This study sought to investigate adverse drug event(ADE)signals associated with eltrombopag use in pediatric patients aged 0–18 years,utilizing data from the U.S.Food and Drug Administration Adverse Event Reporting S...This study sought to investigate adverse drug event(ADE)signals associated with eltrombopag use in pediatric patients aged 0–18 years,utilizing data from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS).By analyzing this extensive pharmacovigilance database,the study aimed to offer meaningful insights for improving the clinical safety of eltrombopag in children.Data covering eltrombopag-related ADEs from Q12004 to Q42023 were extracted from FAERS,and signal detection was conducted using both the reporting odds ratio(ROR)and proportional reporting ratio(PRR)methods.ADEs were categorized based on the System Organ Class(SOC)classification in MedDRA version 25.0.A total of 582 reports involving pediatric patients receiving eltrombopag were identified,encompassing 21 SOC categories.The analysis revealed that,in addition to the known ADEs listed in the drug label,clinicians should remain vigilant for potential off-label ADE signals.These included abnormal platelet counts,thrombocytosis,antiphospholipid syndrome,myelofibrosis,reduced serum iron levels,myelodysplastic syndrome,hepatic infections,and other related conditions.Given these findings,it is strongly recommended that serum iron and ferritin levels should be routinely monitored in pediatric patients undergoing eltrombopag therapy,particularly during long-term treatment.Such proactive surveillance may help prevent the onset of iron deficiency anemia and enhance overall treatment safety.展开更多
For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to p...For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.展开更多
文摘This study sought to investigate adverse drug event(ADE)signals associated with eltrombopag use in pediatric patients aged 0–18 years,utilizing data from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS).By analyzing this extensive pharmacovigilance database,the study aimed to offer meaningful insights for improving the clinical safety of eltrombopag in children.Data covering eltrombopag-related ADEs from Q12004 to Q42023 were extracted from FAERS,and signal detection was conducted using both the reporting odds ratio(ROR)and proportional reporting ratio(PRR)methods.ADEs were categorized based on the System Organ Class(SOC)classification in MedDRA version 25.0.A total of 582 reports involving pediatric patients receiving eltrombopag were identified,encompassing 21 SOC categories.The analysis revealed that,in addition to the known ADEs listed in the drug label,clinicians should remain vigilant for potential off-label ADE signals.These included abnormal platelet counts,thrombocytosis,antiphospholipid syndrome,myelofibrosis,reduced serum iron levels,myelodysplastic syndrome,hepatic infections,and other related conditions.Given these findings,it is strongly recommended that serum iron and ferritin levels should be routinely monitored in pediatric patients undergoing eltrombopag therapy,particularly during long-term treatment.Such proactive surveillance may help prevent the onset of iron deficiency anemia and enhance overall treatment safety.
基金supported by the National Natural Science Foundation of China(61371172)the International S&T Cooperation Program of China(2015DFR10220)+1 种基金the Ocean Engineering Project of National Key Laboratory Foundation(1213)the Fundamental Research Funds for the Central Universities(HEUCF1608)
文摘For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.
