RT Book, Section A1 Zampieri, Fernando G. A1 Harhay, Michael O. A1 Casey, Jonathan D. A2 Schmidt, Gregory A. A2 Kress, John P. A2 Douglas, Ivor S. SR Print(0) ID 1201798390 T1 Interpreting and Applying Evidence in Critically Ill Patients T2 Hall, Schmidt and Wood’s Principles of Critical Care, 5th Edition YR 2023 FD 2023 PB McGraw Hill PP New York, NY SN 9781264264353 LK accessanesthesiology.mhmedical.com/content.aspx?aid=1201798390 RD 2024/09/11 AB Interpreting evidence requires a basic understanding of how evidence is generated.There is not one ideal research design. Diverse research methods are needed to answer a broad range of questions confronting clinicians. However, an understanding of the potential weaknesses of each method is needed for clinicians to determine if the results are strong enough to change practice.Observational studies are efficient and can provide data when randomized trials are unavailable or infeasible, but determining causality and estimating treatment effects (causal inference) require complicated methods to identify and account for biases that may, in some cases, be insurmountable.Randomized trials are protected against many of the biases of observational research, but they are expensive and time-consuming and may provide uninformative results if underpowered (insufficiently large), poorly designed, or inappropriately analyzed. Assessing and applying clinical trial results require an understanding of the methods used to design and conduct clinical trials.Novel trial designs are improving trial efficiency (ie, fewer patients and faster results), and novel methods of analysis are improving the robustness of their interpretation (ie, moving away from interpretations of statistical significance as “positive or negative,” to probabilistic assessments of trial results and more robust subgroup assessments), but these changes are accompanied by an increase in complexity that may be challenging for many clinicians to understand.