【摘要】 目的 分析儿童社区获得性肺炎（CAP）患儿住院期间由轻症转为重症的危险因素，并构建其风险预测模型。方法 回顾性选取2022年1月至2024年12月福建医科大学附属南平第一医院儿科收治的475例CAP患儿临床资料，分析CAP患儿病原分布特点，并根据患儿入院后病情分为轻症组（337例）与重症组（138例），比较两组中性粒细胞/淋巴细胞比值（NLR）、25-羟基维生素D3[25-(OH)D3]、儿童早期预警评分（PEWS）等一般资料，使用多因素Logistic回归分析评估CAP患儿重症的影响因素，使用列线图构建CAP患儿重症的风险预测模型，Bootstrap法重复抽样100次行内部验证，以校准曲线评估模型的预测价值。结果 475例CAP患儿病原学检查阳性率为54.74%(260/475)。以单种病原体感染居多（76.54%,199/260），其中肺炎支原体感染最常见（52.26%,104/199）；混合病原体感染占比23.46%(61/260)。475例CAP患儿入院后进展为重症138例（29.05%），重症组患儿细菌+病毒检出率及细菌+肺炎支原体检出率、中性粒细胞占比、NLR、C反应蛋白及PEWS评分均高于轻症组（P<0.05），淋巴细胞占比、白蛋白、25-(OH)D3均低于轻症组（P<0.05）。多因素Logistic向前逐步回归分析显示，NLR[OR=2.046,95%CI(1.200～3.490),P<0.05]、C反应蛋白[OR=1.516,95%CI(1.260～1.823),P<0.05]及PEWS评分[OR=235.077,95%CI(29.282～1 887.184),P<0.05]均为CAP患儿重症的独立危险因素，白蛋白[OR=0.846,95%CI(0.763～0.937),P<0.05]及25-(OH)D3[OR=0.757,95%CI(0.666～0.862),P<0.05]则为独立保护因素。以上述5项独立影响因素构建CAP患儿重症的风险列线图预警模型，内部验证显示校准曲线趋近于理想曲线。结论 CAP患儿以单种病原体感染居多，入院早期高NLR、C反应蛋白及PEWS评分可能增加患儿进展为重症风险，高白蛋白及高25-(OH)D3可能降低病情进展风险，5项因素构建的列线图模型对预测重症CAP有利，可辅助临床尽早诊疗。更多还原

【Abstract】 Objective To analyze the risk factors for progression of children with community-acquired pneumonia(CAP) from mild to severe during hospitalization, and to construct its risk prediction model. Methods The clinical data of 475 children with CAP admitted from January 2022 to December 2024 Department of Pediatrics, Nanping First Hospital, Fujian Medical University were retrospectively analyzed. The distribution characteristics of pathogens in children with CAP were analyzed, and the children were divided into mild group(337 children) and severe group(138 children) according to their disease status after admission. General clinical data, including neutrophil/lymphocyte ratio(NLR), 25-hydroxyvitamin D3 [25-(OH)D3], and pediatric early warning score(PEWS) were compared between the two groups. Multivariate Logistic regression analysis was used to evaluate the influencing factors of severe CAP in children. The nomogram was used to construct a risk prediction model for severe CAP in children. The bootstrap method was used for internal validation, repeatedly sampling 100 times, to evaluate the predictive value of the model using a calibration curve. Results The positive rate of pathogenic examination in 475 children with CAP was 54.74%(260/475). Single pathogen infection predominated(76.54%, 199/260) with Mycoplasma pneumoniae being most common(52.26%, 104/199). Mixed pathogen infection accounted for 23.46%(61/260). Of the 475 children with CAP, 138(29.05%) progressed to severe disease after admission. In the severe group, the detection rate of bacteria+virus, detection rate of bacteria+Mycoplasma pneumoniae, neutrophil proportion, NLR, C-reactive protein(CRP) level and PEWS score were higher than those in the mild group(P<0.05), while lymphocyte proportion, albumin level, and 25-(OH)D3 level were lower than those in the mild group(P<0.05). Multivariate logistic forward stepwise regression analysis showed that NLR(OR=2.046, 95%CI: 1.200-3.490, P<0.05), CRP(OR=1.516, 95%CI: 1.260-1.823, P<0.05), and PEWS score(OR=235.077, 95%CI: 29.282-1 887.184, P<0.05) were independent risk factors for severe CAP in children, and albumin(OR=0.846, 95%CI: 0.763-0.937, P<0.05) and 25-(OH)D3(OR=0.757, 95%CI: 0.666-0.862, P<0.05) were independent protective factors. A risk nomogram early warning model for severe CAP in children was constructed using these five independent factors. Internal validation showed that the calibration curve approached the ideal curve. Conclusion Children with CAP are mostly infected with a single pathogen. High NLR, C-reactive protein levels, and PEWS score early in hospitalization may increase the risk of progression to severe CAP, while high albumin and high 25-(OH)D3 levels may reduce this risk. The five-factor nomogram model facilitates early prediction of severe CAP, aiding timely clinical intervention.更多还原