ABSTRACT
Background: Determining cardiovascular disease (CVD) research priorities is essential given the high burden of these diseases, limited financial resources, and competing priorities. This study aimed to determine the research priorities in CVD field in Iran using standard indigenous methods. Materials and Methods: An extensive search was done in relevant international and national studies. Then, an indigenous standard multistage approach based on multicriteria decision analysis steps was adapted to local situation and implemented. This process included forming a working group of experts in priority setting methodology, identifying the context and prioritization framework, discussing the methodology with the National Network of CVD Research (NCVDR) members who ultimately determined the priority research topics, weighted topics criteria, ranked topics, and reviewed all determined research priorities for final report. Results: Thirteen cardiovascular research priorities were determined by the NCVDR members. The first five priorities based on their scores include studies in hypertension, prevention and control of ischemic heart disease (IHD) and its risk factors, burden of IHD, Registration of CVDs, and COVID-19 and CVDs. Conclusion: Cardiovascular research priorities were determined using a standard indigenous approach by national experts who are the NCVDR members. These priorities can be used by researchers and health decision makers.
ABSTRACT
BACKGROUND: Already at hospital admission, clinicians require simple tools to identify hospitalized COVID-19 patients at high risk of mortality. Such tools can significantly improve resource allocation and patient management within hospitals. From the statistical point of view, extended time-to-event models are required to account for competing risks (discharge from hospital) and censoring so that active cases can also contribute to the analysis. METHODS: We used the hospital-based open Khorshid COVID Cohort (KCC) study with 630 COVID-19 patients from Isfahan, Iran. Competing risk methods are used to develop a death risk chart based on the following variables, which can simply be measured at hospital admission: sex, age, hypertension, oxygen saturation, and Charlson Comorbidity Index. The area under the receiver operator curve was used to assess accuracy concerning discrimination between patients discharged alive and dead. RESULTS: Cause-specific hazard regression models show that these baseline variables are associated with both death, and discharge hazards. The risk chart reflects the combined results of the two cause-specific hazard regression models. The proposed risk assessment method had a very good accuracy (AUC = 0.872 [CI 95%: 0.835-0.910]). CONCLUSIONS: This study aims to improve and validate a personalized mortality risk calculator based on hospitalized COVID-19 patients. The risk assessment of patient mortality provides physicians with additional guidance for making tough decisions.