Browsing by Author "Öztürk, Nilufer Aylin Acet"

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Comorbid conditions and social determinants of smoking in an adult population
(Turkish Green Crescent Soc, 2019-12-01) Güçlü, Özge Aydın; Öztürk, Nilufer Aylin Acet; GÖREK DİLEKTAŞLI, ASLI; ACET ÖZTÜRK, NİLÜFER AYLİN; DEMİRDÖĞEN, EZGİ; Demirdöğen, Ezgi; Uzaslan, Esra; UZASLAN, AYŞE ESRA; Karadağ, Mehmet; KARADAĞ, MEHMET; Bursa Uludağ Üniversitesi/Tıp Fakültesi/Göğüs Hastalıkları Anabilim Dalı.; 0000-0003-1005-3205; 0000-0002-6375-1472; 0000-0001-7099-9647; 0000-0002-7400-9089; 0000-0002-9027-1132; Z-1424-2019; AAG-8744-2021; JPK-7012-2023; AAH-9812-2021
Tobacco smoking is a significant risk factor for a variety of chronic disorders, such as chronic obstructive pulmonary disease (COPD), lung cancer, cardiovascular diseases, and other forms of malignancies. In this study, we investigated the comorbid medical conditions and sociodemographic features that contribute to disparities in tobacco smoking prevalence in the adult population. We induded volunteers who participated in events for the "World COPD day" in 4 consecutive years (i.e., 2014, 2015, 2016, and 2017) held in Bursa, Turkey. Sociodemographic features, smoking characteristics, and comorbidities were recorded. A total of 747 volunteers who were 47.1 +/- 14.5 [16-84] years of age and smoked 24.1 +/- 20.91 pack-years were included. The study population consisted of 405 (54.2%) males, 36.3% of which were current smokers, 23.6% exsmokers, and 40.2% nonsmokers. Moreover, 15.7% of participants with asthma were nonsmokers and 9.4% ever-smoker (p=0.011), while 2% of participants with coronary artery disease (CAD) were nonsmoker and 6.7% were ever-smoker (p=0.003). Current smoker participants exhibited more symptoms such as cough. sputum, and wheezing (p<0.001, in both cases). In this study, we found that the factors associated with smoking in the general population are male gender and higher educational level.
Development and validation of a simple risk scoring system for a COVİD-19 diagnostic prediction model
(Tüberküloz ve Toraks, 2023-01-01) Güçlü, Özge Aydın; Ursavaş, Ahmet; Ocakoğlu, Gokhan; Demirdogen, Ezgi; Öztürk, Nilufer Aylin Acet; Topçu, Dilara Ömer; Terzi, Orkun Eray; Onal, Uğur; Dilektaşlı, Aslı Görek; Sağlık, İmran; Coşkun, Funda; Ediger, Dane; Uzaslan, Esra; AkalIn, Halis; Karadağ, Mehmet; AYDIN GÜÇLÜ, ÖZGE; URSAVAŞ, AHMET; OCAKOĞLU, GÖKHAN; DEMİRDÖĞEN, EZGİ; ACET ÖZTÜRK, NİLÜFER AYLİN; ÖMER TOPÇU, DİLARA; TERZİ, ORKUN ERAY; ÖNAL, UĞUR; GÖREK DİLEKTAŞLI, ASLI; SAĞLIK, İMRAN; COŞKUN, NECMİYE FUNDA; EDİGER, DANE; UZASLAN, AYŞE ESRA; AkalIn, Halis; KARADAĞ, MEHMET; Uludağ Üniversitesi/Tıp Fakültesi/Göğüs Hastalıkları Anabilim Dalı; Uludağ Üniversitesi/Tıp Fakültesi/Biyoistatistik Anabilim Dalı; Uludağ Üniversitesi/Tıp Fakültesi/Enfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Anabilim Dalı; 0000-0003-1005-3205; 0000-0002-1114-6051; 0000-0002-7400-9089; 0000-0002-6375-1472; 0000-0001-7099-9647; 0000-0002-2954-4293; 0000-0001-7530-1279; 0000-0002-9027-1132; AAH-5180-2021; A-4970-2019; AAG-8744-2021; AAI-3169-2021; JCO-3678-2023; JPK-7012-2023
Introduction: In a resource-constrained situation, a clinical risk stratification system can assist in identifying individuals who are at higher risk and should be tested for COVID-19. This study aims to find a predictive scoring model to estimate the COVID-19 diagnosis.Materials and Methods: Patients who applied to the emergency pandemic clinic between April 2020 and March 2021 were enrolled in this retrospective study. At admission, demographic characteristics, symptoms, comorbid diseases, chest computed tomography (CT), and laboratory findings were all recorded. Development and validation datasets were created. The scoring system was performed using the coefficients of the odds ratios obtained from