A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses

<p>Abstract</p> <p>Background</p> <p>Kawasaki disease is an acute vasculitis of infants and young children that is recognized through a constellation of clinical signs that can mimic other benign conditions of childhood. The etiology remains unknown and there is no specific laboratory-based test to identify patients with Kawasaki disease. Treatment to prevent the complication of coronary artery aneurysms is most effective if administered early in the course of the illness. We sought to develop a diagnostic algorithm to help clinicians distinguish Kawasaki disease patients from febrile controls to allow timely initiation of treatment.</p> <p>Methods</p> <p>Urine peptidome profiling and whole blood cell type-specific gene expression analyses were integrated with clinical multivariate analysis to improve differentiation of Kawasaki disease subjects from febrile controls.</p> <p>Results</p> <p>Comparative analyses of multidimensional protein identification using 23 pooled Kawasaki disease and 23 pooled febrile control urine peptide samples revealed 139 candidate markers, of which 13 were confirmed (area under the receiver operating characteristic curve (ROC AUC 0.919)) in an independent cohort of 30 Kawasaki disease and 30 febrile control urine peptidomes. Cell type-specific analysis of microarrays (csSAM) on 26 Kawasaki disease and 13 febrile control whole blood samples revealed a 32-lymphocyte-specific-gene panel (ROC AUC 0.969). The integration of the urine/blood based biomarker panels and a multivariate analysis of 7 clinical parameters (ROC AUC 0.803) effectively stratified 441 Kawasaki disease and 342 febrile control subjects to diagnose Kawasaki disease.</p> <p>Conclusions</p> <p>A hybrid approach using a multi-step diagnostic algorithm integrating both clinical and molecular findings was successful in differentiating children with acute Kawasaki disease from febrile controls.</p

Inventory Control Research: A Survey

In past decades there have been occasional upsurges of intensive interest in inventory control problems, sometimes in the aftermath of forced inventory liquidation. For the most part, the literature consisted of a few articles in business journals that had but little impact on the current business behavior of the time. In the last few years we have witnessed another upsurge of interest which far surpasses any of its predecessors, with respect to the quantity and quality of the work accomplished as well as its overall impact on the business community. This vigorous research and the interest it has aroused have been made possible by parallel development in research and in business. Statisticians and economists have become interested in industrial problems concomitantly with the increased attention in business to techniques of advanced management. The appearance of this journal is an example of this harmony of interests that has come into being. The fact that modern statistical methods have been applied successfully in several instances has had much influence on the interest level of both research workers and industrialists.

A Family of Dynamic Inventory Models

A family of inventory models in which demand is allowed to change with time is studied. One general model is presented which includes every member of the "family" as a special case. The general model assumes that demand is a random variable. The mean rate of demand may vary over time but demands in different time periods are assumed independent. It is assumed that there is a date of obsolescence for the item with no demands occurring after this date. The time of obsolescence may be either known or alternatively a finite number of obsolescence dates and their probable occurrence may be specified. Procurement lead times are allowed to be random variables, subject to certain restrictions which are discussed. Procurements are allowed only at a finite number of predetermined times which may be specified in any way desired. Demands occurring when the system is out of stock are assumed to be backordered. The procurement quantities are determined by solving a dynamic programming problem which minimizes the sum of the expected costs of procurement, carrying inventory, stockouts, and losses from obsolescence. The dynamic programming problem is within the range of feasibility computationally, because only tables involving a single parameter are required. A number of special cases of the general model are studied and it is shown that most dynamic models which have appeared in the literature are special cases of the general model.

An Optimal Final Inventory Model

A model is developed which allows the determination of the optimal inventory level for an item at any time if no additional procurements are to be made. It is assumed that the item has a known date of obsolescence and that the demand is Poisson distributed with a fixed mean over the useful life of the tem. The model constitutes an extension of other life-of-type models in that both costs which are incurred at a fixed point in time (liquidation losses) and other costs which are a function of time (carrying charges and stock-out costs) are included. In many operational situations both of these types of costs are relevant.