90, CyPA), interleukin-6, C-reactive protein and malondialdehyde were measured in 16 healthy non-smoker, 14 smokers without COPD and 50 patients with stable COPD. Pulmonary function tests (PFT) and arterial blood gases parameters were measured. Health Related Quality of Life was evaluated and exercise capacity was measured with 6 minute walking test. RESULTS: Only HSP27 levels was significantly higher in COPD patients when compared with both healthy non-smoker and smokers without COPD (for both, p< 0.001). There was a weak-moderate negative correlation between serum levels of HSP27 and PFT parameters and between HSP27 levels and PaO2. Serum levels of HSP27 showed a weak-moderate positive correlation with symptom, activity and total scores. Subjects evaluated only smokers without COPD and patients with COPD; HSP27 had an area under the curve (AUC) in the receiver operating characteristic (ROC) curve of 0.819 (0.702-0.935; 95% CI; p= 0.000). CONCLUSION: Increased serum levels of HSP27 was found in COPD patients and our results showed sensitivity and specificity of serum HSP27 as diagnostic markers for COPD.