Work

Prediction of hereditary angioedema during attacks in patients with recurrent angioedema: Awareness at a glance with the hereditary angioedema prediction score

Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND/AIM: Misdiagnosis of hereditary angioedema (HAE) leads to inappropriate management of the attacks. A scoring system that anticipates diagnosis can be beneficial for clinicians who are unfamiliar with angioedema. This study aims to develop a practical scoring system for use during acute attacks to predict HAE in patients with recurrent angioedema (RAE). METHOD: To predict HAE, nine HAE experts unanimously identified five predictive items (PIs); absence of urticaria, presence of abdominal pain episodes, family history, early onset of attacks and previous unresponsiveness to anti-histaminergic treatments. The researchers questioned 106 patients with HAE and 155 patients with mast cell-mediated angioedema (MMAE) about PIs. A score was attributed to each significant PI based on OR values obtained through logistic regression analysis. The cut-off point for the prediction of HAE and its sensitivity and specificity were determined by ROC curve analysis. RESULTS: In a univariate analysis, all items showed significant differences between HAE and MMAE patients. Regression analysis attributed scores as follows: 23 points for the absence of urticaria, 11 points for the abdominal pain episodes, 9 points for family history, and 53 points for unresponsiveness to antihistaminergic treatments. No score was attributed to early onset of age (p > 0.05). The ROC analysis revealed an area under the curve of 0.990, with a total score of ≥38 demonstrating the best sensitivity (96.4%) and specificity (96.1%). CONCLUSIONS: HAEps is a valuable tool for diagnosing HAE in patients with RAE. A score of 38 or more indicates the possible presence of HAE with substantial sensitivity and specificity.
Language: English
Subfield: Hematology
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,690
OpenAlex ID: W4409502867
FWCI:
Cites: 31
Cited by:
Related to: 10