Characterization of anaphylaxis reveals different metabolic changes depending on severity and triggers.

BACKGROUND: Despite the increasing incidence of anaphylaxis, its underlying molecular mechanisms and biomarkers for appropriate diagnosis remain undetermined. The rapid onset and potentially fatal outcome in the absence of managed treatment prevent its study. Up today, there are still no known biomarkers that allow an unequivocal diagnosis. Therefore, the aim of this study was to explore metabolic changes in patients suffering anaphylactic reactions depending on the trigger (food and/or drug) and severity (moderate and severe) in a real-life set-up. METHODS: Eighteen episodes of anaphylaxis, one per patient, were analysed. Sera were collected during the acute phase (T1), the recovery phase (T2) and around 2-3 months after the anaphylactic reaction (T0: basal state). Reactions were classified following an exhaustive allergological evaluation for severity and trigger. Sera samples were analysed using untargeted metabolomics combining liquid chromatography coupled to mass spectrometry (LC-MS) and proton nuclear magnetic resonance spectroscopy (1 H-NMR). RESULTS: 'Food T1 vs T2' and 'moderate T1 vs T2' anaphylaxis comparisons showed clear metabolic patterns during the onset of an anaphylactic reaction, which differed from those induced by drugs, food + drug or severe anaphylaxis. Moreover, the model of food anaphylaxis was able to distinguish the well-characterized IgE (antibiotics) from non-IgE-mediated anaphylaxis (nonsteroidal anti-inflammatory drugs), suggesting a differential metabolic pathway associated with the mechanism of action. Metabolic differences between 'moderate vs severe' at the acute phase T1 and at basal state T0 were studied. Among the altered metabolites, glucose, lipids, cortisol, betaine and oleamide were observed altered. CONCLUSIONS: The results of this exploratory study provide the first evidence that different anaphylactic triggers or severity induce differential metabolic changes along time or at specific time-point, respectively. Besides, the basal status T0 might identify high-risk patients, thus opening new ways to understand, diagnose and treat anaphylaxis.

Clinical Characterization and Diagnostic Approaches for Patients Reporting Hypersensitivity Reactions to Quinolones.

BACKGROUND: Quinolones are the second most frequent cause of hypersensitivity reactions (HSRs) to antibiotics. A marked increase in the number of patients with HSRs to quinolones has been detected. OBJECTIVE: To describe the clinical characteristics of patients with HSRs to quinolones and present methods for their diagnosis. METHODS: Patients attending the allergy unit due to reactions suggestive of HSRs to quinolones were prospectively evaluated between 2005 and 2018. Diagnosis was achieved using clinical history, skin tests (STs), basophil activation tests (BATs), and drug provocation tests (DPTs) if ST and BAT results were negative. RESULTS: We included 128 subjects confirmed as having HSRs to quinolones and 42 found to be tolerant. Anaphylaxis was the most frequent entity in immediate HSRs and was most commonly induced by moxifloxacin. Patients were evaluated a median of 150 days (interquartile range, 60-365 days) after the reaction. Of patients who underwent ST and BAT, 40.7% and 70%, respectively, were positive. DPT with a quinolone was performed in 48 cases, giving results depending on the culprit drug: when moxifloxacin was involved, 62.5% of patients gave a positive DPT result to ciprofloxacin, whereas none reacted to levofloxacin. The risk of HSR was 96 times higher in subjects who reported moxifloxacin-induced anaphylaxis and 18 times higher in those reporting immediate reactions compared with clinical entities induced by quinolones other than moxifloxacin and nonimmediate reactions. CONCLUSIONS: The diagnosis of HSR to quinolones is complex. The use of clinical history is essential as a first step. BAT shows higher sensitivity than STs. DPTs can be useful for finding safe alternative quinolones.

Allergy alerts in electronic health records for hospitalized patients.

BACKGROUND: Electronic health records (EHRs) are used to register important health-related information, such as allergic conditions, and contribute to the safety and quality of medical care. OBJECTIVES: To evaluate the use of allergy alert entries in EHRs and to establish the allergy profile of hospitalized patients. METHODS: Allergy data recorded in EHRs were analyzed in a cross-sectional, observational, descriptive study of patients admitted to the hospital from January 1 through June 30, 2011. RESULTS: A total of 15,534 patients were admitted to the hospital during the study period. The rate of inclusion of allergy information in the EHRs was 64.4%. In 2,106 patients an alert was activated to declare an allergy, intolerance, or any other type of adverse reaction. Drugs were the most common responsible agent (74.4%), followed by foods (12.6%) and materials (4.8%). Entries for drug allergy or intolerance were more common in females (64.8%) than males, with a significant statistical difference (P < .01), and increased proportionally with age. Entries for food allergy or intolerance were also more common in females (58.0%) than males (P < .01), but this trend was reversed in the 0- to 15-year-old age group. By contrast, the entries for food allergy or intolerance decreased proportionally with age. In 7,907 cases the EHRs revealed that patients were free of allergies, intolerances, or any other type of adverse reactions. CONCLUSION: Drug allergy was the most frequently reported allergic condition, followed by foods and materials. Allergy alerts vary depending on age and sex. The proper use of a system for allergy alerts included in EHRs provides valuable information about hospitalized patients, contributing to the improvement of clinical practice.