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Objective: The primary aim was to compare the "clinical value" of tranexamic acid (TXA) with ε-aminocaproic acid (EACA) when used for blood conservation during high-risk cardiac surgery., Design: Data previously reported by the Blood Conservation Using Antifibrinolytics in a Randomized Trial (BART) study investigators were reanalyzed independently after appropriate statistical adjustment. The authors compared TXA with EACA for important primary and secondary outcomes and applied the "clinical value" equation to this comparison., Setting: BART, the largest blinded multicenter study on this topic to date, compared all 3 commonly used antifibrinolytics head-to-head in a randomized dose-equivalent fashion during high-risk cardiac surgery. Comparisons of TXA with EACA with application of the clinical value equation was not performed specifically by the BART investigators., Participants: One thousand five hundred fifty patients enrolled in 2 of the 3 arms of the BART study were included in the analysis (TXA, n= 770 and EACA, n = 780, with data reported by the investigators in the New England Journal of Medicine)., Main Results: The major finding was that there were no significant differences in overall safety and clinically important efficacy between TXA and EACA., Conclusions: Considering the substantial difference in costs and with the increasing volume of high-risk cardiac surgery, EACA has increased "clinical value" when compared with TXA. EACA should be the antifibrinolytic medication of choice for high-risk cardiac surgery., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Objective: The objective of the study was to characterize the variations in normal cervical spectra because of menopausal status and location within the menstrual cycle. Using the information obtained, the accuracy of Raman spectroscopy to diagnose low-grade squamous intraepithelial lesion (LGSIL) will be improved., Study Design: A total of 133 patients undergoing either colposcopy or Papanicolaou smear were recruited from either Vanderbilt University or Tri-State Women's Health. Raman spectra were collected from both normal and diseased areas. The data were processed and analyzed using a multiclass discrimination and classification algorithm to determine whether the spectra were correctly classified., Results: Stratifying the data by menopausal state resulted in correctly classifying LGSIL 97% of the time (from 74%)., Conclusion: This study brings Raman spectroscopy one step closer to clinical use by improving the sensitivity to differentiate LGSIL from normal.

Raman spectroscopy has the potential to differentiate among the various stages leading to high-grade cervical cancer such as normal, squamous metaplasia, and low-grade cancer. For Raman spectroscopy to successfully differentiate among the stages, an applicable statistical method must be developed. Algorithms like linear discriminant analysis (LDA) are incapable of differentiating among three or more types of tissues. We developed a novel statistical method combining the method of maximum representation and discrimination feature (MRDF) to extract diagnostic information with sparse multinomial logistic regression (SMLR) to classify spectra based on nonlinear features for multiclass analysis of Raman spectra. We found that high-grade spectra classified correctly 95% of the time; low-grade data classified correctly 74% of the time, improving sensitivity from 92 to 98% and specificity from 81 to 96% suggesting that MRDF with SMLR is a more appropriate technique for categorizing Raman spectra. SMLR also outputs a posterior probability to evaluate the algorithm's accuracy. This combined method holds promise to diagnose subtle changes leading to cervical cancer.