Concurrent sexual partnerships may help to explain the disproportionately high prevalence of HIV and other sexually transmitted infections among African Americans. The persistence of such disparities would also require strong assortative mixing by race. We examined descriptive evidence from 4 nationally representative US surveys and found consistent support for both elements of this hypothesis. Using a data-driven network simulation model, we found that the levels of concurrency and assortative mixing observed produced a 2.6-fold racial disparity in the epidemic potential among young African American adults.

BACKGROUND CONTEXT The possibility and likelihood of a postoperative medical complication after spine surgery undoubtedly play a major role in the decision making of the surgeon and patient alike. Although prior study has determined relative risk and odds ratio values to quantify risk factors, these values may be difficult to translate to the patient during counseling of surgical options. Ideally, a model that predicts absolute risk of medical complication, rather than relative risk or odds ratio values, would greatly enhance the discussion of safety of spine surgery. To date, there is no risk stratification model that specifically predicts the risk of medical complication. PURPOSE The purpose of this study was to create and validate a predictive model for the risk of medical complication during and after spine surgery. STUDY DESIGN/SETTING Statistical analysis using a prospective surgical spine registry that recorded extensive demographic, surgical, and complication data. Outcomes examined are medical complications that were specifically defined a priori. This analysis is a continuation of statistical analysis of our previously published report. METHODS Using a prospectively collected surgical registry of more than 1,476 patients with extensive demographic, comorbidity, surgical, and complication detail recorded for 2 years after surgery, we previously identified several risk factor for medical complications. Using the beta coefficients from those log binomial regression analyses, we created a model to predict the occurrence of medical complication after spine surgery. We split our data into two subsets for internal and cross-validation of our model. We created two predictive models: one predicting the occurrence of any medical complication and the other predicting the occurrence of a major medical complication. RESULTS The final predictive model for any medical complications had a receiver operator curve characteristic of 0.76, considered to be a fair measure. The final predictive model for any major medical complications had receiver operator curve characteristic of 0.81, considered to be a good measure. The final model has been uploaded for use on SpineSage.com. CONCLUSION We present a validated model for predicting medical complications after spine surgery. The value in this model is that it gives the user an absolute percent likelihood of complication after spine surgery based on the patient’s comorbidity profile and invasiveness of surgery. Patients are far more likely to understand an absolute percentage, rather than relative risk and confidence interval values. A model such as this is of paramount importance in counseling patients and enhancing the safety of spine surgery. In addition, a tool such as this can be of great use particularly as health care trends toward pay-for-performance, quality metrics, and risk adjustment. To facilitate the use of this model, we have created a website (SpineSage.com) where users can enter in patient data to determine likelihood of medical complications after...

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Power-law models do not fit the data better than alternative models, and they consistently make inaccurate epidemic predictions. Better models are needed to represent the behavioral basis of sexual networks and the structures that result, if these data are to be used for disease transmission modeling.

Background Unloader braces are a nonsurgical approach for predominantly unicompartmental knee arthritis. Although noninvasive, braces are expensive and it is unclear whether clinical factors, if any, will predict regular brace use. Questions/purposes We asked: (1) Do patients continue to use the unloader brace more than 1 year after it is prescribed? (2) Do any clinical or radiographic factors predict continued use of the unloader brace after the first year? (3) What are the most common subjective reasons that patients give for discontinuing the brace?Methods We administered 110 surveys to all patients who were fitted for unloader knee braces for predominantly unicompartmental osteoarthritis 12 to 40 months before administration of the survey. Standardized indications and fitting protocols were used. The following parameters were tested for association with ongoing brace use: alignment, arthritis severity, compartment involved, BMI, weight, age, gender, pain and function, number of refittings, and problems with the brace. The survey response rate was 81% (89 of 110). Results Of the 89 responders, 28% reported regular brace use (twice per week, an hour at a time, or more); at 2 years, 25% used the brace regularly. No clinical or radiographic factors considered were associated with ongoing brace use. Patients reported lack of symptomatic relief, brace discomfort, poor fit, and skin irritation as reasons for discontinuing the brace. Conclusions Surgeons and patients need to balance the benefits and absence of complications of bracing against cost and the low likelihood of ongoing use 1 year or more after the prescription of the brace. Level of Evidence Level III, prognostic study. See Instructions for Authors for a complete description of levels of evidence.