严重烧伤患者发生ARDS风险预测模型的构建与验证

姚颐; 刘伟; 王盛书; 华天桢; 张广良; 贾皓冉; 马舒洁; 申传安

doi:10.3760/cma.j.cn501225-20260204-00070

严重烧伤患者发生ARDS风险预测模型的构建与验证

doi: 10.3760/cma.j.cn501225-20260204-00070

姚颐^{1, 2},
刘伟^1, ,,
王盛书³,
华天桢¹,
张广良¹,
贾皓冉⁴,
马舒洁⁴,
申传安¹

1.
解放军总医院第四医学中心烧伤整形医学部,北京　100048
2.
解放军医学院,北京　100853
3.
解放军总医院第二医学中心老年医学研究所,衰老及相关疾病研究北京市重点实验室,国家老年疾病临床医学研究中心,北京　100853
4.
南开大学医学院,天津　300350

基金项目:

解放军总医院创新类技术项目 2025CXT017V

详细信息

通讯作者:
刘伟,Email：liuwei1@301hospital.com.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2026-02-04

Construction and validation of a predictive model for the risk of ARDS in severely burned patients

1.
Senior Department of Burns and Plastic Surgery, the Fourth Medical Center of Chinese PLA General Hospital, Beijing 100048, China
2.
PLA Medical School, Beijing 100853, China
3.
Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Institute of Geriatrics, the Second Medical Center, Chinese PLA General Hospital, Beijing 100853, China
4.
Nankai University Medical School, Tianjin 300350, China

Funds:

