There are about 15072 clinical studies being (or have been) conducted in Turkey. The country of the clinical trial is determined by the location of where the clinical research is being studied. Most studies are often held in multiple locations & countries.
The aim of the study is to investigate the potential effects of face-to-face supervised tele-rehabilitation to home exercise program on walking speed, handgrip strength, muscle endurance, quality of life, physical activity level and perceived respiratory disability in COVID-19 patients who hospitalized in ICU due to ARDS and discharged from hospital.
Systemic sclerosis (SSc) is a heterogeneous autoimmune disease characterized by fibrosis of the skin and internal organs. Hand involvement is one of the most observed musculoskeletal involvements in patients with SSc, which can impact on general health, quality of life, and psychological status. Hand exercise programs can help patients to improve not only hand function but also general health status; nevertheless, further randomized control trials (RCTs) are needed to clarify its effect. Hence, the investigators aimed to investigate the effectiveness of home-based, self-administered exercise program for hands in patients with SSc and demonstrate the improvements in general health status.
In gastric cancer, laparoscopic gastrectomy is commonly performed in Asian countries. In other regions where tumor incidence is relatively low and patient characteristics are different, developments in this issue have been limited. In this study, the investigators aimed to compare the early results for patients who underwent open or laparoscopic gastrectomy for gastric cancer in a center in Turkey.
Knee osteoarthritis is a common disease that causes pain and loss of function. Total Knee Arthroplasty (TKA) is a frequently used surgical method in the treatment of severe knee osteoarthritis. The aim of this study was to investigate the effect of TKA on IL-6, TNF-α and IL-1β cytokine levels, pain intensity at rest and walking, knee joint valgity angle,malaligment, functional status and knee joint position sense.
The aim of this randomized, controlled, prospective clinical trial is to evaluate the performances of a universal adhesive in three different application modes, a self-etch adhesive and an etch&rinse adhesive in restoration of non-caries cervical lesions. Thirty-four patients will receive restorations. Lesions will be divided into 5 groups according to adhesive systems and application modes: CU-SE: Clearfil Universal Bond Quick in self-etch mode, CU-SLE: Clearfil Universal Bond Quick in selective etch mode, CU-ER: Clearfil Universal Bond Quick in etch&rinse mode, CSE: Clearfil SE Bond, TB: Tetric N-Bond. Restorations (Tetric N-Ceram composite) will be scored with regard to retention, marginal discoloration, marginal adaptation, recurrent caries and post operative sensitivity using modified USPHS criteria after 48 months. Two examiners who is not involved in the placement of restorations will conduct the evaluations. Descriptive statistics will be performed using Chi-square tests.
The study was planned as a prospective randomized controlled clinical trial to determine the effect of thermal evaluation in preventing diabetic foot ulcers in patients with Type II Diabetes Mellitus (DM).
COVID-19, which emerged in China in December 2019, has become a pandemic with its spread to many countries of the world. Although it is suggested that hospital admissions are reduced due to some reasons such as trauma, during COVID-19 pandemic, it is controversial whether in-hospital mortality rates changed. Therefore this multi-centered study aimed to determine how in-hospital mortality effected during the pandemic period according to the specific patient groups.
COVID-19, which emerged in China in December 2019, has become a pandemic with its spread to many countries of the world. Emergency departments also carried out an important part of the fight against pandemics in our country/Turkey. The emergency department including an intensive care unit is very few in this country/Turkey and the only hospital, which has an Emergency Intensive Care Unit (EICU) in Istanbul, is the study center. Therefore, this retrospective study aimed to provide useful information about how an effective EICU should be, especially how to use them during pandemic periods.
COVID-19 is an infectious disease caused by a newly discovered Coronavirus which was first identified in Wuhan, China in December 2019. Then the novel coronavirus outbreak was described and announced as a pandemic by World Health Organization (WHO) on March 11, 2020. Reverse transcription-polymerase chain reaction (RT-PCR) is currently the gold standard test for diagnosis of COVID-19. Nevertheless, due to its high false-negative rates (%10-50), diagnosis and treatment decisions do not depend on RT-PCR alone. Clinical presentation of patient and radiological findings are also important. However, neither clinical presentation nor computed tomography (CT) findings are specific for COVID-19. As a consequence of these challenges, the diagnosis of the disease and the protection of the community health become more difficult. The investigators of this study hypothesized that deep learning-based decision support system may help for definitive diagnosis of COVID-19. The aim is to develop a deep learning-based decision support system algorithm based on clinical presentation of patient, laboratory and CT findings and RT-PCR data. Previously, deep learning algorithms with the use of widely known deep neural network architectures such as Inception, UNet, ResNet were developed. However all of these studies were based on CT findings. There are not any deep learning study in literature combining the clinical, radiological, and laboratory findings of patients. The project is based on the available data of COVID-19 patients that will be obtained from the Ministry of Health. Then the data will be evaluated for relevance and reliability and labeled for the training of machine. Following the anonymization of data, data will be processed according to the predetermined inclusion-exclusion criteria. Thorax CT data will be labeled as typical / indeterminate / atypical / negative for COVID-19 pneumonia. Also, CT images of patients with known non-COVID-19 diseases will be labeled for the training of machine. Then, fever, lymphocyte count, neutrophil to lymphocyte ratio, contact information, RT-PCR findings will be labeled. Subsequently, the patients will be labeled and the machine will be trained with deep learning method with the help of this grouped and labeled data. Following the training phase, the algorithm will be tested and if the machine reaches the target specificity and sensitivity, the prototype will be tested. And then, the prototype will be embedded into the hospital software system. This software and algorithm will serve as an early warning system for clinicians and provide a better diagnostic rate especially with decreasing false-negative results. The effects of a pandemic cannot be measured by only the number of people diagnosed and isolated, or treatment provided. A pandemic affects not only community health but also individuals' psychological status, education, teaching methods, working models, daily lifestyles, producer/consumer behaviors, supply/demand balance; in other words every single area of life. On top of that, a pandemic causes long-term damages hard to reverse. The software will increase the diagnostic success rates, help to control the pandemic and minimize the collateral damages mentioned above. The investigators believe that, the product that will be produced at the end of this project will be of great benefit in controlling the secondary wave of COVID-19 expected to occur.
COVID-19, which emerged in China in December 2019, has become a pandemic with its spread to many countries of the world. Mortality rates of COVID-19 pandemics vary between countries. It is known that mortality based on COVID-19 is higher in old population. Therefore the aim of this study to analyze the experience of 7 governmental hospitals in terms of patient characteristics, possible risk factors of mortality based on COVID-19.