Medical Student Research Fellowship for Summer 2010
Mentor: Dr. Edward Livingston
Human subjects IRB approved project number (where applicable): N/A
Animal subjects IRB approved project number (where applicable): N/A
Project Type (patient-based research, animal-based research, or basic research; this characterization is only to permit a general classification for grouping similar types of projects)
This project is likely best categorized as exploring research methods; it involves analysis and review of previously published patient-based research.
Brief Description of Project:
The application of statistical analysis to medical research findings has allowed
for many important advances in modern medicine. Statistics offer a formalized
way to minimize the risk of promoting practices based solely upon empirical
evidence. For example, society benefited from the rejection of empirical practices
such as bloodletting that formal statistical analysis proved ineffective in
the early 20th century, and great strides were made in health care when formal
clinical trials showed the benefits of surgical antisepsis and widespread vaccinations.
Thus, it is important for physicians to have an understanding of statistics
as a way to assess to what degree new research findings are valid. Unfortunately
statistics are only covered in a very cursory fashion in most US medical school
curricula. As a result, many clinicians confuse statistical significance (p<=0.05)
with clinical relevance. When evaluating experimental data, establishing statistical
significance only represents a starting point for determining if the observations
are important. In order to know if observations are important once a statistical
test has demonstrated p<=0.05, subsequent evaluations are required to know
the magnitude of the difference between groups. We hypothesize that studies
demonstrating large differences between groups as measured by effect size determination
will have more lasting findings as measured by a published studies impact.
Effect sizes measure the magnitude of differences between groups and help to determine if statistically significant differences represent practically significant ones. Standardized effect size indices are unitless numbers that have a constant range of values across experiments and allow investigators to compare the magnitude of differences between experimental groups. They provide a measure of the magnitude of an effect independent of experimental units or scale, so as to facilitate the comparison of treatment effects across studies. As proposed by Cohen 1, effects are classified as small, medium and large to provide context to experimental conditions. Several professional groups and journals encourage investigators to report effect size as a necessary component of statistical results. Cohen's effect size classification was arbitrarily developed. Our study will establish the relationship between effect size and the actual importance of scientific findings. We will establish this relationship by calculating effect size for all studies published in JAMA and the NEJM in 1980 and correlate them with the number of citations each paper had. We have chosen 1980 as the study year because sufficient time as passed enabling us to establish the long term significance of these papers. The number of citations since their publication will serve as a surrogate marker for a published papers overall impact.
Previous Research Activities or Publications with Medical Students:
Dr. Livingston has worked extensively with students at UTSW, UCLA and UT Arlington. In each instance, the projects resulted in publications, the only exceptions being when students did not follow up on the work. Publications resulting from projects that involved students include:
1. Roessler, J., Srivatsan, E., Peters, J., and Livingston, E.: Tumor Suppressor
Activity of Neural Cell Adhesion Molecule in Colon Carcinoma. American Journal
of Surgery 174:251-257, 1997.
2. Roesler, J.M., Livingston, E., Chang, P., Wang, M. Deletion of P15 (MTS2) in Head and Neck Squamous Cell Carcinomas. Journal of Surgical Research 77:50-54, 1998.
3. Livingston, EH; Lee, S. Percentage of burned body surface area determination in obese and nonobese patients. Journal of Surgical Research. 91:106-110, 2000.
4. Huerta, S., Srivatsan, E.S., Venkatesan, N., Peters, J., Moatamed, F., Renner, S., Livingston, E.H. Alternative mRNA splicing in colon cancer causes loss of neural cell adhesion molecule (NCAM) expression. Surgery 130:834-843,2001.
5. Huerta, S., Srivatsan, E.S., Venkatasan N., Livingston, E.H. Human colon cancer cells deficient in DCC produce abnormal transcripts in the progression of carcinogenesis. Digestive Diseases and Sciences 46:1884-1891, 2001.