the multivariable logistic regression analysis.Results: Among 1187 patients admitted to the hospital, the median age was 58 years old (22-96), and 52.7% were male. In a multivariable analysis, typical radiological findings (OR= 8.47, CI= 5.48-13.10, p< 0.001) and dyspnea (OR= 2.85, CI= 1.71-4.74, p< 0.001) were found to be the two important risk factors for COVID-19 diagnosis, followed by myalgia (OR= 1.80, CI= 1.082.99, p= 0.023), cough (OR= 1.65, CI= 1.16-2.26, p= 0.006) and fatigue symptoms (OR= 1.57, CI= 1.06-2.30, p= 0.023). In our scoring system, dyspnea was scored as 2 points, cough as 1 point, fatigue as 1 point, myalgia as 1 point, and typical radiological findings were scored as 5 points. This scoring system had a sensitivity of 71% and a specificity of 76.3% for a cut-off value of >2, with a total score of 10 (p< 0.001).Conclusion: The predictive scoring system could accurately predict the diagnosis of COVID-19 infection, which gave clinicians a theoretical basis for devising immediate treatment options. An evaluation of the predictive
Is serum iron responsive protein-2 level associated with pulmonary functions and frequent exacerbator phenotype in copd?
(Turkish Assoc Tuberculosis & Thorax, 2020-01-01) Öztürk, Nilufer Aylin Acet; ACET ÖZTÜRK, NİLÜFER AYLİN; Dilektaşlı, Aslı Görek; GÖREK DİLEKTAŞLI, ASLI; Demirdoğen, Ezgi; DEMİRDÖĞEN, EZGİ; Coşkun, Funda; COŞKUN, NECMİYE FUNDA; Ursavas, Ahmet; URSAVAŞ, AHMET; Karadağ, Mehmet; KARADAĞ, MEHMET; Uzaslan, Esra Kunt; Bursa Uludağ Üniversitesi/Tıp Fakültesi/Göğüs Hastalıkları Anabilim Dalı.; 0000-0002-6375-1472; 0000-0001-7099-9647; 0000-0002-7400-9089; 0000-0003-3604-8826; 0000-0002-9027-1132; JPK-7012-2023; Z-1424-2019; AAI-3169-2021; AAD-1271-2019; AAH-9812-2021; AAI-1004-2021; AAG-8744-2021
Introduction: Chronic Obstructive Pulmonary Disease (COPD) exacerbations contribute to the overall severity in individual patients because they are associated with airway inflammation, pulmonary function loss, decreased quality of life and increased mortality. Although, identifying frequent exacerbator patients is important due to severe outcomes associated with frequent exacerbator phenotype in COPD patients there is no single biomarker which can differentiate this phenotype. Iron responding protein-2 (IRP2) is the protein product of IREB2 gene, which is a COPD susceptibility gene that regulates cellular iron homeostasis and has a key role in hypoxic conditions. Previous research indicates that IREB2 expression in lung tissue is associated with spirometric measurements and emphysema in COPD. In this study, our aim was to investigate whether serum IRP2 levels were associated with frequent exacerbator phenotype, to evaluate whether IRP2 levels in serum are associated with pulmonary functions and selected systemic inflammation biomarkers.Materials and Methods: Designed as a single tertiary care center based, cross-sectional study, included high risk (GOLD C, D) COPD patients who admitted to outpatient clinic consecutively between December 2015 and July 2016.Results: The study included 80 COPD patients. Serum IRP2 levels were negatively correlated with FEV ml (r= -0.25, p= 0.02) and body weight (r= -0.35, p= 0.002) but not with markers of systemic inflammation. COPD patients with at least one exacerbation history in the last year tended to have higher 1RP2 levels than patients without any exacerbation (12.3 (IQR 25-75: 10.417.1) vs 10.5 (1QR 25-75: 8.8-18.5), p= 0.061.Conclusion: Serum IRP2 level is significantly correlated with FEV1 mL but not with FEV1 predicted and cannot be used to differentiate frequent exacer bator patients. Although IREB2 gene expressions in lung tissue and bronchoalveolar lavage results have significant associations with emphysema and FEV1/FVC, FEV1 %predicted in COPD patients, our results suggests serum IRP2 level is not as promising.