RESUMO
There are vast numbers of evidenced-based clinical trials produced each year, making it increasingly difficult to stay up to date with new treatments and protocols designed to provide the most optimal patient care. A physician's ability to combine existing knowledge with new data is limited by a basic understanding of the background statistics used in these studies. Our goal is to not only define the basic statistics commonly used in clinical trials but to also ensure that practitioners are able to have a working understanding of these statistical measurements to effectively make the most informed and efficacious decisions regarding patient management. On the basis of the recent growth of empirical spine literature, it is becoming more important for spine surgeons to have the basic statistical background necessary to efficiently interpret new data, which may affect clinical decision making regarding patient care.
Assuntos
Ortopedia/normas , Coluna Vertebral/cirurgia , Cirurgiões , Algoritmos , Interpretação Estatística de Dados , Tomada de Decisões , Medicina Baseada em Evidências , Humanos , Ortopedia/métodos , Qualidade de Vida , Análise de Regressão , Reprodutibilidade dos Testes , Projetos de Pesquisa , Risco , Fatores de Risco , Estatística como AssuntoRESUMO
With the rapid rise of clinical spine surgery literature in the last few decades, there is a greater need for practicing spine surgeons to confidently analyze and critique published literature within the field. The conclusions drawn from published studies are often integrated into a physician's clinical decision-making. A strong knowledge in the fundamental statistical measurements used most frequently in spine surgery literature can enhance the ability to properly interpret the meaning of a study's results. However, medical education often lacks the incorporation of clinically relevant statistical analysis. The purpose of this review is to provide an overview of some of the most commonly used statistical measurements in spine surgery, specifically intraclass correlation coefficient, diagnostic testing analyses, Kaplan-Meier curves, hazard ratios, distribution, and variance.