Study of length of stay in the cardiovascular intensive care unit

Coronary artery bypass graft (CABG) surgery is among the most common operations performed in the United States and accounts for more resources expended in cardiovascular medicine than any other single procedure. CABG surgery patients initially recover in the Cardiovascular Intensive Care Unit (CVICU). The post-procedure CVICU length of stay (LOS) goal is two days or less. A longer ICU LOS is associated with a prolonged hospital LOS, poor health outcomes, greater use of limited resources, and increased medical costs. ^ Research has shown that experienced clinicians can predict LOS no better than chance. Current CABG surgery LOS risk models differ greatly in generalizability and ease of use in the clinical setting. A predictive model that identified modifiable pre- and intra-operative risk factors for CVICU LOS greater than two days could have major public health implications as modification of these identified factors could decrease CVICU LOS and potentially minimize morbidity and mortality, optimize use of limited health care resources, and decrease medical costs. ^ The primary aim of this study was to identify modifiable pre-and intra-operative predictors of CVICU LOS greater than two days for CABG surgery patients with cardiopulmonary bypass (CPB). A secondary aim was to build a probability equation for CVICU LOS greater than two days. Data were extracted from 416 medical records of CABG surgery patients with CPB, 50 to 80 years of age, recovered in the CVICU of a large teaching, referral hospital in southeastern Texas, during the calendar year 2004 and the first quarter of 2005. Exclusion criteria included Diagnosis Related Group (DRG) 106, CABG surgery without CPB, CABG surgery with other procedures, and operative deaths. The data were analyzed using multivariate logistic regression for an alpha=0.05, power=0.80, and correlation=0.26. ^ This study found age, history of peripheral arterial disease, and total operative time equal to and greater than four hours to be independent predictors of CVICU LOS greater than two days. The probability of CVICU LOS greater than two days can be calculated by the following equation: -2.872941 +.0323081 (age in years) + .8177223 (history of peripheral arterial disease) + .70379 (operative time). ^

The Role of Relationships in the Professional Formation of Physicians

BACKGROUND: Studies of the professional development of physicians highlight the important effect that the learning environment, or \"hidden curriculum,\" has in shaping student attitudes, behaviors, and values. We conducted this study to better understand the role that relationships have in mediating these effects of the hidden curriculum. [See PDF for complete abstract]

Sex Trafficking of Minors in the U.S.: Implications for Policy, Prevention and Research

Context: Information currently available on the trafficking of minors in the U.S. for commercial sexual exploitation includes approximations of the numbers involved, risk factors that increase the likelihood of victimization and methods of recruitment and control. However, specific characteristics about this vulnerable population remain largely unknown. Objective: This article has two distinct purposes. The first is to provide the reader with an overview of available information on minor sex trafficking in the U.S. The second is to present findings and discuss policy, research, and educational implications from secondary data analysis of 115 cases of minor sex trafficking in the U.S. Design: Minor sex trafficking cases were identified through two main venues - a review of U.S. Department of Justice press releases of human trafficking cases and an online search of media reports. Searches covered the time period from October 28, 2000, which coincided with the passage of the VTVPA through October 31, 2009. Cases were included in analysis if the incident involved at least one victim under the age of 18, occurred in the U.S., and at least one perpetrator had been arrested, indicted, or convicted. Results: A total of 115 separate incidents involving at least 153 victims were located. These occurrences involved 215 perpetrators, with the majority of them having been convicted (n = 117, 53.4%), The number of victims involved in a single incident ranged from 1 to 9. Over 90% of victims were female who ranged in age from 5 to 17 years. There were more U.S. minor victims than those from other countries. Victims had been in captivity from less than 6 months to 5 years. Minors most commonly fell into exploitation through some type of false promise indicated (16.3%, n = 25), followed by kidnapping (9.8%, n = 15). Over a fifth of the sample (22.2%, n = 34) were abused through two commercial sex practices, with almost all (94.1%, n = 144) used in prostitution. One of every five victims (24.8%, n = 38) had been advertised on an Internet website. Conclusions: Results of a review of known information about minor sex trafficking and findings from analysis of 115 incidents of the sex trafficking of youth in the U.S. indicate a need for stronger legislation to educate various professional groups, more comprehensive services for victims, stricter laws for pimps and traffickers, and preventive educational interventions beginning at a young age.