Innovation Technology Project of Chinese PLA General Hospital 2025CXT017V

More Information

Corresponding author: Liu Wei, Email: liuwei1@301hospital.com.cn

摘要

摘要: 目的构建并验证用于预测严重烧伤患者发生急性呼吸窘迫综合征（ARDS）风险的列线图模型。方法该研究为回顾性队列研究。2015年1月—2025年8月,解放军总医院第四医学中心收治372例符合入选标准的严重烧伤患者,其中男279例、女93例,年龄18~78岁。按照伤后7 d内是否发生ARDS,将患者分为ARDS组及非ARDS组。采用分层随机抽样法,按照7∶3的比例将患者划分为训练集和验证集。训练集中,ARDS组患者35例、非ARDS组患者227例；验证集中,ARDS组患者14例、非ARDS组患者96例。收集患者一般临床资料,包括烧伤总面积、改良Baux指数、烧伤指数、Ⅱ度烧伤面积、Ⅲ度烧伤面积、吸入性损伤程度、入院时是否行机械通气或高流量氧疗、气管切开天数、住院天数、病危病重天数及病死率等；以及入院24 h内与伤后发生ARDS相关的资料,包括白细胞计数、中性粒细胞计数、凝血酶时间及血红蛋白、肌酐、氯、降钙素原、白蛋白、纤维蛋白原（FIB）水平等。筛选训练集患者组间比较差异有统计学意义的变量,并基于最小绝对值压缩和选择算法（LASSO）回归结合权重调整策略进一步筛选特征性变量。进行多因素logistic回归分析确定患者发生ARDS风险的独立预测因子,并据此构建列线图模型。在训练集和验证集中对该模型效能进行验证。结果训练集一般临床资料中,ARDS组患者的烧伤总面积、Ⅲ度烧伤面积均显著大于非ARDS组（P<0.05）,改良Baux指数、烧伤指数、入院时行机械通气或高流量氧疗比例及病死率均显著高于非ARDS组（P<0.05）,吸入性损伤程度显著重于非ARDS组（P<0.05）,气管切开天数、住院天数及病危病重天数均显著多于非ARDS组（P<0.05）,Ⅱ度烧伤面积显著小于非ARDS组（P<0.05）；与伤后发生ARDS相关的资料中,ARDS组患者入院24 h内的白细胞计数、中性粒细胞计数及血红蛋白、肌酐、氯、降钙素原水平均显著高于非ARDS组（P<0.05）,凝血酶时间显著长于非ARDS组（P<0.05）,而白蛋白、FIB水平均显著低于非ARDS组（P<0.05）。LASSO回归分析显示,改良Baux指数、中性粒细胞计数、白蛋白及FIB水平为训练集中262例严重烧伤患者发生ARDS的特征性变量。多因素logistic回归分析显示,改良Baux指数、中性粒细胞计数、白蛋白及FIB水平为训练集中262例严重烧伤患者发生ARDS的独立预测因子（OR分别为1.058、1.147、0.752、0.615,95%CI分别为1.045~1.072、1.092~1.206、0.694~0.814、0.500~0.757,P值均<0.05）。基于前述4个独立预测因子构建了训练集中262例严重烧伤患者发生ARDS风险的列线图模型。受试者操作特征曲线分析显示,该模型在训练集的曲线下面积（AUC）为0.960（95%CI为0.934~0.986）,在验证集的AUC为0.914（95%CI为0.837~0.991）。校准曲线显示,该模型预测的ARDS发生风险与实际观察值高度一致。临床决策曲线分析显示,在阈值概率为17%~78%的范围内,应用该模型进行临床决策所能获得的临床净收益均显著高于对所有患者均干预或对所有患者均不干预的策略。结论构建的包含改良Baux指数、中性粒细胞计数、白蛋白及FIB水平的列线图模型,对严重烧伤患者发生ARDS风险具有良好的预测效能,具备潜在临床辅助决策价值。
- 烧伤 /
- 呼吸窘迫综合征,成人 /
- 回顾性研究 /
- 危险因素 /
- Logistic模型 /
- 列线图
Abstract: Objective To construct and validate a nomogram model for predicting the risk of acute respiratory distress syndrome (ARDS) in severely burned patients. Methods This study was a retrospective cohort study. From January 2015 to August 2025, 372 severely burned patients who met the inclusion criteria were admitted to the Fourth Medical Center of Chinese PLA General Hospital, including 279 males and 93 females, aged 18 to 78 years. According to whether ARDS occurred within 7 days post-injury, patients were divided into ARDS group and non-ARDS group. Stratified random sampling was used to allocate patients into training set and validation set in a ratio of 7∶3. In training set, there were 35 patients in ARDS group and 227 patients in non-ARDS group; in validation set, there were 14 patients in ARDS group and 96 patients in non-ARDS group. General clinical data of the patients were collected, including total burn area, modified Baux score, burn index, partial-thickness burn area, full-thickness burn area, severity of inhalation injury, whether mechanical ventilation or high-flow oxygen therapy performed upon admission, number of days after tracheostomy, length of hospital stay, duration in critical illness, and mortality rate, as well as data related to post-burn ARDS development within 24 hours of admission, including white blood cell count, neutrophil count, thrombin time, and levels of hemoglobin, creatinine, chloride, procalcitonin, albumin, and fibrinogen (FIB). Variables with statistically significant differences between two groups in training set were screened, and characteristic variables were further selected using least absolute shrinkage and selection operator (LASSO) regression combined with a weight adjustment strategy. Multivariate logistic regression analysis was performed to identify independent predictors, based on which a nomogram model was constructed. The performance of the model was validated in both training set and validation set. Results In the general clinical data of training set, patients in ARDS group had significantly larger total burn area and full-thickness burn area (P<0.05), significantly higher modified Baux score, burn index, proportion of patients receiving mechanical ventilation or high-flow oxygen therapy upon admission, and mortality rate (P<0.05), significantly more severe degree of inhalation injury (P<0.05), significantly greater number of days after tracheostomy, length of hospital stay, and duration in critical illness (P<0.05), and significantly smaller partial-thickness burn area (P<0.05) than those in non-ARDS group. With the data related to post-burn ARDS development, patients in ARDS group had significantly higher white blood cell count, neutrophil count, and levels of hemoglobin, creatinine, chloride, and procalcitonin (P<0.05), significantly longer thrombin time (P<0.05), and significantly lower levels of albumin and FIB (P<0.05) than those in non-ARDS group within 24 hours of admission. LASSO regression analysis showed that modified Baux score, neutrophil count, albumin level, and FIB level were the characteristic variables for the development of ARDS in 262 severely burned patients in training set. Multivariate logistic regression analysis revealed that modified Baux score, neutrophil count, albumin level, and FIB level were independent predictors of ARDS in 262 severely burned patients in training set (with ORs of 1.058, 1.147, 0.752, and 0.615, respectively, 95%CIs of 1.045-1.072, 1.092-1.206, 0.694-0.814, and 0.500-0.757, respectively, P values all <0.05). A nomogram model for predicting the risk of ARDS in 262 severely burned patients in training set was constructed based on the above four independent predictors. Receiver operating characteristic curve analysis showed that the model had an area under the curve (AUC) of 0.960 (with 95%CI of 0.934-0.986) in training set and an AUC of 0.914 (with 95%CI of 0.837-0.991) in validation set. The calibration curve showed that the risk of ARDS predicted by the model was in high agreement with the actual observed values. Clinical decision curve analysis showed that within the threshold probability range of 17% to 78%, the clinical net benefit obtained by applying this model for clinical decision-making was significantly higher than that of the strategies of intervening in all patients or intervening in none. Conclusions The constructed nomogram model incorporating the modified Baux score, neutrophil count, albumin level, and FIB level demonstrates good predictive performance for the risk of ARDS in severely burned patients and holds potential value for clinical decision-making.
- Burns /
- Respiratory distress syndrome, adult /
- Retrospective studies /
- Risk factors /
- Logistic models /
- Nomograms
姚颐：数据收集、统计分析、论文撰写；刘伟：研究设计、数据质控、临床指标把关、审读和修订、监督指导；王盛书：数据分析指导,文章审读、修改；华天桢：数据整理、文章审读；张广良、贾皓冉、马舒洁：数据收集、整理,论文图表制作；申传安：文章审读和把关、监督指导

