Lee Youn-Jung, Jang Hee Jung
Department of Nursing, Hallym Polytechnic University, Chuncheon 24210, Republic of Korea.
School of Nursing, Research Institute of Nursing Science, Hallym University, Chuncheon 24252, Republic of Korea.
Healthcare (Basel). 2023 Nov 22;11(23):3015. doi: 10.3390/healthcare11233015.
The purpose of this study was to develop a prediction model for stroke-associated pneumonia (SAP) based on risk factors for SAP and to suggest nursing interventions to prevent SAP. In addition, a nomogram was developed to enhance its utility in nursing practice. The retrospective cohort study included 551 patients hospitalized for acute ischemic stroke at a university hospital in South Korea. Data were collected through a structured questionnaire and a review of the electronic medical record (EMR). In the development of a predictive model for SAP, multivariate logistic regression analysis showed that independent risk factors for SAP were age ≥ 65 years, National Institute of Health Stroke Scale (NIHSS) score ≥ 7, nasogastric tube feeding, and C-reactive protein (CRP) ≥ 5.0 mg/dL. The logit model was used to construct the SAP prediction nomogram, and the area under the curve (AUC) of the nomogram was 0.94. Furthermore, the slope of the calibration plot was close to the 45-degree line, indicating that the developed nomogram may be useful for predicting SAP. It is necessary to monitor the age, NIHSS score, nasogastric tube feeding status, and CRP level of stroke patients and identify high-risk groups using the developed nomogram to provide active nursing interventions to prevent SAP.
本研究的目的是基于卒中相关性肺炎（SAP）的危险因素开发一种SAP预测模型，并提出预防SAP的护理干预措施。此外，还开发了一种列线图以提高其在护理实践中的实用性。这项回顾性队列研究纳入了韩国一家大学医院551例因急性缺血性卒中住院的患者。数据通过结构化问卷和电子病历（EMR）回顾收集。在开发SAP预测模型时，多因素逻辑回归分析显示，SAP的独立危险因素为年龄≥65岁、美国国立卫生研究院卒中量表（NIHSS）评分≥7分、鼻饲以及C反应蛋白（CRP）≥5.0mg/dL。采用logit模型构建SAP预测列线图，该列线图的曲线下面积（AUC）为0.94。此外，校准图的斜率接近45度线，表明所开发的列线图可能有助于预测SAP。有必要监测卒中患者的年龄、NIHSS评分、鼻饲状态和CRP水平，并使用所开发的列线图识别高危人群，以提供积极的护理干预措施来预防SAP。