Factors contributing to the attrition of women in the African-American Nutrition for Life study

Background. There is currently a push to increase the number of minorities in cancer clinical trials in an effort to reduce cancer health disparities. Overcoming barriers to clinical trial research for minorities is necessary if we are to achieve the goals of Healthy People 2010. To understand the unexpectedly high rate of attrition in the A NULIFE study, the research team examined the perceived barriers to participation among minority women. The purpose of this study was to determine if either personal or study-related factors influenced healthy pre-menopausal women aged 25-45 years to terminate their participation in the A NULIFE Study. We hypothesized that personal factors were the driving forces for attrition rates in the prevention trial.^ Methods. The target population consisted of eligible women who consented to the A NULIFE study but withdrew prior to being randomized (N= 46), as well as eligible women who completed the informed consent process for the A NULIFE study and withdrew after randomization (N= 42). Examination of attrition rates in this study occurred at a time point when 10 out of 12 participant groups had completed the A NULIFE study. Data involving the 2 groups that were actively engaged in study activities were not used in this analysis. A survey instrument was designed to query the personal and study-related factors that were believed to have contributed to the decision to terminate participation in the A NULIFE study.^ Results. Overall, the highest ranked personal reason that influenced withdrawal from the study was being “too busy” with other obligations. The second highest ranked factor for withdrawal was work obligations. Whereas, more than half of all participants agreed that they were well-informed about the study and considered the study personnel to be approachable, 54% of participants would have been inclined to remain in the study if it were located at a local community center.^ Conclusions. Time commitment was likely a major factor for withdrawal from the A NULIFE study. Future investigators should implement trials within participant communities where possible. Also, focus group settings may provide detailed insight into factors that contribute to the attrition of minorities in cancer clinical trials.^

Estimates of life expectancy gains from reducing/eliminating major causes of death in the USA: An update analysis for population in 2001--2008

Evaluation of the impact of a disease on life expectancy is an important part of public health. Potential gains in life expectancy (PGLE) that can properly take into account the competing risks are an effective indicator for measuring the impact of the multiple causes of death. This study aimed to measure the PGLEs from reducing/eliminating the major causes of death in the USA from 2001 to 2008. To calculate the PGLEs due to the elimination of specific causes of death, the age-specific mortality rates for heart disease, malignant neoplasms, Alzheimer disease, kidney diseases and HIV/AIDS and life table constructing data were obtained from the National Center for Health Statistics, and the multiple decremental life tables were constructed. The PGLEs by elimination of heart disease, malignant neoplasms or HIV/AIDS continued decreasing from 2001 to 2008, but the PGLE by elimination of Alzheimer's disease or kidney diseases revealed increased trends. The PGLEs (by years) for all race, male, female, white, white male, white female, black, black male and black female at birth by complete elimination of heart disease 2001–2008 were 0.336–0.299, 0.327–0.301, 0.344–0.295, 0.360–0.315, 0.349–0.317, 0.371–0.316,0.278–0.251, 0.272–0.255, and 0.282–0.246 respectively. Similarly, the PGLEs (by years) for all race, male, female, white, white male, white female, black, black male and black female at birth by complete elimination of malignant neoplasms, Alzheimer's disease, kidney disease or HIV/AIDS 2001–2008 were also uncovered, respectively. Most diseases affect specific population, such as, HIV/AIDS tends to have a greater impact on people of working age, heart disease and malignant neoplasms have a greater impact on people over 65 years of age, but Alzheimer's disease and kidney diseases have a greater impact on people over 75 years of age. To measure the impact of these diseases on life expectancy in people of working age, partial multiple decremental life tables were constructed and the PGLEs were computed by partial or complete elimination of various causes of death during the working years. Thus, the results of the study outlined a picture of how each single disease could affect the life expectancy in age-, race-, or sex-specific population in USA. Therefore, the findings would not only assist to evaluate current public health improvements, but also provide useful information for future research and disease control programs.^

Association between length of stay in the U.S. and diabetes risk factors among Chinese Americans in Houston, Texas in 2004-2005

Studies have suggested that acculturation is related to diabetes prevalence and risk factors among immigrant groups in the United States (U.S.), however scant data are available to investigate this relationship among Asian Americans and Asian American subgroups. The objective of this cross-sectional study was to examine the association between length of stay in the U.S. and type 2 diabetes prevalence and its risk factors among Chinese Americans in Houston, Texas. Data were obtained from the 2004-2005 Asian-American Health Needs Assessment in Houston, Texas (N=409 Chinese Americans) for secondary analysis in this study. Diabetes prevalence and risk factors (overweight/obesity and access to medical care) were based on self-report. Descriptive statistics summarized demographic characteristics, diabetes prevalence, and reasons for not seeing a doctor. Logistic regression, using an incremental modeling approach, was used to measure the association between length of stay and diabetes prevalence and related risk factors, while adjusting for the potential confounding factors of age, gender, education level, and income level. Although the prevalence of type 2 diabetes was highest among those living in the U.S. for more than 20 years, there was no significant association between length of stay in the U.S. and diabetes prevalence among these Chinese Americans after adjustment for confounding factors. No association was found between length of stay in the U.S. and overweight/obese status among this population either, after adjusting for confounding factors, too. On the other hand, a longer length of stay was significantly associated with increased health insurance coverage in both unadjusted and adjusted models. The findings of this study suggest that length of stay in the U.S. alone may not be an indicator for diabetes risk among Chinese Americans. Future research should consider alternative models to measure acculturation (e.g., models that reflect acculturation as a multi-dimensional, not uni-dimensional process), which may more accurately depict its effect on diabetes prevalence and related risk factors.^