Zhang Shumei, Wang Hongyao, Lin Shuting, Zhang Yihuang, Lin Yingbin, Fang Wenhua, Chen Yue
Department of Neurosurgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Department of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Front Pediatr. 2025 Aug 6;13:1638012. doi: 10.3389/fped.2025.1638012. eCollection 2025.
Pneumonia is a common complication in children undergoing neurosurgery, leading to prolonged length of stay as well as increased hospital expenses. A prediction model for pneumonia in children undergoing neurosurgery based on common laboratory indicators is an effective clinical measure for early intervention in high-risk patients. In this study, we proposed to construct a pneumonia prediction model for children undergoing neurosurgery by selecting routine baseline characteristics and laboratory indicators.
This study retrospectively collected children admitted from January 2021 to April 2025. The data collected included common clinical baseline data and regular laboratory test results. Variables were filtered by multivariate regression and constructed a prediction model.
Screening revealed that whether emergency admission, whether surgical treatment, type of disease, serum creatinine level and neutrophil count were statistically different indicators. A prediction model was constructed based on the above indicators, and the C-statistic values of the model were 0.835 (test set, 95% CI: 0.7692-0.9006) and 0.716 (validation set, 95% CI: 0.5803-0.8509), which were satisfactory. And a clinically usable nomogram based on the above model was constructed.
Hospital-acquired pneumonia is a common complication in children undergoing neurosurgery and may be related to a variety of factors. Using basic clinical baseline data and laboratory data to monitor and detect high-risk patients in the early stages of the disease is a useful clinical attempt that deserves further exploration.
肺炎是神经外科手术患儿常见的并发症，会导致住院时间延长以及住院费用增加。基于常见实验室指标构建神经外科手术患儿肺炎预测模型，是对高危患者进行早期干预的有效临床措施。在本研究中，我们提议通过选择常规基线特征和实验室指标，构建神经外科手术患儿肺炎预测模型。
本研究回顾性收集了2021年1月至2025年4月收治的患儿。收集的数据包括常见临床基线数据和常规实验室检查结果。通过多因素回归对变量进行筛选并构建预测模型。
筛选发现急诊入院与否、是否接受手术治疗、疾病类型、血清肌酐水平和中性粒细胞计数是有统计学差异的指标。基于上述指标构建了预测模型，该模型的C统计量值在测试集为0.835（95%CI：0.7692 - 0.9006），在验证集为0.716（95%CI：0.5803 - 0.8509），结果令人满意。并基于上述模型构建了临床可用的列线图。
医院获得性肺炎是神经外科手术患儿常见的并发症，可能与多种因素有关。利用基本临床基线数据和实验室数据在疾病早期监测和发现高危患者是一项有益的临床尝试，值得进一步探索。
