Sun Kang, Li Wangping, Li Yu, Li Guangyu, Pan Lei, Jin Faguang
Department of Respiratory and Critical Care Medicine, Tang Du Hospital, Air Force Military Medical University, Xi'an, Shaanxi Province, 710038, People's Republic of China.
Department of Respiratory and Critical Care Medicine, The 989th Hospital of Joint Support Force of Chinese People's Liberation Army, Luoyang, Henan Province, 471003, People's Republic of China.
Infect Drug Resist. 2022 Mar 15;15:1055-1066. doi: 10.2147/IDR.S356764. eCollection 2022.
The prognosis of ABA-HAP patients is very poor. This study aimed to develop a scoring model to predict ABA-HAP in patients with GNB-HAP.
A single center retrospective cohort study was performed among patients with HAP caused by GNB in our hospital during January 2019 to June 2019 (the derivation cohort, DC). The variables were assessed on the day when qualified respiratory specimens were obtained. A prediction score was formulated by using independent risk factors obtained from logistic regression analysis. It was prospectively validated with a subsequent cohort of GNB-HAP patients admitted to our hospital during July 2019 to Dec 2019 (the validation cohort, VC).
The final logistic regression model of DC included the following variables: transferred from other hospitals (3 points); blood purification (3 points); risk for aspiration (4 points); immunocompromised (3 points); pulmonary interstitial fibrosis (3 points); pleural effusion (1 points); heart failure (3 points); encephalitis (5 points); increased monocyte count (2 points); and increased neutrophils count (2 points). The AUROC of the scoring model was 0.845 (95% CI, 0.796 ~ 0.895) in DC and 0.807 (95% CI, 0.759 ~ 0.856) in VC. The scoring model clearly differentiated the low-risk patients (the score < 8 points), moderate-risk patients (8 ≤ the score < 12 points) and high-risk patients (the score ≥ 12 points), both in DC ( < 0.001) and in VC ( < 0.001).
This simple scoring model could predict ABA-HAP with high predictive value and help clinicians to choose appropriate empirical antibiotic therapy.
产酸克雷伯菌所致医院获得性肺炎（ABA-HAP）患者的预后很差。本研究旨在建立一个评分模型来预测革兰阴性菌所致医院获得性肺炎（GNB-HAP）患者发生ABA-HAP的风险。
对2019年1月至2019年6月在我院住院的GNB-HAP患者进行单中心回顾性队列研究（推导队列，DC）。在获取合格呼吸道标本当天评估各项变量。通过逻辑回归分析得出的独立危险因素制定预测评分。随后对2019年7月至2019年12月入住我院的GNB-HAP患者队列（验证队列，VC）进行前瞻性验证。
DC的最终逻辑回归模型包括以下变量：从其他医院转入（3分）；血液净化（3分）；误吸风险（4分）；免疫功能低下（3分）；肺间质纤维化（3分）；胸腔积液（1分）；心力衰竭（3分）；脑炎（5分）；单核细胞计数增加（2分）；中性粒细胞计数增加（2分）。该评分模型在DC中的曲线下面积（AUROC）为0.845（95%可信区间，0.7960.895），在VC中的AUROC为0.807（95%可信区间，0.7590.856）。该评分模型在DC（<0.001）和VC（<0.001）中均能清晰区分低风险患者（评分<8分）、中度风险患者（8≤评分<12分）和高风险患者（评分≥12分）。
这个简单的评分模型对ABA-HAP具有较高的预测价值，有助于临床医生选择合适的经验性抗生素治疗方案。
