A Comparison of the Prevalence of, Demographics of, and Effects on Outcomes of Bilateral Versus Unilateral Femoral Shaft Fractures: A Retrospective Cohort Analysis From the National Trauma Data Bank.

OBJECTIVES: To document the prevalence of, and the effect on outcomes, operatively treated bilateral femur fractures treated using contemporary treatments. DESIGN: A retrospective cohort using data from the National Trauma Data Bank. PARTICIPANTS: In total, 119,213 patients in the National Trauma Data Bank between the years 2007 and 2015 who had operatively treated femoral shaft fractures. MAIN OUTCOME MEASUREMENTS: Complication rates, hospital length of stay (LOS), days in the intensive care unit (ICU LOS), days on a ventilator, and mortality rates. RESULTS: Patients with bilateral femur fractures had increased overall complications (0.74 vs. 0.50, P < 0.0001), a longer LOS (14.3 vs. 9.2, P < 0.0001), an increased ICU LOS (5.3 vs. 2.4, P < 0.0001), and more days on a ventilator (3.1 vs. 1.3, P < 0.0001), when compared with unilateral fractures. Bilateral femoral shaft fractures were independently associated with worse outcomes in all primary domains when adjusted by Injury Severity Score (P < 0.0001), apart from mortality rates. Age-adjusted bilateral injuries were independently associated with worse outcomes in all primary domains (P < 0.0001) except for the overall complication rate. A delay in fracture fixation beyond 24 hours was associated with increased mortality (P < 0.0001) and worse outcomes for all other primary measures (P < 0.0001 to P = 0.0278) for all patients. CONCLUSIONS: Bilateral femoral shaft fractures are an independent marker for increased hospital and ICU LOS, number of days on a ventilator, and increased complication rates, when compared with unilateral injuries and adjusted for age and Injury Severity Score. Timely definitive fixation, in a physiologically appropriate patient, is critical because a delay is associated with worse inpatient outcome measures and higher mortality rates. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Epidemiology and Outcomes of Granulomatosis With Polyangiitis in Pediatric and Working-Age Adult Populations In the United States: Analysis of a Large National Claims Database.

OBJECTIVE: The incidence and prevalence of granulomatosis with polyangiitis (GPA) in the US is not well characterized. Owing to its rarity, outcomes data in pediatric-onset GPA are also lacking. The aims of this study were to describe the epidemiology of GPA and outcomes in GPA patients in the US, and to compare outcomes between pediatric and working-age adult patients. METHODS: A retrospective cohort study using the 2006-2014 Truven Health Analytics MarketScan Commercial Claims and Encounters Database was conducted. The incidence and prevalence rates of pediatric and adult GPA (age <65 years) were calculated. Outcomes among the 2 age groups were analyzed. RESULTS: A total of 5,562 cases of GPA were identified, of which 214 (3.8%) were pediatric onset and 5,348 (96.2%) were adult onset. The incidence rate of pediatric-onset GPA was 1.8 cases per 1 million person-years, compared to 12.8 cases per 1 million person-years in working-age adults. There was a slight female preponderance in both groups (63% and 53% among pediatric and adult GPA patients, respectively). Rates of hospitalization and severe infections were high in both children and working-age adults, but children had more frequent hospitalizations (rate ratio [RR] 1.3 [95% confidence interval (95% CI) 1.1-1.4]) and 2-3-times higher rates of leukopenia (RR 2.6 [95% CI 1.5-4.3]), neutropenia (RR 2.2 [95% CI 1.2-4.0]), and hypogammaglobulinemia (RR 3.7 [95% CI 2.0-6.4]). Time-to-event analyses showed no differences in the time to hospitalization, severe infection, major relapse, or end-stage renal disease. CONCLUSION: This study represents the largest cohort of GPA reported to date. Pediatric GPA patients experienced more frequent hospitalizations and were more vulnerable to hematologic complications than non-elderly adult patients.

Neurofibromatosis type 1 and chronic neurological conditions in the United States: an administrative claims analysis.

