目的 运用数据挖掘的方法检测奥马珠单抗上市后的不良反应信号,为临床安全合理用药提供参考。方法 本研究采用报告比值比法（ROR）和贝叶斯判别可信区间递进神经网络法（BCPNN）对美国FDA不良事件报告系统（FAERS）中2004年第1季度至2023年第2季度的奥马珠单抗相关不良事件（ADE）报告进行数据挖掘和信号检测。结果 通过数据挖掘和信号检测,涉及奥马珠单抗的ADE报告中提取了186,353份报告,涉及45,383例患者。在这些报告中,女性（65.31%）比例远高于男性（24.97%）。主要报告国家为美国（64.93%）和加拿大（11.96%）。报告者中以消费者（41.35%）和医师（36.97%）为主要群体。研究发现了621个ADE阳性信号,涉及25个系统器官分类（SOC）,主要包括呼吸系统、胸部和纵隔疾病（21.29%）以及感染和侵染类疾病（10.91%）。其中,183个信号被评定为高风险信号,其中包括57个新的高风险信号,如血压升高、易醒型失眠和心律失常等。这些发现有助于更全面地了解奥马珠单抗的安全性和潜在风险。结论 在奥马珠单抗的临床应用过程中,除了要注意药品说明中提到的已知不良反应外,还需特别警惕潜在的不良药物事件,如血压升高、心率升高、中间易醒型失眠、体位性心动过速综合征等。

Objective To use data mining method to detect the adverse reaction signal of omalizumab after marketing,and to provide reference for clinical safety and rational drug use．Methods In this study,the report odds ratio method（ROR）and Bayesian confidence propagation neural network（BCPNN）were used to conduct data mining and signal detection for omalizumab-related adverse event（ADE）reports from the FDA Adverse Event Reporting System（FAERS）from the first quarter of 2004 to the second quarter of 2023．Results Through data mining and signal detection,186,353 reports of ADE involving omalizumab were extracted,involving 45,383 patients．Among these reports,the proportion of women（65.31%）was much higher than that of men（24.97%）．The main reporting countries were the United States（64.93%）and Canada（11.96%）．consumers（41.35%）and doctors（36.97%）were the main groups of reporters．The study identified 621 ADE positive signals across 25 system organ classes（SOCs）,including respiratory,chest,and mediastinal diseases（21.29%）and infectious and infectious diseases（10.91%）．Of these,183 signals were assessed as high risk,including 57 new high-risk signals．These findings contribute to a more complete understanding of the safety and potential risks of omalizumab．Conclusions In the clinical application of omalizumab,in addition to the known adverse reactions mentioned in the drug description,special attention should be paid to potential adverse drug events,such as elevated blood pressure,elevated heart rate,intermediate insomnia,and postatic tachycardia syndrome．

目的 探讨老年吸入性肺炎的危险因素,建立风险预测模型,以期降低老年吸入性肺炎的发病率。方法 选取2017年8月28日—2020年 10月30日广州市第一人民医院老年病科住院治疗的老年肺炎患者205例,按照是否发生吸入性肺炎分为吸入性肺炎组和非吸入性肺炎组,对比2组患者的各项指标,分析老年吸入性肺炎的危险因素,建立风险预测模型,采用ROC曲线对模型进行预测效果检验。结果 多因素Logistic回归分析结果显示,脑梗塞、帕金森、留置胃管、长期卧床为老年吸入性肺炎的危险因素(P<0.05)。模型公式为Logit(P)=-2.952+1.221X₂+2.417X₃+2.388X₈+1.683X₁₀。该模型ROC曲线下面积为0.894。结论 本研究中的模型预测效果良好,可为医护人员预测老年患者发生吸入性肺炎的概率,及时采取相应的预见性护理及干预性治疗。

Objective To explore the risk factors of aspiration pneumonia in the elderly and establish the risk prediction model, in order to reduce the incidence of aspiration pneumonia in the elderly. Methods A total of 205 elderly patients with pneumonia who were hospitalized in the department of geriatrics, Guangzhou First People's Hospital from August 28, 2017 to October 30, 2020, were divided into aspiration pneumonia group and non-aspiration pneumonia group according to whether aspiration pneumonia occurred. The indicators of the two groups of patients were compared, the risk factors of aspiration pneumonia in the elderly were analyzed, the risk prediction model was established, and the prediction effect of the model was tested by receiver operating characteristic curve. Results Multivariate Logistic regression analysis showed that cerebral infarction, Parkinson's disease, indwelling nasogastric tube, and being bedridden were risk factors for aspiration pneumonia in elderly patients (P<0.05). The model formula was Logit (P)=-2.952+1.221X₂+2.417X₃+2.388X₈+1.683X₁₀. The area under receiver operating characteristic curve of this model was 0.894. Conclusion The prediction effect of the model in this study was good, which could predict the probability of aspiration pneumonia in elderly patients for medical staff, and to timely take the corresponding predictive care and interventional treatment.

目的 探讨慢性阻塞性肺疾病急性期加重期(AECOPD)患者血清降钙素原(PCT)、白介素6(IL-6)、超敏C反应蛋白(hs-CRP)水平变化及与肺功能的相关性。方法 选择121例COPD急性加重期患者为实验组研究对象,选取同期体检的80例稳定期COPD患者为对照组,比较两组患者血清PCT、IL-6、hs-CRP的差别,并对三者与COPD患者肺功能的相关性进行探讨。结果 实验组患者IL-6、hs-CRP水平显著高于对照组(P＜0.05)。实验组FEV1值、FEV1%显著低于对照组(P＜0.05)。Pearson分析显示,实验组hs-CRP与肺功能指标FEV1%呈负相关关系(r=-1.51,P=0.048)。结论 AECOPD患者的血清炎症因子水平明显高于COPD稳定期患者,血清炎症因子与慢阻肺患者肺功能损伤密切相关。