Meslek Yüksek Okulları / Vocational Schools

Permanent URI for this communityhttps://hdl.handle.net/11727/1410

Browse

Filters

2021 - 20243

Settings

Start date: 2020Subject: search.filters.subject.COVID-19

Search Results

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    Comparison Of Efficacy And Reliability Of Six Commercial Covid-19 Diagnostic PCR Kits
    (Başkent Üniversitesi Kazan Meslek Yüksek Okulu, 2024-03-26) Sharafi, Parisa; Gokdemir, F. Seyma; Akyol, Mesut; Ardicoglu-Akisin, Yasemin; Gocmen, J. Sedef; Taylan-Ozkan, Aysegul
    Objectives. All countries have been deeply affected by the coronavirus disease 2019 pandemic, both economically and in situations that strain health systems, such as workforce and workload. Therefore, various measures should be taken to control the disease and prevent its spread. Since the disease onset, real-time PCR tests have been used as the gold standard for disease diagnosis. Owing to the rapid progress of the pandemic and the spread of the disease, validation, consistency, and optimization tests of some commercial kits have been conducted directly in the field. Therefore, it is important to compare the results of these kits and improve the existing ones. Methods. We compared five kits (Bioexen, Polgen, Coronex, Diagen, and Anatolia) donated to the TOBB Economics and Technology University Hospital PCR laboratory with the KrosGen kit to detect severe acute respiratory syndrome coronavirus 2. A total of 244 samples were selected and analyzed using five different severe acute respiratory syndrome coronavirus 2 PCR detection kits. Results. Positive and negative results from the six kits were compared using the working protocols of the kits, primers, and cycle threshold (Ct) values. Five of the six kits have reliable compatibility for Ct<30 but decreases for Ct >= 30. Therefore, it is important to evaluate the performance of these kits for reduced viral loads. Conclusions. Using a suitable kit with high compatibility for Ct >= 30 is important for detecting patients with a low viral load and helping prevent disease spread.
  • No Thumbnail Available
    Item
    Detecting COVID-19 from Respiratory Sound Recordings with Transformers
    (2022) Aytekin, Idil; Dalmaz, Onat; Ankishan, Haydar; Saritas, Emine U.; Bagci, Ulas; Cukur, Tolga; Celik, Haydar; Drukker, K; Iftekharuddin, KM
    Auscultation is an established technique in clinical assessment of symptoms for respiratory disorders. Auscultation is safe and inexpensive, but requires expertise to diagnose a disease using a stethoscope during hospital or office visits. However, some clinical scenarios require continuous monitoring and automated analysis of respiratory sounds to pre-screen and monitor diseases, such as the rapidly spreading COVID-19. Recent studies suggest that audio recordings of bodily sounds captured by mobile devices might carry features helpful to distinguish patients with COVID-19 from healthy controls. Here, we propose a novel deep learning technique to automatically detect COVID-19 patients based on brief audio recordings of their cough and breathing sounds. The proposed technique first extracts spectrogram features of respiratory recordings, and then classifies disease state via a hierarchical vision transformer architecture. Demonstrations are provided on a crowdsourced database of respiratory sounds from COVID-19 patients and healthy controls. The proposed transformer model is compared against alternative methods based on state-of-the-art convolutional and transformer architectures, as well as traditional machine-learning classifiers. Our results indicate that the proposed model achieves on par or superior performance to competing methods. In particular, the proposed technique can distinguish COVID-19 patients from healthy subjects with over 94% AUC.
  • No Thumbnail Available
    Item
    Factors Affecting Nurses' Professional Commitment During the COVID-19 Pandemic: A Cross-Sectional Study
    (2021) Duran, Secil; Celik, Isa; Ertugrul, Bekir; Ok, Serife; Albayrak, Sevil; 33794061
    Aim This study aims to investigate the factors affecting nurses' professional commitment during the COVID-19 pandemic. Background Commitment to a profession requires doing the best for that profession. In the case of the nursing profession, professional commitment gains greater importance in times of crisis, like the COVID-19 pandemic. Methods This cross-sectional study was conducted with 389 nurses in the Turkish state hospital. Institutional permissions, ethical approval and written consents from the participants were obtained before carrying out the study. Results The participants' mean Perceived Organizational Obstruction Scale score was 20.07 +/- 8.06 (min = 5.0, max = 35.0), and their mean Nursing Professional Commitment Scale score was 71.20 +/- 11.94 (min = 30.0, max = 103.0). Socio-demographic variables and perception of organisational obstruction predicted 36.7% of the variance in the professional commitment (p < .001). Conclusion A road map based on the study results was developed for hospitals and nurse managers to maintain and increase nurses' professional commitment. Implications for Nursing Management The results of this study may help institutions and nurse managers understand the factors affecting professional commitment during the pandemic as a whole, as well as determine primary strategies based on the importance of these factors.