View clinical trials related to Risk Factors.
Filter by:The goal of this observational study is to establish and verify the Chinese version of surgical risk assessment system and explore its clinical application. The main questions it aims to answer are: The process of establishing a Chinese version of surgical risk assessment system; What is the accuracy of the system; How can the system be used in clinic; How does this system compare with other systems (such as NSQIP). Participants will comprehensively collect the general information, examination and pathological information of the patients, using machine learning and artificial intelligence methods for data processing. Finally, the Chinese version of the surgical risk assessment system will be established. After the system is established, investigators will evaluate the accuracy of the system and compare it with other related systems.
The goal of this observational study is to identify the risk factors for early acute lung injury (ALI) after liver transplantation in children .The main questions it aims to answer are what the risk factors are for early ALI in children and to evaluate the predictive value for the development of ALI.Participants will be divided into non-ALI group and ALI group according to whether they had ALI in a week after liver transplantation.Researchers will compare the difference between the two groups and use multivariate logistic regression analysis to screen the risk factors of ALI, and receiver operating characteristic(ROC) curve was used to evaluate the predictive efficacy of risk factors.
In the previous investigation, investigators found that when the risk factors of stress injury in critical patients changed, clinical nurses lacked the awareness of evaluating the risk of stress injury, and lacked the risk assessment of this link. The stress risk prediction model is based on etiology. By analyzing the risk factors, the machine learning algorithm is used to evaluate the risk of pressure damage, and the prediction model of pressure damage can dynamically and comprehensively evaluate its risk. It is also a risk assessment tool. At present, there is no research on applying the stress injury risk prediction model of critical patients to the intensive care information software in China. In this study, the artificial intelligence algorithm library will be used to construct and apply the stress injury risk prediction model for critical patients.
The incidence rate of drug-induced blood diseases accounts for about 10% of all drug-induced diseases, most of which are serious at the time of onset, and the mortality rate can be as high as 32.5%. In this study, cefoperazone sulbactam sodium, which is commonly used in clinic, was selected as the target drug, and the epidemiological characteristics of drug-induced coagulation dysfunction and the construction of risk factor models were studied by single factor and multiple factor Logistic regression analysis.
Postoperative pulmonary complications are important factors affecting the prognosis of patients undergoing surgery. Studies have shown that patients undergoing abdominal or pelvic surgery, emergency surgery, or prolonged surgery are more likely to develop PPCs, especially when robot-assisted laparoscopic surgery is performed at extreme head low. The incidence of PPCs and associated risk factors in patients undergoing robot-assisted laparoscopic surgery compared with those undergoing conventional surgery should be re-examined.
Autoimmune hepatitis (AIH) is a chronic liver disease, which is characterized by the increase of immunoglobulin G (IgG) level, the presence of auto-antibodies and a typical histology, in the absence of other liver disease. Due to the heterogeneity of AIH manifestations, different scoring systems have been validated in order to make a reliable diagnosis. The two most recent scoring systems are: the revised International Autoimmune Hepatitis Group (IAIHG) criteria and the IAIHG simplified criteria. The second one is recommended by the European Association for the Study of the Liver (EASL) clinical practice guidelines (CPGs). The EASL clinical practice guidelines suggests that the treatment of ASAIH (Acute Severe AIH) is high doses of corticosteroids (superior to 1mg/kg/day) as early as possible and a lack of improvement within seven days should lead to listing for emergency liver transplantation (LT). However, the "lack of improvement" is not objectively defined and the grading of recommendation is III (Opinions of respected authorities). The hypothesis of the study is that the previously developed decisional score on a retrospective series will prospectively allow the differentiation between patients with ASAIH (Acute Severe AIH) who respond to corticosteroid therapy and should be maintained on treatment and patients who do not respond and should be rapidly evaluated for LT. The score will be computed at day 3 since corticosteroid introduction.
Despite the extensive research on prevention and prediction strategies, hamstrings strains injury (HSI) persists at a high rate in team sports and specifically in football. An initial injury increases the risk for re-injury and affects performance, whereas the financial cost for athletes and teams is crucial due to the time needed for appropriate rehabilitation. For that reason, it is critical to formulate better strategies in order to predict and prevent HSI. This study aims to develop a system dynamics (SD) model to evaluate HSI risk. First, a literature review will be carried out on the current approaches and identification of intrinsic and extrinsic risk factors of hamstrings strain injuries. Second, co-creation workshops based on the method of Group Modeling Building (GMB) will be applied to develop the SD for the HSI model. This co-creation process will involve stakeholders such as sports physiotherapists, doctors, and sports scientists. After creating the SD for HSI model, a one-year prospective cohort study will be performed to validate the model with real data and evaluate the ability of the model to predict HSIs. Sports teams will be invited to take part in the validation of the model. Multiple biomechanical parameters and other personal characteristics will be collected. Then, athletes will be monitored for the occurrence of injury and their exposure to injury risk during training and games. The factors' non-linear interaction will be assessed with the statistical method of structural equation modeling and factor analysis. In this way, the factors' interactions extracted for the qualitative phase of the study (group modeling building process) will be quantitatively evaluated. Validating the model with real data will provide a computer simulation platform to test plausible strategies for preventing hamstrings strain injuries prior to implementation and optimize intervention programs.
A cross-sectional household survey with two-stage cluster-randomized sampling. This cross-sectional household survey design to recruit a random sample of households that is representative for each of the study sites. From the selected households, all consenting, household members will be included in the study. This study is funded by the UK Wellcome Trust. The grant reference number is 215604/Z/19/Z
Breast cancer is the most frequently diagnosed malignant tumor in women. In 2018, in Spain, the estimated incidence was 101/100,000 women. Screening strategies and greater knowledge of risk factors by the population have contributed to a better prognosis. Specifically, in the case of behavioral factors, making women aware of their influence enables them to establish preventive measures themselves. Technologies are becoming a channel of communication, from a healthcare perspective, between the population and healthcare personnel. There are even specific terms like eHealth or mHealth. There is beginning to be evidence that collects the benefits and ways of using web-apps to achieve modification of risky behaviors and/or behaviors to prevent pathologies are acquired. The use of digital media, such as a web-app, to publicize BC risk factors makes it possible to specifically establish measures aimed at reducing its prevalence, which in turn will contribute to reducing the number of cases of BC. CM. On the other hand, making women aware of their BC risk factors, as well as quantifying the risk of developing the tumor, is useful for them to become aware of the magnitude of the problem and adopt measures to minimize their risk. Since there is no digital strategy in Asturias that informs and reduces the risk of developing breast cancer, through the modification of the main risk factors, in young women, the present study has been proposed with the aim of evaluating the effectiveness and feasibility of an educational intervention for BC risk prevention through the use of a Web-App in women residing in health area VII of the Principality of Asturias.
The overall goals of this project are to evaluate the feasibility of web-based nurse-led motivational interviewing and educational interventions to promote healthy behaviours for obesity prevention and maintenance of healthy weight and behaviours among young adults attending university (age 18-29) in Hamilton, Ontario. A secondary goal is to evaluate if the intervention is more successful among people at higher risk of obesity (a risk stratification approach). A pilot randomized controlled trial will be conducted. Young adults will be randomized to receive a tailored behavioural intervention through motivational interviewing sessions with a nurse combined with educational materials, or control (educational materials only). Both groups will be followed for 6 months and their weight at baseline and end of the study will be measured. Outcomes related to the feasibility of the intervention and participants' experiences in the study will also be measured.