We investigated genetic, epidemiologic, and environmental factors contributing to positive Staphylococcus epidermidis joint cultures.

Retrospective cohort study with whole-genome sequencing (WGS).

We identified S. epidermidis isolates from hip or knee cultures in patients with 1 or more prior corresponding intra-articular procedure at our hospital.

WGS and single-nucleotide polymorphism–based clonality analyses were performed, including species identification, in silico multilocus sequence typing (MLST), phylogenomic analysis, and genotypic assessment of the prevalence of specific antibiotic resistance and virulence genes. Epidemiologic review was performed to compare cluster and noncluster cases.

In total, 60 phenotypically distinct S. epidermidis isolates were identified. After removal of duplicates and impure samples, 48 isolates were used for the phylogenomic analysis, and 45 (93.7%) isolates were included in the clonality analysis. Notably, 5 S. epidermidis strains (10.4%) showed phenotypic susceptibility to oxacillin yet harbored mecA, and 3 (6.2%) strains showed phenotypic resistance despite not having mecA. Smr was found in all isolates, and mupA positivity was not observed. We also identified 6 clonal clusters from the clonality analysis, which accounted for 14 (31.1%) of the 45 S. epidermidis isolates. Our epidemiologic investigation revealed ties to common aspirations or operative procedures, although no specific common source was identified.

Most S. epidermidis isolates from clinical joint samples are diverse in origin, but we identified an important subset of 31.1% that belonged to subclinical healthcare–associated clusters. Clusters appeared to resolve spontaneously over time, suggesting the benefit of routine hospital infection control and disinfection practices.

Registry-based trials have emerged as a potentially cost-saving study methodology. Early estimates of cost savings, however, conflated the benefits associated with registry utilisation and those associated with other aspects of pragmatic trial designs, which might not all be as broadly applicable. In this study, we sought to build a practical tool that investigators could use across disciplines to estimate the ranges of potential cost differences associated with implementing registry-based trials versus standard clinical trials.

We built simulation Markov models to compare unique costs associated with data acquisition, cleaning, and linkage under a registry-based trial design versus a standard clinical trial. We conducted one-way, two-way, and probabilistic sensitivity analyses, varying study characteristics over broad ranges, to determine thresholds at which investigators might optimally select each trial design.

Registry-based trials were more cost effective than standard clinical trials 98.6% of the time. Data-related cost savings ranged from $4300 to $600,000 with variation in study characteristics. Cost differences were most reactive to the number of patients in a study, the number of data elements per patient available in a registry, and the speed with which research coordinators could manually abstract data. Registry incorporation resulted in cost savings when as few as 3768 independent data elements were available and when manual data abstraction took as little as 3.4 seconds per data field.

Registries offer important resources for investigators. When available, their broad incorporation may help the scientific community reduce the costs of clinical investigation. We offer here a practical tool for investigators to assess potential costs savings.

To evaluate invasiveness index as a potential predictor of spine surgical site infection (SSI) after spinal fusion, revision fusion, or laminectomy.

Retrospective cohort study.

Single, large, academic medical center.

Adults undergoing spinal fusion, revision fusion, or laminectomy.

Data were obtained from electronic hospital databases; cases of SSI were extracted from the infection control database using National Healthcare Safety Network (NHSN) definitions. For each case, an invasiveness index, determined by surgical approach, procedure, and number of spine levels treated, was calculated using current procedural terminology (CPT) billing codes. Statistical analyses were performed using univariate and multivariate logistic regression models.

In total, 3,143 patients met inclusion criteria, and 43 of these developed SSI. Multivariate regression showed that advanced age (odds ratio [OR], 1.03; 95% confidence interval [CI], 1.005–1.05, for each year of life) and invasiveness index (medium invasiveness index OR, 5.36; 95% CI, 1.92–14.96; high invasiveness index OR, 14.1; 95% CI, 4.38–45.43) were significant predictors of infection. In subgroup analyses of spinal fusion patients, morbid obesity (OR, 2.542; 95% CI, 1.08–5.99), trauma (OR, 2.41; 95% CI, 1.05–5.55), and invasiveness index (medium invasiveness index OR, 5.39; 95% CI, 1.56–18.61; high invasiveness index OR, 13.44; 95% CI, 3.28–55.01) were significant predictors of SSI. Models containing invasiveness index were compared to NHSN models and demonstrated similar performance.

Invasiveness index is a predictor of SSI after spinal fusion and performs similarly to NHSN models. Invasiveness index shows promise as a potential risk stratification tool that is easily calculated and is available preoperatively.

Infect Control Hosp Epidemiol 2016:1–7