In Vitro Methods for Specific IgE Detection on Cow’s Milk Allergy

Background: A new method for determining serum specific IgE (IMMULITE“ 2000 3gAllergy) has recently become available. Objective: To evaluate the clinical performance of IMMULITE 2000 in the diagnosis of cow’s milk allergy compared with that of UniCAP“. Additionally, we verified the behavior of both methods at two diagnostic decision points proposed by other authors. Methods: The study population consisted of 31 children with cow’s milk allergy (group A) and a control group of 19 atopic children without food allergy(group B). A blood sample from each child was tested using both methods and the results were compared. Results: In group A, the values for cow’s milk IgE ranged from 0.35 kU/L (the lowest common detection limit) to above 100 kU/L. In group B, the values were less than 1.1 kU/L for IMMULITE 2000 and less than 1.6 kU/L for UniCAP. An agreement of 90 % in IgE classes was obtained. Both methods demonstrated exactly the same diagnostic performance(sensitivity: 100 %; specificity: 78.9 %; negative predictive value: 100%; positive predictive value: 84.6%;efficiency: 90.2 %). The evaluation of the two methods at the two different decision points proposed in the literature showed a better positive predictive value with UniCAP, but we obtained equivalent performance with IMMULITE 2000 by choosing higher cutoff values. Conclusions: We conclude that IMMULITE 2000 is as effective as UniCAP in the diagnosis of cow’s milk allergy. Both methods can be used to obtain site-specific decision points that are population, age and disease dependent.

Characterizing the Risk Profiles of Intensive Care Units

OBJECTIVE: To develop a new method to evaluate the performance of individual ICUs through the calculation and visualisation of risk profiles. METHODS: The study included 102,561 patients consecutively admitted to 77 ICUs in Austria. We customized the function which predicts hospital mortality (using SAPS II) for each ICU. We then compared the risks of hospital mortality resulting from this function with the risks which would be obtained using the original function. The derived risk ratio was then plotted together with point-wise confidence intervals in order to visualise the individual risk profile of each ICU over the whole spectrum of expected hospital mortality. MAIN MEASUREMENTS AND RESULTS: We calculated risk profiles for all ICUs in the ASDI data set according to the proposed method. We show examples how the clinical performance of ICUs may depend on the severity of illness of their patients. Both the distribution of the Hosmer-Lemeshow goodness-of-fit test statistics and the histogram of the corresponding P values demonstrated a good fit of the individual risk models. CONCLUSIONS: Our risk profile model makes it possible to evaluate ICUs on the basis of the specific risk for patients to die compared to a reference sample over the whole spectrum of hospital mortality. Thus, ICUs at different levels of severity of illness can be directly compared, giving a clear advantage over the use of the conventional single point estimate of the overall observed-to-expected mortality ratio.