Interview with Dorothy Otto

Interview with Dorothy Otto, Associate Professor at the School of Nursing, University of Texas Houston Health Science Center.

Design and implementation of a multicriteria medical decision support system for diagnosis and treatment

Health care providers face the problem of trying to make decisions with inadequate information and also with an overload of (often contradictory) information. Physicians often choose treatment long before they know which disease is present. Indeed, uncertainty is intrinsic to the practice of medicine. Decision analysis can help physicians structure and work through a medical decision problem, and can provide reassurance that decisions are rational and consistent with the beliefs and preferences of other physicians and patients. ^ The primary purpose of this research project is to develop the theory, methods, techniques and tools necessary for designing and implementing a system to support solving medical decision problems. A case study involving “abdominal pain” serves as a prototype for implementing the system. The research, however, focuses on a generic class of problems and aims at covering theoretical as well as practical aspects of the system developed. ^ The main contributions of this research are: (1) bridging the gap between the statistical approach and the knowledge-based (expert) approach to medical decision making; (2) linking a collection of methods, techniques and tools together to allow for the design of a medical decision support system, based on a framework that involves the Analytic Network Process (ANP), the generalization of the Analytic Hierarchy Process (AHP) to dependence and feedback, for problems involving diagnosis and treatment; (3) enhancing the representation and manipulation of uncertainty in the ANP framework by incorporating group consensus weights; and (4) developing a computer program to assist in the implementation of the system. ^

The relationship between calcium and fluoride intake, pregnancy and lactation and the risk of height loss in white women

This study was designed to investigate the effect of calcium and fluoride intake, and parity and lactation on the risk of spinal osteoporosis. Height loss was used as a surrogate measure for spinal fractures by taking advantage of documented changes in height found during the 25-year follow-up of the Charleston Heart Study cohort. Women who had lost 2-4" in height or who had no change in height during the follow-up period were defined as case and comparison subjects respectively. Calcium intake when the subjects were "about 25" and in the recent past, average intake of fluoride over 25 years, and parity and history of breastfeeding were ascertained by questionnaire from 54 case and 77 comparison subjects. Low calcium intake in the past decreased the risk of height loss (age-adjusted OR = 0.3, 95%CI: 0.1-0.96) although several potentially important confounding variables could not be adjusted for. There was no association between risk of height loss and present calcium intake (OR = 0.8, 95%CI: 0.3-2.6 for low versus high intake) after adjustment for past calcium intake. High fluoride intake decreased the risk of height loss (adjusted OR = 0.4, 95%CI: 0.1-1.2). The effect of fluoride or calcium intake in the present was modified by the level of the other nutrient. Compared to a low intake of both calcium and fluoride, a high intake of one increased the risk of height loss (crude OR = 3.3 for high fluoride/low calcium, crude OR = 6.0 for high calcium/low fluoride) although a high intake of both was slightly protective (crude OR = 0.7). It is estimated that a "high" nutrient intake in this population was greater than 850mg/day for calcium and 2mg/day for fluoride. After adjustment for age, increasing parity decreased the risk of height loss in women who had never breastfed (OR = 0.2, 95%CI: 0.01-1.7 for 4 or more children). Women who had breastfed were also at lower risk of height loss than nulliparous women (OR = 0.3, 95%CI: 0.1-1.2 for 4 or more children) although at any level of parity, breastfeeding women had a greater risk of height loss than did non-breastfeeding women. ^

A STUDY OF INFLUENZA AND OF STATISTICAL METHODS USED TO REPORT INFLUENZA

This paper defines and compares several models for describing excess influenza pneumonia mortality in Houston. First, the methodology used by the Center for Disease Control is examined and several variations of this methodology are studied. All of the models examined emphasize the difficulty of omitting epidemic weeks.^ In an attempt to find a better method of describing expected and epidemic mortality, time series methods are examined. Grouping in four-week periods, truncating the data series to adjust epidemic periods, and seasonally-adjusting the series y(,t), by:^ (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI)^ is the best method examined. This new series w(,t) is stationary and a moving average model MA(1) gives a good fit for forecasting influenza and pneumonia mortality in Houston.^ Influenza morbidity, other causes of death, sex, race, age, climate variables, environmental factors, and school absenteeism are all examined in terms of their relationship to influenza and pneumonia mortality. Both influenza morbidity and ischemic heart disease mortality show a very high relationship that remains when seasonal trends are removed from the data. However, when jointly modeling the three series it is obvious that the simple time series MA(1) model of truncated, seasonally-adjusted four-week data gives a better forecast.^

Risk factors for metabolic syndrome among overweight and obese Hispanic children attending a pediatric clinic in New Braunfels, Texas

Childhood obesity is a persistent problem in the U.S., especially among Hispanics. Health complications like hypertension, type II diabetes, and metabolic syndrome (Met-S) are being seen at younger ages, and current screening procedures may be inadequate. This study sought to describe the risk factors for Met-S present in a sample of 106 overweight and obese Hispanic children, aged 5-14 years, participating in Nutrition and Exercise Start Today (NEST), a randomized weight management intervention trial at a rural health clinic in New Braunfels, Texas; and to determine associations between these factors and other clinical and socio-demographic characteristics linked to obesity. Baseline data was analyzed for the prevalence of large waist circumference (WC), elevated blood pressure (BP), high fasting serum glucose and serum triglycerides (TG), and low serum HDL cholesterol, in relationship with selected sample characteristics. Main findings included high baseline prevalence rates of large WC (77%), reduced HDL (57%), and elevated BP (30%). WC was significantly associated with BMI percentile and the serum liver function test alanine aminotransferase (ALT) by Fisher's exact test (p<0.001 and p=0.032, respectively), while there were significant relationships between HDL and both female gender and ALT. BMI percentile and ALT were associated with all sets of Met-S diagnostic criteria examined. BMI percentile also had a strong association (p=0.005) with total number of Met-S risk factors, while ALT had a weaker association (p=0.093). WC is a low-cost, simple measure whose use may improve clinic surveillance for childhood obesity and complications like Met-S. WC, BP, HDL and ALT may be used as part of targeted screening for obesity complications like Met-S, particularly in situations where resources are limited.^