2 resultados para IDI
em DigitalCommons@The Texas Medical Center
Resumo:
Objective. The objective of this study is to determine the prevalence of MRSA colonization in adult patients admitted to intensive care units at an urban tertiary care hospital in Houston, Texas and to evaluate the risk factors associated with colonization during a three month active-screening pilot project. Design. This study used secondary data from a small cross-sectional pilot project. Methods. All patients admitted to the seven specialty ICUs were screened for MRSA by nasal culture. Results were obtained utilizing the BD GeneOhm™ IDI-MRSA assay in vitro diagnostic test, for rapid MRSA detection. Statistical analysis was performed using the STATA 10, Epi Info, and JavaStat. Results . 1283/1531 (83.4%) adult ICU admissions were screened for nasal MRSA colonization. Of those screened, demographic and risk factor data was available for 1260/1283 (98.2%). Unresolved results were obtained for 73 patients. Therefore, a total of 1187/1531 (77.5%) of all ICU admissions during the three month study period are described in this analysis. Risk factors associated with colonization included the following: hospitalization within the last six months (odds ratio 2.48 [95% CI, 1.70-3.63], p=0.000), hospitalization within the last 12 months, (odds ratio 2.27 [95% CI, 1.57-3.80], p=0.000), and having diabetes mellitus (odds ratio 1.63 [95% CI, 1.14-2.32], p=0.007). Conclusion. Based on the literature, the prevalence of MRSA for this population is typical of other prevalence studies conducted in the United States and coincides with the continual increasing trend of MRSA colonization. Significant risk factors were similar to those found in previous studies. Overall, the active surveillance screening pilot project has provided valuable information on a population not widely addressed. These findings can aid in future interventions for the education, control, prevention, and treatment of MRSA. ^
Resumo:
Although the area under the receiver operating characteristic (AUC) is the most popular measure of the performance of prediction models, it has limitations, especially when it is used to evaluate the added discrimination of a new biomarker in the model. Pencina et al. (2008) proposed two indices, the net reclassification improvement (NRI) and integrated discrimination improvement (IDI), to supplement the improvement in the AUC (IAUC). Their NRI and IDI are based on binary outcomes in case-control settings, which do not involve time-to-event outcome. However, many disease outcomes are time-dependent and the onset time can be censored. Measuring discrimination potential of a prognostic marker without considering time to event can lead to biased estimates. In this dissertation, we have extended the NRI and IDI to survival analysis settings and derived the corresponding sample estimators and asymptotic tests. Simulation studies were conducted to compare the performance of the time-dependent NRI and IDI with Pencina’s NRI and IDI. For illustration, we have applied the proposed method to a breast cancer study.^ Key words: Prognostic model, Discrimination, Time-dependent NRI and IDI ^