@article{GrubeKoenneckeWalteretal.2013,
  author    = {Grube, Maike Miriam and Koennecke, Hans-Christian and Walter, Georg and Meisel, Andreas and Sobesky, Jan and Nolte, Christian Hans and Wellwood, Ian and Heuschmann, Peter Ulrich},
  title     = {Influence of Acute Complications on Outcome 3 Months after Ischemic Stroke},
  series = {PLOS ONE},
  volume    = {8},
  journal   = {PLOS ONE},
  number    = {9},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0075719},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-128362},
  pages     = {e75719},
  year      = {2013},
  abstract  = {Background: Early medical complications are potentially modifiable factors influencing in-hospital outcome. We investigated the influence of acute complications on mortality and poor outcome 3 months after ischemic stroke. Methods: Data were obtained from patients admitted to one of 13 stroke units of the Berlin Stroke Registry (BSR) who participated in a 3-months-follow up between June 2010 and September 2012. We examined the influence of the cumulative number of early in-hospital complications on mortality and poor outcome (death, disability or institutionalization) 3 months after stroke using multivariable logistic regression analyses and calculated attributable fractions to determine the impact of early complications on mortality and poor outcome. Results: A total of 2349 ischemic stroke patients alive at discharge from acute care were included in the analysis. Older age, stroke severity, pre-stroke dependency and early complications were independent predictors of mortality 3 months after stroke. Poor outcome was independently associated with older age, stroke severity, pre-stroke dependency, previous stroke and early complications. More than 60\% of deaths and poor outcomes were attributed to age, pre-stroke dependency and stroke severity and in-hospital complications contributed to 12.3\% of deaths and 9.1\% of poor outcomes 3 months after stroke. Conclusion: The majority of deaths and poor outcomes after stroke were attributed to non-modifiable factors. However, early in-hospital complications significantly affect outcome in patients who survived the acute phase after stroke, underlining the need to improve prevention and treatment of complications in hospital.},
  language  = {en}
}
@article{EliasHeuschmannSchmittetal.2013,
  author    = {Elias, Johannes and Heuschmann, Peter U. and Schmitt, Corinna and Eckhardt, Frithjof and Boehm, Hartmut and Maier, Sebastian and Kolb-M{\"a}urer, Annette and Riedmiller, Hubertus and M{\"u}llges, Wolfgang and Weisser, Christoph and Wunder, Christian and Frosch, Matthias and Vogel, Ulrich},
  title     = {Prevalence dependent calibration of a predictive model for nasal carriage of methicillin-resistant Staphylococcus aureus},
  series = {BMC Infectious Diseases},
  journal   = {BMC Infectious Diseases},
  doi       = {10.1186/1471-2334-13-111},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96091},
  year      = {2013},
  abstract  = {Background Published models predicting nasal colonization with Methicillin-resistant Staphylococcus aureus among hospital admissions predominantly focus on separation of carriers from non-carriers and are frequently evaluated using measures of discrimination. In contrast, accurate estimation of carriage probability, which may inform decisions regarding treatment and infection control, is rarely assessed. Furthermore, no published models adjust for MRSA prevalence. Methods Using logistic regression, a scoring system (values from 0 to 200) predicting nasal carriage of MRSA was created using a derivation cohort of 3091 individuals admitted to a European tertiary referral center between July 2007 and March 2008. The expected positive predictive value of a rapid diagnostic test (GeneOhm, Becton \& Dickinson Co.) was modeled using non-linear regression according to score. Models were validated on a second cohort from the same hospital consisting of 2043 patients admitted between August 2008 and January 2012. Our suggested correction score for prevalence was proportional to the log-transformed odds ratio between cohorts. Calibration before and after correction, i.e. accurate classification into arbitrary strata, was assessed with the Hosmer-Lemeshow-Test. Results Treating culture as reference, the rapid diagnostic test had positive predictive values of 64.8\% and 54.0\% in derivation and internal validation corhorts with prevalences of 2.3\% and 1.7\%, respectively. In addition to low prevalence, low positive predictive values were due to high proportion (> 66\%) of mecA-negative Staphylococcus aureus among false positive results. Age, nursing home residence, admission through the medical emergency department, and ICD-10-GM admission diagnoses starting with "A" or "J" were associated with MRSA carriage and were thus included in the scoring system, which showed good calibration in predicting probability of carriage and the rapid diagnostic test's expected positive predictive value. Calibration for both probability of carriage and expected positive predictive value in the internal validation cohort was improved by applying the correction score. Conclusions Given a set of patient parameters, the presented models accurately predict a) probability of nasal carriage of MRSA and b) a rapid diagnostic test's expected positive predictive value. While the former can inform decisions regarding empiric antibiotic treatment and infection control, the latter can influence choice of screening method.},
  language  = {en}
}