6. Huerta, S., Heber, D., Sawicki, M.P., Liu, C.D., Arthur, D., Alexander, P., Yip, I., Li, Z., Livingston, E.H. Reduced Length of Stay by Implementation of a Clinical Pathway for Bariatric Surgery in an Academic Health Care Center. American Surgeon 67:1128-1135, 2001
7. Huerta, S., Rogers, L.M., Li, Z., Heber,D., Liu, C., Livingston, E,H,. Vitamin A deficiency in a newborn due to maternal vitamin A deficiency after biliopancreatic diversion for the treatment of morbid obesity: a case report. American Journal of Clinical Nutrition.76:426-429, 2002.
8. Huerta S, DeShields S, Shpiner R, Li Z, Liu C, Sawicki M, Arteaga J, Livingston
EH. Safety and efficacy of postoperative continuous positive airway pressure
to prevent pulmonary complications after Roux-en-Y gastric bypass. The Journal
of Gastrointestinal Surgery , 6:354-358, 2002.
9. Livingston, E.H., Huerta, S., Arthur, D., Lee, S., DeShields, S., Heber, D. Male gender is a predictor of morbidity and age a predictor of mortality for patients undergoing gastric bypass surgery. Annals of Surgery 236:576-582, 2002.
10. Melinek, J., Livingston, E., Cortina, G.R., Fishbein, M.C. Death following
gastric bypass surgery for morbid obesity. The Archives of Pathology & Laboratory
11. Arteaga, J.R., Huerta, S., Livingston, E.H. Management of gastrojejunal anastomotic leaks after Roux-en-Y gastric bypass. American Surgeon 68:1061-1065, 2002.
12. Huerta S, Arteaga J, Li Z, Livingston EH. Acinar cell carcinoma of the
pancreas in a morbidly obese patient. Pancreas. 25:414-5, 2002. (Highlighted
as the Case Report of the Month by NAASO News, May, 2003).
13. Huerta S, DeShields S, Sawicki M, Liu C, Arteaga J, Livingston EH. Assessment of Routine Elimination of Postoperative Nasogastric Decompression Following Roux-en-Y Gastric Bypass. Surgery 132:844-848, 2002.
14. Miller JAG, Rege RV, Ko, CY, Livingston EH. Health care access and poverty do not explain the higher cancer mortality in blacks. American Journal of Surgery 188:22-26, 2004.
15. Livingston, E.H. Langert, J. The impact of age and Medicare status on bariatric surgery outcomes. Archives of Surgery. 141:1115-1120, 2006.
16. Zuzak, K.J., Naik, S., Alexandrakis, G., Hawkins, D., Behbehani, K., Livingston, E.H. Characterization of a near-infrared laparoscopic hyperspectral imaging system for minimally invasive surgery. Analytical Chemistry. 79:4709-4715, 2007.
17. Zuzak, K.J., Naik, S., Alexandrakis, G., Hawkins, D., Behbehani, K., Livingston, E.H. Intraoperative Bile Duct Visualization Using Near-Infrared Hyperspectral Video Imaging. The American Journal of Surgery. 195(4): 491-7, 2008.
18. Livingston, E.H., Miller, J.A.G., Coan, B., Rege, R.V. Costs and utilization of intraoperative cholangiography. Journal of Gastrointestinal Surgery. 11:1162-1167, 2007.
19. Zuzak KJ, Naik SC, Alexandrakis G, Hawkins D, Behbehani K, Livingston E. Intraoperative bile duct visualization using near-infrared hyperspectral video imaging. Am J Surg. 2008 Apr;195:491-7.
20. Alexandrakis, G, Nadkar, D, Patel, N, Liu, H, Livingston, E, Localization of adipose tissue embedded biliary tree vessels by use of near-infrared diffuse photon propagation models: a computational feasibility study. Applied Optics 47: No. 32, 2008
21. Livingston EH, Gulaka P, Kommera S, Wang B, Liu H. In vivo spectroscopic characterization of porcine biliary tract tissues: first step in the development of new biliary tract imaging devices. Annals of Biomedical Engineering. 2009 Jan;37(1):201-9.
(1) Cohen J. Statistical Power Analysis for the Behavioral Sciences. New York: Lawrence Erlbaum Associates, 1998.