Three-Dimensional-Printed Liver Model Helps Learners Identify Hepatic Subsegments: A Randomized-Controlled Cross-Over Trial.

INTRODUCTION: The purpose of this study was to find out whether 3-dimensional (3D)-printed models improved the learners' ability to identify liver segments. METHODS: A total of 116 physicians from 3 disciplines were tested in a cross-over trial at baseline and after teaching with 3D models and 2-dimensional (2D) images. Adjusted multilevel-mixed models were used to compare scores at baseline and after 3D and 2D. RESULTS: Accuracy in identifying hepatic segments was higher with 3D first than 2D (77% vs 69%; P = 0.05) and not significantly improved by a combination of 3D and 2D. Increased confidence in segment identification was highest in trainees after 3D (P = 0.04). DISCUSSION: 3D-printed models facilitate learning hepatic segmental anatomy.

Impact of direct-to-consumer predictive genomic testing on risk perception and worry among patients receiving routine care in a preventive health clinic.

OBJECTIVE: To assess the impact of direct-to-consumer (DTC) predictive genomic risk information on perceived risk and worry in the context of routine clinical care. PATIENTS AND METHODS: Patients attending a preventive medicine clinic between June 1 and December 18, 2009, were randomly assigned to receive either genomic risk information from a DTC product plus usual care (n=74) or usual care alone (n=76). At intervals of 1 week and 1 year after their clinic visit, participants completed surveys containing validated measures of risk perception and levels of worry associated with the 12 conditions assessed by the DTC product. RESULTS: Of 345 patients approached, 150 (43%) agreed to participate, 64 (19%) refused, and 131 (38%) did not respond. Compared with those receiving usual care, participants who received genomic risk information initially rated their risk as higher for 4 conditions (abdominal aneurysm [P=.001], Graves disease [P=.04], obesity [P=.01], and osteoarthritis [P=.04]) and lower for one (prostate cancer [P=.02]). Although differences were not significant, they also reported higher levels of worry for 7 conditions and lower levels for 5 others. At 1 year, there were no significant differences between groups. CONCLUSION: Predictive genomic risk information modestly influences risk perception and worry. The extent and direction of this influence may depend on the condition being tested and its baseline prominence in preventive health care and may attenuate with time.