Count data are common in many fields such as public health. Hurdle models have been developed to model count data when the zero count could be either inflated or deflated. However, when data are repeatedly collected over time and spatially correlated, it is very challenging to model the data appropriately. For example, to study health professional shortage areas, the number of primary care physicians along with other demographic characteristics are collected at the county level in the USA and over different years. Since the data are repeatedly collected over time, counties are nested within the state, and adjacent counties are geographically correlated, the dependence structure of the data is very complex. We develop a Bayesian hurdle model with multilayered random effects to incorporate this complex structure. We use a time-varying random effect for each state to capture the time effect at the state level, and a temporal thin plate spline to capture the spatiotemporal correlation across different counties. We use STAN to obtain samples for inference from the posterior distribution. By using the model proposed, we can identify the important factors which impact health professional shortage areas. Simulation studies also confirm the effectiveness of the model.
Background
Delta granule storage pool deficiency (δ‐SPD) is a rare platelet disorder in which a deficiency of platelet granules leads to poor aggregation, resulting in varying clinical bleeding phenotypes. Children with δ‐SPD have variable laboratory results, making the proper diagnosis and evaluation controversial.
Objectives
To describe the demographic and laboratory trends of this population and to assess the value of electron microscopy in diagnostic evaluation and its correlation to bleeding symptoms.
Methods
We performed a retrospective review of 109 pediatric patients diagnosed with δ‐SPD. We collected demographic information and bleeding scores using a validated bleeding assessment tool. A descriptive and exploratory analysis was performed.
Results
The majority of patients were female, with an average age at diagnosis of 11.61 years. Females were diagnosed at a significantly older age presenting most often with menorrhagia, while males presented most commonly with epistaxis. The majority showed normal lumiaggregometry, the mean platelet electron microscopy (PEM) value was 2.37, and the mean bleeding score was 6. Bleeding assessment tool and PEM had a significantly weak correlation.
Conclusions
Patients with more dense granules per platelet had higher bleeding scores than those with fewer dense granules per platelet. The current body of evidence does not favor the use of PEM in routine clinical practice, and results are difficult to interpret. In patients with severe mucocutaneous bleeding symptoms and normal platelet aggregation studies, consideration should be given to an alternative diagnosis and further evaluation is warranted.
Cefdinir is frequently prescribed for pediatric infections despite lack of first-line indications. We reviewed Kentucky Medicaid claims from 2012 through 2016. Cefdinir prescriptions and spending significantly increased over the study period. Upper respiratory infections accounted for the majority of use. Inappropriate cefdinir use should be a priority for stewardship efforts.
Background. We hypothesize that preoperative functional platelet number (platelet count multiplied by platelet aggregation percentage) are associated with 30-day mortality after cardiac surgery. Methods. We linked our preoperative testing database with the STS (Society of Thoracic Surgeon) database to form a study cohort of 1390 patients who had cardiac surgeries between January 2008 and December 2013. Preoperative tests of platelet count and platelet aggregation were routinely performed on all cardiac surgical patients within 24 hours before entering the operating room. Multiple logistic regression models were used to determine whether functional platelet number are associated with 30-day mortality, modified composite major adverse cardiocerebral events, postoperative renal failure or requirement for new renal replacement therapy, and reoperation for bleeding. Log-linear models were used to examine whether functional platelet numbers are associated with hospital length of stay and intensive care unit length of stay. Results. Functional platelet number had an inverse association with 30-day mortality, and each 50 × 109/L increase in functional platelet number resulted in decreased 30-day mortality (odds ratio of 0.767 with 95% confidence interval = 0.591-0.996). For secondary outcomes, functional platelet number was neither associated with major adverse cardiocerebral event nor length of stay. However, we found that each 50 × 109/L increase in functional platelet number was associated with decreased reoperations for bleeding (odds ratio of 0.778 with 95% confidence interval = 0.636-0.951). Conclusions. The preoperative functional platelet number had significant associations with 30-day mortality after cardiac surgery. Functional platelet number could be used to guide timing of cardiac surgery, especially as more and more patients are receiving antiplatelet medications nowadays.
In many diagnostic accuracy studies, a priori orders may be available on multiple receiver operating characteristic curves. For example, being closer to delivery, fetal ultrasound measures in the third trimester should be no less accurate than those in the second trimester in predicting small-for-gestational-age births. Such an a priori order should be incorporated in estimating receiver operating characteristic curves and associated summary accuracy statistics, as it can potentially improve statistical efficiency of these estimates. Early work in the literature has mainly taken an indirect approach to this task and has induced the desired a priori order through modeling test score distributions. We instead propose a new strategy that incorporates the order directly through the modeling of receiver operating characteristic curves. We achieve this by exploiting the link between placement value (the relative position of a diseased test score in the healthy score distribution), the cumulative distribution function of placement value, and receiver operating characteristic curve, and by building stochastically ordered random variables through mixture distributions. We take a Bayesian semiparametric approach in using Dirichlet process mixture models so that the placement values can be flexibly modeled. We conduct extensive simulation studies to examine the performance of the proposed methodology and apply the new framework to data from obstetrics and women’s health studies.
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