Clinical prediction rules in trauma imaging: who, how, and why?
Clinical prediction rules are multifactorial tools used to aid in clinical decision making. In radiology, clinical prediction rules are an important method for determining who should undergo imaging and, in combination with cost-effectiveness analysis, how imaging should be performed. To be useful, clinical prediction rules should be clinically important, have face validity, be reproducible and easy to use, be clinically relevant, and suggest a course of action. To insure generalizability, clinical prediction rules should also be validated in subjects distinct from those used to develop the rule. In this review, several examples from trauma imaging are used to demonstrate the development, validation, and use of clinical prediction rules.
Blackmore
C Craig
CC
Department of Radiology and Harborview Injury Prevention and Research Center, Harborview Medical Center, University of Washington, Box 359728, 325 Ninth Ave, Seattle, WA 98104, USA. craige@u.washington.edu
D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D004630:Emergencies / Q000191:economics*; D019317:Evidence-Based Medicine / Q000191:economics; D006801:Humans; D011859:Radiography / Q000191:economics*; D014057:Tomography, X-Ray Computed / Q000191:economics*; D014481:United States; D014947:Wounds and Injuries / Q000145:classification / Q000000981:diagnostic imaging* / Q000191:economics