A randomized trial comparing didactics, demonstration, and simulation for teaching teamwork to medical residents.

RATIONALE: Effective teamwork is fundamental to the management of medical emergencies, and yet the best method to teach teamwork skills to trainees remains unknown. OBJECTIVES: In a cohort of incoming internal medicine interns, we tested the hypothesis that expert demonstration of teamwork principles and participation in high-fidelity simulation would each result in objectively assessed teamwork behavior superior to traditional didactics. METHODS: This was a randomized, controlled, parallel-group trial comparing three teamwork teaching modalities for incoming internal medicine interns. Participants in a single-day orientation at the Vanderbilt University Center for Experiential Learning and Assessment were randomized 1:1:1 to didactic, demonstration-based, or simulation-based instruction and then evaluated in their management of a simulated crisis by five independent, blinded observers using the Teamwork Behavioral Rater score. Clinical performance was assessed using the American Heart Association Advanced Cardiac Life Support algorithm and a novel "Recognize, Respond, Reassess" score. MEASUREMENTS AND MAIN RESULTS: Participants randomized to didactics (n = 18), demonstration (n = 17), and simulation (n = 17) were similar at baseline. The primary outcome of average overall Teamwork Behavioral Rater score for those who received demonstration-based training was similar to simulation participation (4.40 ± 1.15 vs. 4.10 ± 0.95, P = 0.917) and significantly higher than didactic instruction (4.40 ± 1.15 vs. 3.10 ± 0.51, P = 0.045). Clinical performance scores were similar between the three groups and correlated only weakly with teamwork behavior (coefficient of determination [Rs(2)] = 0.267, P < 0.001). CONCLUSIONS: Among incoming internal medicine interns, teamwork training by expert demonstration resulted in similar teamwork behavior to participation in high-fidelity simulation and was more effective than traditional didactics. Clinical performance was largely independent of teamwork behavior and did not differ between training modalities.

Lung cancer diagnosis from proteomic analysis of preinvasive lesions.

Early detection may help improve survival from lung cancer. In this study, our goal was to derive and validate a signature from the proteomic analysis of bronchial lesions that could predict the diagnosis of lung cancer. Using previously published studies of bronchial tissues, we selected a signature of nine matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) mass-to-charge ratio features to build a prediction model diagnostic of lung cancer. The model was based on MALDI MS signal intensity (MALDI score) from bronchial tissue specimens from our 2005 published cohort of 51 patients. The performance of the prediction model in identifying lung cancer was tested in an independent cohort of bronchial specimens from 60 patients. The probability of having lung cancer based on the proteomic analysis of the bronchial specimens was characterized by an area under the receiver operating characteristic curve of 0.77 (95% CI 0.66-0.88) in this validation cohort. Eight of the nine features were identified and validated by Western blotting and immunohistochemistry. These results show that proteomic analysis of endobronchial lesions may facilitate the diagnosis of lung cancer and the monitoring of high-risk individuals for lung cancer in surveillance and chemoprevention trials.