老年性痴呆患者隐匿性肺炎风险预测模型的构建和验证

 目的 分析老年性痴呆患者隐匿性肺炎的危险因素并构建预测模型。方法 回顾性分析2019年1月—2020年12月安徽医科大学第三附属医院收治的明确诊断为老年性痴呆合并肺部感染患者病历资料，从确诊患者中随机挑选部分患者作为建模组，并根据是否具备隐匿性分为隐匿性肺炎组、非隐匿性肺炎组，其余病例作为验证组。分别采用单因素和logistic回归多因素分析老年痴呆患者发生隐匿性肺炎的危险因素，应用R4.0.3软件构建nomogram图并对模型进行验证。结果 共纳入216例患者。其中148例（隐匿性肺炎75例、非隐匿性肺炎73例）用于建模，68例（隐匿性肺炎37例、非隐匿性肺炎31例）用于验证。糖尿病（OR=2.565，95%CI：1.094~6.015）、重度痴呆（OR=3.079，95%CI：1.116~8.494）、痴呆病程≥10年（OR=5.782，95%CI：2.139~15.627）、年龄≥80岁（OR=2.737，95%CI：1.011~7.413）、长期卧床（OR=4.835，95%CI：1.716~13.625）为痴呆合并隐匿性肺炎的独立危险因素（均P<0.05）。通过该5项危险因素构建预测模型并进行验证，验证结果显示：建模组曲线下面积（AUC）为0.841，验证组AUC为0.756，提示该模型诊断能力良好；Hosmer-Lemeshow检验显示模型拟合优度良好；decision曲线分析显示该模型有较高的获益性。结论 年龄≥80岁、重度痴呆、痴呆病程≥10年、糖尿病、长期卧床是老年性痴呆患者发生隐匿性肺炎的独立危险因素，通过列线图模型个体化可预测老年性痴呆患者发生隐匿性肺炎的概率，从而尽早干预，改善预后。

Drug resistance genes and clinical characteristics of imipenem-resistant Acinetobacter baumannii in a hospital

Objective To analyze carrying status of drug-resistant genes of clinically isolated imipenem-resistant Acinetobacter baumannii (IRAB) in a hospital, provide laboratory basis for prevention and control as well as gui-dance for clinical treatment of HAI. Methods Polymerase chain reaction (PCR) was used to detect carrying status of carbapenem-resistant genes (blaIMP, blaKPC, blaNDM-1, blaOXA-23, blaOXA-50, blaOXA-51, and blaOXA-58), aminoglycoside-resistant genes (ant3"]-Ⅰ, aac6']-Ⅰ, armA) and disinfectant-resistant gene qacE△1 of 26 clinically isolated IRAB strains in this hospital. Results 26 strains of IRAB all carried carbapenem-resistant genes OXA-23 and OXA-51,detection rate was 100%,other carbapenem-resistant genes were not found. The detected rates of aminoglycoside-resistant genes ant (3")-Ⅰ, aac (6')-Ⅰand armA were all 96.15%, the carrying rate of disinfectant-resistant gene qacE△1 was 65.38%. 92.31% of clinically isolated IRAB strains were from sputum of patients. Conclusion The majority of clinically isolated IRAB strains in this hospital carry the same carbapenem-resistant gene and aminoglycoside-resistant gene, it is necessary to strengthen the prevention and control measures of HAI.