Quispe, Renato

Introduction: Big data techniques offer a novel opportunity to characterize individuals with extreme phenotypes. In this context, we aimed to describe the prevalence of classical Fredrickson-Levy dyslipidemia phenotypes at the extremes of HDL-C levels in a cross-sectional big data study. Methods: We examined 848,801 U.S. adults and children from the Very Large Database of Lipids 1.0 who were referred for lipoprotein testing from 2009 to 2011. We categorized patients into HDL-C percentile categories (<0.1th, 0.1th to 99th to 99.9th, and >99.9th). We examined the prevalence of Fredrickson-Levy dyslipidemia phenotypes (I, IIa, IIb, III, IV and V) within these categories. We identified those who did not meet criteria for any classical dyslipidemia phenotype as the continuum group. Results: Type I and V were mostly present at extremely low HDL-C levels. Type IIa was more prevalent in high vs. low HDL-C levels. Type III was 2-fold more prevalent in extremely low vs. high HDL-C levels. Type IV was the most prevalent classical dyslipidemia phenotype in our population, and was the most frequent at low HDL-C percentiles. About 50% of the extremely low and 90% of the extremely high HDL-C levels were classified into the continuum group. Conclusion: In our cross-sectional big data analysis, there was a significantly higher prevalence of most classical dyslipidemia phenotypes at extremely low HDL-C compared with extremely high HDL-C levels. Only types I and V were more prevalent in extreme groups than general population. To some extent, very low HDL-C levels may be determined by inheritable, highly atherogenic dyslipidemias.

Purpose. To explore perceptions and experiences of Peruvian medical students about observed, preferred, and feasible decision-making approaches. Methods. We surveyed senior medical students from 19 teaching hospitals in 4 major cities in Peru. The self-administered questionnaire collected demographic information, current approach, exposure to role models for and training in shared decision making, and perceptions of the pertinence and feasibility of the different decision-making approaches in general as well as in challenging scenarios. Results. A total of 327 senior medical students (51% female) were included. The mean age was 25 years. Among all respondents, 2% reported receiving both theoretical and practical training in shared decision making. While 46% of students identified their current decision-making approach as clinician-as-perfect-agent, 50% of students identified their teachers with the paternalistic approach. Remarkably, 53% of students thought shared decision making should be the preferred approach and 50% considered it feasible in Peru. Among the 10 challenging scenarios, shared decision making reached a plurality (40%) in only one scenario (terminally ill patients). Conclusion. Despite limited exposure and training, Peruvian medical students aspire to practice shared decision making but their current attitude reflects the less participatory approaches they see role modeled by their teachers.