Evaluation and Treatment of Iron Deficiency Anemia: A Gastroenterological Perspective

A substantial volume of the consultations requested of gastroenterologists are directed towards the evaluation of anemia. Since iron deficiency anemia often arises from bleeding gastrointestinal lesions, many of which are malignant, establishment of a firm diagnosis usually obligates an endoscopic evaluation. Although the laboratory tests used to make the diagnosis have not changed in many decades, their interpretation has, and this is possibly due to the availability of extensive testing in key populations. We provide data supporting the use of the serum ferritin as the sole useful measure of iron stores, setting the lower limit at 100 μg/l for some populations in order to increase the sensitivity of the test. Trends of the commonly obtained red cell indices, mean corpuscular volume, and the red cell distribution width can provide valuable diagnostic information. Once the diagnosis is established, upper and lower gastrointestinal endoscopy is usually indicated. Nevertheless, in many cases a gastrointestinal source is not found after routine evaluation. Additional studies, including repeat upper and lower endoscopy and often investigation of the small intestine may thus be required. Although oral iron is inexpensive and usually effective, there are many gastrointestinal conditions that warrant treatment of iron deficiency with intravenous iron

Forecast Evaluation of Explanatory Models of Financial Return Variability

A practice that has become widespread is that of comparing forecasts of financial return variability obtained from discrete time models against high frequency estimates based on continuous time theory. In explanatory financial return variability modelling this raises several methodological and practical issues, which suggests an alternative framework is needed. The contribution of this study is twofold. First, the finite sample properties of operational and practical procedures for the forecast evaluation of explanatory discrete time models of financial return variability are studied. Second, with basis in the simulation results a simple framework is proposed and illustrated

A simple message for autocorrelation correctors: don't

Though the practice of ‘correcting for residual autocorrelation’ has long been critized, it is still commonly advocated and followed. A simple example shows that even when a linear regression model has first-order autoregressive errors, it is possible for autoregressive least squares estimation (e.g., Cochrane-Orcutt) to yield inconsistent estimates. This dramatically illustrates that ‘autocorrelation correction’ is invalid in general, and cannot be justified on the grounds of ‘robustifying’ estimation against the presence of residual serial correlation. Invalid common factors in I(1) systems also have adverse effects on inference. A ‘general-to-specific’ modelling strategy applied to the observed modelled variables avoids these difficulties