2 resultados para breath testing

em DigitalCommons@The Texas Medical Center


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Background: Helicobacter pylori infection among Native Americans is more prevalent than any other minority group in the United States. Few studies involving Helicobacter pylori have been conducted on Native Americans and no previous studies have been conducted in the Ysleta del Sur Pueblo population. Therefore we wanted to explore the prevalence and risk factors of Helicobacter pylori within this community. We also explored whether household transmission is occurring. ^ Materials and Methods: We conducted a cross-section study on the prevalence of Helicobacter pylori in the Ysleta del Sur Pueblo community. Main household caregivers were interviewed on household conditions, hygiene practices, and household sociodemographics. All household members were tested for IgG urine antibodies against Helicobacter pylori using RAPIRUN test kits. 13C urea breath testing using BREATHTEK kits was provided to study participants that had positive antibody results and utilized as confirmatory results of infection. ^ Results: Prevalence of Ysleta del Sur Pueblo was determined to be 27.4%. When comparing for ethnicity, Native Americans had increased prevalence of infection then Mexican-Americans living on the Pueblo. That prevalence increased from 1.6 to 3.3 when taking account only United States born study participants. The household secondary prevalence rate was found to be 23.8%. Helicobacter pylori infection rates increased with increasing age and decreasing income. ^ Conclusions: Native Americans had an increased risk of infection. As expected risk factors for Helicobacter pylori correlated with previous studies, but we found evidence of limited current transmission within households. However, due to the limited sample size (n=62) and power, we were not able to find statistical significance for some risk factors. A statistical association was found with age where increasing prevalence corresponded with increasing age suggesting that the birth cohort may be in effect within this population.^

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Tuberculosis (TB) is an infectious disease of great public health importance, particularly to institutions that provide health care to large numbers of TB patients such as Parkland Hospital in Dallas, TX. The purpose of this retrospective chart review was to analyze differences in TB positive and TB negative patients to better understand whether or not there were variables that could be utilized to develop a predictive model for use in the emergency department to reduce the overall number of suspected TB patients being sent to respiratory isolation for TB testing. This study included patients who presented to the Parkland Hospital emergency department between November 2006 and December 2007 and were isolated and tested for TB. Outcome of TB was defined as a positive sputum AFB test or a positive M. tuberculosis culture result. Data were collected utilizing the UT Southwestern Medical Center computerized database OACIS and included demographic information, TB risk factors, physical symptoms, and clinical results. Only two variables were significantly (P<0.05) related to TB outcome: dyspnea (shortness of breath) (P<0.001) and abnormal x-ray (P<0.001). Marginally significant variables included hemoptysis (P=0.06), weight loss (P=0.11), night sweats (P=0.20), history of homelessness or incarceration (P=0.15), and history of positive skin PPD (P=0.19). Using a combination of significant and marginally significant variables, a predictive model was designed which demonstrated a specificity of 24% and a sensitivity of 70%. In conclusion, a predictive model for TB outcome based on patients who presented to the Parkland Hospital emergency department between November 2006 and December 2007 was unsuccessful given the limited number of variables that differed significantly between TB positive and TB negative patients. It is suggested that a future prospective cohort study should be implemented to collect data on TB positive and TB negative patients. It may be possible that a more thorough prospective collection of data may lead to clearer comparisons between TB positive and TB negative patients and ultimately to the design of a more sensitive predictive model for TB outcome. ^