Complementary and alternative medicines versus prescription drugs: perceptions of emergency department patients.

BACKGROUND: The perceptions of emergency department (ED) patients towards complementary and alternative medicines (CAM) are poorly understood. We assessed these perceptions and compared CAM users with non-users, particularly regarding CAM safety and efficacy. METHODS: This was an analytical, cross sectional survey of ED patients undertaken in a tertiary referral ED. A five point Likert scale evaluated patients' level of agreement with statements relating to CAM and prescription drugs. RESULTS: Of 404 patients who were enrolled (participation rate 97.1%), 275 (68.1%; 95% confidence interval (CI) 63.2 to 72.5) were CAM users (had taken a CAM within the previous 12 months). There were 178 patients (44.1%, 95% CI 39.2 to 49.1) who agreed or strongly agreed that CAM are drug free, and there was no significant difference between CAM users and non-users (p = 0.77). There were 115 patients (28.5%, 95% CI 24.2 to 33.2) who agreed or strongly agreed that CAM are always safe to take with prescription drugs, and there were no significant difference between CAM users and non-users (p = 0.39). Significantly more CAM users agreed or strongly agreed that CAM are safe to take, can prevent people from becoming ill, allow people to be in charge of their own health, can treat the mind, body, and spirit, and are more effective than prescription drugs (p<0.01). Significantly fewer CAM users agreed or strongly agreed that prescription drugs are safe to take (p<0.001). CONCLUSION: Considerable proportions of ED patients are CAM users yet are ignorant of the nature and potential toxicities of CAM. In addition, CAM users have significantly different perceptions of CAM and prescription drugs from non-users. The impact of these perceptions on clinical practice needs evaluation.

Novel potential ALL low-risk markers revealed by gene expression profiling with new high-throughput SSH-CCS-PCR.

The current systems of risk grouping in pediatric acute lymphoblastic leukemia (ALL) fail to predict therapeutic success in 10-35% of patients. To identify better predictive markers of clinical behavior in ALL, we have developed an integrated approach for gene expression profiling that couples suppression subtractive hybridization, concatenated cDNA sequencing, and reverse transcriptase real-time quantitative PCR. Using this approach, a total of 600 differentially expressed genes were identified between t(4;11) ALL and pre-B ALL with no determinant chromosomal translocation. The expression of 67 genes was analyzed in different cytogenetic ALL subgroups and B lymphocytes isolated from healthy donors. Three genes, BACH1, TP53BPL, and H2B/S, were consistently expressed as a significant cluster associated with the low-risk ALL subgroups. A total of 42 genes were differentially expressed in ALL vs normal B lymphocytes, with no specific association with any particular ALL subgroups. The remaining 22 genes were part of a specific expression profile associated with the hyperdiploid, t(12;21), or t(4;11) subgroups. Using an unsupervised hierarchical cluster analysis, the discriminating power of these specific expression profiles allowed the clustering of patients according to their subgroups. These genes could help to understand the difference in treatment response and become therapeutical targets to improve ALL clinical outcomes.