Understanding the literature: Complexity of statistical methods used in high-impact cardiothoracic surgery research

Biostatistics are frequently used in research published in the domain of cardiothoracic surgery. The objective of this study was to describe the scope of statistical techniques reported in the literature and to highlight implications for editorial review and critical appraisal. Original research articles published between January and April 2017 in the Journal of Thoracic and Cardiovascular Surgery, Annals of Thoracic Surgery, and the European Journal of Cardio-Thoracic Surgery were examined. For each article, the statistical method(s) reported were recorded and categorized by complexity. We reviewed 293 articles that reported 1068 statistical methods. The mean number of different statistical methods reported per article was 3.6 ± 1.9, with variation by subspecialty and journal. The most common statistical methods were contingency tables (in 59% of articles), t tests (49%), and survival methods (49%). Only 4% of articles used descriptive statistics alone. An introductory level of statistical knowledge was deemed sufficient for understanding 16% of articles, whereas for the remainder a higher level of knowledge would be needed. Contemporary cardiothoracic surgery research frequently requires the use of complex statistical methods. This was evident across articles for all cardiothoracic surgical subspecialties as reported in 3 high-impact journals. Routine review of manuscript submissions by biostatisticians is needed to ensure the appropriate use and reporting of advanced statistical methods in cardiothoracic surgery research. Cardiothoracic surgery research often requires complex statistical methods. In this study, 293 articles were screened for statistical complexity, in which 1068 statistical methods were found. In this study, 82% of the manuscripts required more than introductory statistical knowledge to be understood. The implication of the study is that cardiothoracic surgery literature, in this era, regularly uses advanced statistical methods. [Display omitted]