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图 1 训练集中262例严重烧伤患者各变量的最小绝对值压缩和选择算法的系数路径图及交叉验证图。1A.路径图；1B.交叉验证图

注：图1A中λ为调优参数,随着正则化参数λ增大,各变量回归系数被压缩直至归零并最终被剔除；不同颜色线条代表不同变量的压缩轨迹,在变量数收缩到4时,从上至下的曲线依次代表改良Baux指数、中性粒细胞计数、纤维蛋白原及白蛋白水平；图1B中实线表示交叉验证误差（二项偏差）随正则化参数λ（对数尺度）的变化,用于平衡模型拟合优度与复杂度,阴影区域表示交叉验证误差的一个标准差范围；右侧虚线对应最小交叉验证误差λ_min,左侧虚线对应最小误差在一个标准差范围内的最大λ值λ_1se；本研究采用λ_1se以获得更简约的模型

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图 2 训练集中262例严重烧伤患者发生ARDS风险的列线图模型

注：ARDS为急性呼吸窘迫综合征；使用该列线图模型时,首先在相应变量的刻度轴上确定每例患者各指标取值所对应的分值,然后将各项分值相加得到总得分,最后在总得分轴上找到对应的ARDS发生风险

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图 3 训练集中262例严重烧伤患者发生急性呼吸窘迫综合征风险的列线图模型验证与评估。3A.训练集与验证集的受试者操作特征曲线；3B.训练集的校准曲线；3C.训练集与验证集的临床决策曲线

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Table 1. 训练集中2组严重烧伤患者基线资料比较

组别	例数	性别（例）		年龄[岁, M（Q₁,Q₃）]	身高[m, M（Q₁,Q₃）]	体重[kg, M（Q₁,Q₃）]	身体质量指数[kg/m²,M（Q₁,Q₃）]
组别	例数	男	女	年龄[岁, M（Q₁,Q₃）]	身高[m, M（Q₁,Q₃）]	体重[kg, M（Q₁,Q₃）]	身体质量指数[kg/m²,M（Q₁,Q₃）]
ARDS组	35	6	29	44.0（34.0,54.0）	1.7（1.7,1.7）	75.0（68.0,80.0）	26.0（23.0,28.4）
非ARDS组	227	52	175	41.0（31.0,51.0）	1.7（1.7,1.8）	72.0（61.0,80.0）	24.7（22.2,27.5）
统计量值		χ²=0.298		Z=-1.317	Z=0.079	Z=-0.678	Z=-1.059
P值		0.585		0.188	0.938	0.498	0.290
注：ARDS为急性呼吸窘迫综合征

