A Predictive Model for the Diagnosis of Allergic Drug Reactions According to the Medical History.

BACKGROUND: Quantification of the risk of an allergic drug reaction through the medical history is essential in clinical decision making. However, in normal clinical practice, this evaluation is generally entirely subjective. OBJECTIVE: The objective of this study was to construct a mathematical model to predict the risk of allergic drug reactions using the data collected in the medical history. METHODS: A total of 696 active principles, corresponding to 466 patients aged more than 14 years attending the Allergy Service of the University Hospital of Salamanca, were included. Simple binary logistic regression was used to determine associations between variables from the medical history and the final diagnosis, to construct a predictive model. RESULTS: Variables useful in predicting a final diagnosis of allergic drug reaction were age, sex, drug class, number of active principles, time to the reaction, number of doses, clinical presentation suggestive of allergic disease, and time to medical consultation. True adverse drug reactions were estimated to occur in 20% of active principles. However, possible allergic reactions could only be ruled out in 52.2%. CONCLUSIONS: The use of mathematical models could greatly improve the discriminatory capacity of the medical history. Both the overdiagnosis and underdiagnosis of allergic drug reactions should be considered a public health problem.

Health impact assessment of air pollution in Valladolid, Spain.

OBJECTIVE: To estimate the attributable and targeted avoidable deaths (ADs; TADs) of outdoor air pollution by ambient particulate matter (PM10), PM2.5 and O3 according to specific WHO methodology. DESIGN: Health impact assessment. SETTING: City of Valladolid, Spain (around 300 000 residents). DATA SOURCES: Demographics; mortality; pollutant concentrations collected 1999-2008. MAIN OUTCOME MEASURES: Attributable fractions; ADs and TADs per year for 1999-2008. RESULTS: Higher TADs estimates (shown here) were obtained when assuming as 'target' concentrations WHO Air Quality Guidelines instead of Directive 2008/50/EC. ADs are considered relative to pollutant background levels. All-cause mortality associated to PM10 (all ages): 52 ADs (95% CI 39 to 64); 31 TADs (95% CI 24 to 39).All-cause mortality associated to PM10 (<5 years): 0 ADs (95% CI 0 to 1); 0 TADs (95% CI 0 to 1). All-cause mortality associated to PM2.5 (>30 years): 326 ADs (95% CI 217 to 422); 231 TADs (95% CI 153 to 301). Cardiopulmonary and lung cancer mortality associated to PM2.5 (>30 years): Cardiopulmonary: 186 ADs (95% CI 74 to 280); 94 TADs (95% CI 36 to 148). Lung cancer : 51 ADs (95% CI 21 to 73); 27 TADs (95% CI 10 to 41).All-cause, respiratory and cardiovascular mortality associated to O3 (all ages): All-cause: 52ADs (95% CI 25 to 77) ; 31 TADs (95% CI 15 to 45). Respiratory: 5ADs (95% CI -2 to 13) ; 3 TADs (95% CI -1 to 8). Cardiovascular: 30 ADs (95% CI 8 to 51) ; 17 TADs (95% CI 5 to 30). Negative estimates which should be read as zero were obtained when pollutant concentrations were below counterfactuals or assumed risk coefficients were below one. CONCLUSIONS: Our estimates suggest a not negligible negative impact on mortality of outdoor air pollution. The implementation of WHO methodology provides critical information to distinguish an improvement range in air pollution control.