Analysis of the effectiveness of a risk stratification protocol based on clinical and physical parameters for the occurrence of signs and symptoms in cardiovascular rehabilitation programs

• Grant number: 23/00543-6
• Support Opportunities: Scholarships in Brazil - Master
• Start date: May 01, 2023
• End date: June 30, 2024
• Field of knowledge: Health Sciences - Physiotherapy and Occupational Therapy
• Principal Investigator: Luiz Carlos Marques Vanderlei
• Grantee: Jéssica Malek da Silva
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil

Abstract

Introduction: Cardiac risk stratification is an essential procedure for correctly prescribing exercise intensity and defining the level of monitoring for patients in cardiovascular rehabilitation programs (PRCV). However, the available stratification protocols do not have a good predictive capacity for the occurrence of signs and/or symptoms, which generally precede major acute events in these programs, which led to the development of a protocol for this purpose, which now needs to be evaluated. Objectives: To evaluate the effectiveness of the cardiac risk stratification protocol developed, to verify the correlation between the risk class determined by the protocol and the occurrence of signs and symptoms, and to assess whether the protocol will have good predictive power for the occurrence of signs and symptoms in PRCV. Material and Methods: Observational longitudinal cohort study, which will evaluate the effectiveness of a risk stratification protocol (n=70). After evaluating the clinical and physical variables used in the protocol, risk stratification will be performed and this sample will be monitored for 24 sessions so that the occurrence of signs and/or symptoms is verified. For data analysis, data normality will be checked using the Shapiro-Wilk test. The relationship between the number of signs and symptoms and their risk class will be evaluated by Pearson or Spearman correlation (according to the normality of the data), and the concordance between the risk class and the number of signs and symptoms that have occurred will be calculated. using the Kappa intraclass correlation coefficient (ICC). The power of the protocol to predict the occurrence of signs and symptoms according to the risk class will be evaluated using the intraclass correlation coefficient and ROC curve.