PURPOSE: Neurofibromatosis type 1 has been linked to several neurological conditions, including epilepsy, Parkinson disease, headache, multiple sclerosis, and sleep disturbances, predominantly through case reports and patient series that lack comparison groups. Our objective was to assess whether specific neurological conditions occur more frequently in individuals with neurofibromatosis type 1 versus those without neurofibromatosis type 1. METHODS: We used the 2006-2010 MarketScan Commercial Claims and Encounters database to examine associations between neurological conditions and neurofibromatosis type 1. The neurofibromatosis type 1 group was identified through ≥2 International Classification of Diseases, Ninth Revision, Clinical Modification neurofibromatosis codes (237.70, 237.71) occurring ≥30 days apart or one inpatient neurofibromatosis code. A nonneurofibromatosis type 1 comparison group was frequency matched to the neurofibromatosis type 1 group on age and enrollment length at a 10:1 ratio. Unconditional logistic regression was employed to calculate adjusted odds ratios and 95% confidence intervals for associations between neurofibromatosis and neurological conditions. RESULTS: Compared with the nonneurofibromatosis type 1 group (n = 85,790), the neurofibromatosis type 1 group (n = 8,579) had significantly higher odds of health insurance claims for epilepsy (odds ratio: 7.3; 95% confidence interval: 6.4-8.3), Parkinson disease (odds ratio: 3.1; 95% confidence interval: 1.3-7.5), headache (odds ratio: 2.9; 95% confidence interval: 2.6-3.1), multiple sclerosis (odds ratio: 1.9; 95% confidence interval: 1.2-2.9), and sleep disturbances/disorder (odds ratio: 1.4; 95% confidence interval: 1.2-3.6). CONCLUSION: This large study provides strong evidence for positive associations between several neurological conditions and neurofibromatosis type 1.

Adding flexible temporal constraints to identify chronic comorbid conditions in ambulatory claims data.

Chronic comorbid conditions are important predictors of primary care outcomes, provide context for clinical decisions, and are potential complications of diseases and treatments. Comorbidity indices and multimorbidity categorization strategies based on administrative claims data enumerate diagnostic codes in easily modifiable lists, but usually have inflexible temporal requirements, such as requiring two claims greater than 30 days apart, or three claims in three quarters. Table structures and claims data search algorithms were developed to support flexible temporal constraints. Tables of disease categories allow subgroups with different numbers of events, different times between similar claims, variable periods of interest, and specified diagnostic code substitutability. The strategy was tested on five years of private insurance claims from 2.2 million working age adults. The contrast between rarely recorded, high prevalence diagnoses (smoking and obesity) and frequently recorded but not necessarily chronic diagnoses (musculoskeletal complaints) demonstrated the advantage of flexible temporal criteria.

The development of a decision analytic model of changes in mean deviation in people with glaucoma: the COA model.

PURPOSE: To create and validate a statistical model predicting progression of primary open-angle glaucoma (POAG) assessed by loss of visual field as measured in mean deviation (MD) using 3 landmark studies of glaucoma progression and treatment. DESIGN: A Markov decision analytic model using patient level data described longitudinal MD changes over 7 years. PARTICIPANTS: Patient-level data from the Collaborative Initial Glaucoma Treatment Study (n = 607), the Ocular Hypertension Treatment Study (OHTS; n = 148; only those who developed POAG in the first 5 years of OHTS) and Advanced Glaucoma Intervention Study (n = 591), the COA model. METHODS: We developed a Markov model with transition matrices stratified by current MD, age, race, and intraocular pressure categories and used a microsimulation approach to estimate change in MD over 7 years. Internal validation compared model prediction for 7 years to actual MD for COA participants. External validation used a cohort of glaucoma patients drawn from university clinical practices. MAIN OUTCOME MEASURES: Change in visual field as measured in MD in decibels (dB). RESULTS: Regressing the actual MD against the predicted produced an R(2) of 0.68 for the right eye and 0.63 for the left. The model predicted ending MD for right eyes of 65% of participants and for 63% of left eyes within 3 dB of actual results at 7 years. In external validation the model had an R(2) of 0.79 in the right eye and 0.77 in the left at 5 years. CONCLUSIONS: The COA model is a validated tool for clinicians, patients, and health policy makers seeking to understand longitudinal changes in MD in people with glaucoma.