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Reported per-patient costs of Clostridium difficile infection (CDI) vary by 2 orders of magnitude among different hospitals, implying that infection control officers need precise, local analyses to guide rational decision making between interventions.
We sought to comprehensively estimate changes in length of stay (LOS) attributable to CDI at a single urban tertiary-care facility using only data automatically extractable from the electronic medical record (EMR).
We performed a retrospective cohort study of 171,938 visits spanning a 7-year period. In total, 23,968 variables were extracted from EMR data recorded within 24 hours of admission to train elastic-net regularized logistic regression models for propensity score matching. To address time-dependent bias (reverse causation), we separately stratified comparisons by time of infection, and we fit multistate models.
The estimated difference in median LOS for propensity-matched cohorts varied from 3.1 days (95% CI, 2.2–3.9) to 10.1 days (95% CI, 7.3–12.2) depending on the case definition; however, dependency of the estimate on time to infection was observed. Stratification by time to first positive toxin assay, excluding probable community-acquired infections, showed a minimum excess LOS of 3.1 days (95% CI, 1.7–4.4). Under the same case definition, the multistate model averaged an excess LOS of 3.3 days (95% CI, 2.6–4.0).
In this study, 2 independent time-to-infection adjusted methods converged on similar excess LOS estimates. Changes in LOS can be extrapolated to marginal dollar costs by multiplying by average costs of an inpatient day. Infection control officers can leverage automatically extractable EMR data to estimate costs of CDI at their own institutions.
This chapter describes the methods used in animal models of sleep to dissect the genetic basis of complex traits that is to say, traits in which variation has both environmental and genetic sources, and in which the genetic component consists of multiple genetic loci. Crosses between inbred strains are still the most widely used method for mapping loci involved in complex traits in model organisms. Cross between inbred strains generates genetically identical offspring, with one chromosome from one strain and one from the other. Genetic mapping using inbred strain crosses proceeds by determining where in the genome genetic variation is associated with phenotypic variation. Two difficulties confront in silico mapping: low power and unequal degrees of relatedness between inbred strains. One attempt to deal with the problem of low power in inbred strain analyses is the development of the hybrid mouse diversity panel (HMDP).