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Table 2. 训练集中2组严重烧伤患者一般临床资料比较

组别	例数	致伤环境（例）		吸入性损伤程度（例）				入院时行机械通气或高流量氧疗（例）		死亡（例）		Ⅱ度烧伤面积[%TBSA,M（Q₁,Q₃）]	Ⅲ度烧伤面积[%TBSA,M（Q₁,Q₃）]
组别	例数	密闭	开放	无	轻度	中度	重度	是	否	是	否	Ⅱ度烧伤面积[%TBSA,M（Q₁,Q₃）]	Ⅲ度烧伤面积[%TBSA,M（Q₁,Q₃）]
ARDS组	35	18	17	2	6	9	18	12	23	11	24	10.0（5.0,30.0）	45.0（22.0,85.0）
非ARDS组	227	122	105	104	86	31	6	4	223	4	223	23.0（15.0,30.0）	20.0（10.0,40.0）
统计量值		χ²=0.005		—				—		—		Z=3.623	Z=-4.427
P值		0.941		<0.001				<0.001		<0.001		0.001	<0.001
注：ARDS为急性呼吸窘迫综合征,TBSA为体表总面积；“—”表示无此统计量值

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Table 3. 训练集中2组严重烧伤患者血常规、凝血指标、血生化指标比较[M（Q₁,Q₃）]

组别	例数	血常规				凝血指标
组别	例数	白细胞计数（×10⁹/L）	淋巴细胞计数（×10⁹/L）	中性粒细胞计数（×10⁹/L）	血红蛋白水平（g/L）	INR	纤维蛋白原水平（g/L）	凝血酶时间（s）
ARDS组	35	26.6（15.8,33.6）	1.0（0.7,1.7）	22.3（13.4,30.3）	170.0（139.0,190.0）	1.1（1.0,1.4）	2.9（2.3,3.6）	14.6（13.6,15.7）
非ARDS组	227	11.2（8.4,16.0）	1.1（0.8,1.4）	9.2（6.8,13.4）	129.0（112.0,153.0）	1.1（1.0,1.2）	4.5（3.3,6.2）	13.0（12.4,13.9）
Z值		-6.154	-0.866	-6.277	-4.302	-1.786	5.291	-5.272
P值		<0.001	0.387	<0.001	<0.001	0.074	<0.001	<0.001
注：ARDS为急性呼吸窘迫综合征,INR为国际标准化比值,ALT为丙氨酸氨基转移酶,NT-proBNP为N末端B型利钠肽前体；血常规、凝血指标和血生化指标均为入院24 h内的首次检验结果或记录值

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Table 4. 2组严重烧伤患者中训练集与验证集患者的改良Baux指数、中性粒细胞计数、白蛋白与纤维蛋白原水平比较[M(Q₁,Q₃)]

组别与分类	例数	改良Baux指数	中性粒细胞计数（×10⁹/L）	白蛋白水平（g/L）	纤维蛋白原水平（g/L）
ARDS组
训练集	35	146.0（124.0,159.0）	22.3（13.4,30.3）	27.5（24.0,30.8）	2.9（2.3,3.6）
验证集	14	143.0（128.0,157.0）	16.4（11.4,28.0）	27.2（20.6,32.5）	2.9（2.4,4.5）
非ARDS组
训练集	227	101.0（79.0,124.0）	9.2（6.8,13.4）	33.4（30.3,37.1）	4.5（3.3,6.2）
验证集	96	94.5（80.5,119.5）	9.9（6.8,13.6）	35.5（31.3,37.9）	4.4（3.1,6.3）
P₁值		0.825	0.424	0.938	0.757
P₂值		0.630	0.509	0.054	0.342
注：P₁值为ARDS组2个子集各指标比较所得,P₂值为非ARDS组2个子集各指标比较所得