Retrospective analysis of Methicillin-Resistant Staphylococcus Aureus (MRSA) skin and Soft-Tissue Infections (SSTI) in a university hospital emergency department (ED)

Study Objective: Identify the most frequent risk factors of Community Acquired-MRSA (CA-MRSA) Skin and Soft-tissue Infections (SSTIs) using a case series of patients and characterize them by age, race/ethnicity, gender, abscess location, druguse and intravenous drug-user (IVDU), underlying medical conditions, homelessness, treatment resistance, sepsis, those whose last healthcare visit was within the last 12 months, and describe the susceptibility pattern from this central Texas population that have come into the University Medical Center Brackenridge (UMCB) Emergency Department (ED). ^ Methods: This study was a retrospective case-series medical record review involving a convenience sample of patients in 2007 from an urban public hospital's ED in Texas that had a SSTI that tested positive for MRSA. All positive MRSA cultures underwent susceptibility testing to determine antibiotic resistance. The demographic and clinical variables that were independently associated with MRSA were determined by univariate and multivariate analysis using logistic regression to calculate odds ratios (OR), 95% confidence intervals, and significance (p≤ 0.05). ^ Results: In 2007, there were 857 positive MRSA cultures. The demographics were: males 60% and females 40%, with the average age of 36.2 (std. dev. =13) the study population consisted of non-Hispanic white (42%), Hispanics (38%), and non-Hispanic black (18.8%). Possible risk factors addressed included using recreational drugs (not including IVDU) (27%) homelessness (13%), diabetes status (12.6%) or having an infectious disease, and IVDU (10%). The most frequent abscess location was the leg (26.6%), followed by the arm and torso (both 13.7%). Eighty-three percent of patients had one prominent susceptibility pattern that had a susceptibility rate for the following antibiotics: trimethoprim/sulfamethoxazole (TMP-SMX) and vancomycin had 100%, gentamicin 99%, clindamycin 96%, tetracycline 96%, and erythromycin 56%. ^ Conclusion: The ED is becoming an important area for disease transmission between the sterile hospital environment and the outside environment. As always, it is important to further research in the ED in an effort to better understand MRSA transmission and antibiotic resistance, as well as to keep surveillance for the introduction of new opportunistic pathogens into the population. ^

Age -period -cohort analysis: An extension of Cox's lifetable regression with time -dependent covariates

It is well known that an identification problem exists in the analysis of age-period-cohort data because of the relationship among the three factors (date of birth + age at death = date of death). There are numerous suggestions about how to analyze the data. No one solution has been satisfactory. The purpose of this study is to provide another analytic method by extending the Cox's lifetable regression model with time-dependent covariates. The new approach contains the following features: (1) It is based on the conditional maximum likelihood procedure using a proportional hazard function described by Cox (1972), treating the age factor as the underlying hazard to estimate the parameters for the cohort and period factors. (2) The model is flexible so that both the cohort and period factors can be treated as dummy or continuous variables, and the parameter estimations can be obtained for numerous combinations of variables as in a regression analysis. (3) The model is applicable even when the time period is unequally spaced.^ Two specific models are considered to illustrate the new approach and applied to the U.S. prostate cancer data. We find that there are significant differences between all cohorts and there is a significant period effect for both whites and nonwhites. The underlying hazard increases exponentially with age indicating that old people have much higher risk than young people. A log transformation of relative risk shows that the prostate cancer risk declined in recent cohorts for both models. However, prostate cancer risk declined 5 cohorts (25 years) earlier for whites than for nonwhites under the period factor model (0 0 0 1 1 1 1). These latter results are similar to the previous study by Holford (1983).^ The new approach offers a general method to analyze the age-period-cohort data without using any arbitrary constraint in the model. ^