Epidemiological characteristics of nosocomial infection in hospitalized children with burns and the establishment and verification of a risk prediction model
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摘要:
目的 分析住院烧伤患儿发生医院感染的流行病学特征，并筛选其独立危险因素，在此基础上建立风险预测模型并进行评估。 方法 采用回顾性队列研究方法。2010年5月—2023年4月，空军军医大学第一附属医院收治417例符合入选标准的烧伤患儿，其中男248例、女169例，年龄≤14岁。统计患儿检出病原菌构成及来源分布。根据是否发生医院感染，将患儿分为感染组（216例）和未感染组（201例），统计2组患儿性别、年龄、烧伤总面积、是否存在Ⅲ度烧伤、致伤原因、致伤季节等一般资料，以及是否存在入院时血清白蛋白水平异常、延迟复苏、合并吸入性损伤与入院后早期休克、气管切开、入住重症监护病房、深静脉置管等情况和入院后手术次数多少（>2次为多，≤2次为少）、留置导尿管天数、住院天数。按照7∶3的比例将患儿分为建模组（291例）和验证组（126例），同前统计2组患儿资料。对前述数据行Mann-Whitney U 检验、 χ 2检验和Fisher确切概率法检验。通过最小绝对值压缩和选择算法（LASSO）回归分析缩减建模组患儿发生医院感染的危险因素，采用多因素logistic回归分析对前述筛选出的危险因素作进一步筛选，根据进一步筛选出的独立危险因素绘制列线图预测模型。采用Bootstrap法对前述预测模型进行内部验证，绘制建模组和验证组预测模型的受试者操作特征（ROC）曲线、校准曲线和临床决策曲线，分别评估其区分度、校准度和临床实用性。 结果 共检出245株病原菌，以金黄色葡萄球菌（101株，占41%）、铜绿假单胞菌（54株，占22%）、鲍曼不动杆菌（33株，占13%）为主，来源于创面分泌物的病原菌（211株，占86%）最多，其次是血液（10株，占4%）和痰液（5株，占2%）。感染组与未感染组患儿烧伤总面积、留置导尿管天数、住院天数以及是否存在Ⅲ度烧伤、合并吸入性损伤、深静脉置管与手术次数多少，差异均有统计学意义（ Z值分别为-2.32、-3.29、-3.85， χ 2值分别为26.36、7.03、10.13、10.53， P<0.05）；2组患者致伤原因比较，差异有统计学意义（ P<0.05）。建模组和验证组患儿的各临床特征均相近（ P>0.05）。LASSO回归分析获得的6个危险因素分别为Ⅲ度烧伤、血清白蛋白水平异常、深静脉置管、多次手术、留置导尿管天数和住院天数；多因素logistic回归分析结果显示，Ⅲ度烧伤、深静脉置管、血清白蛋白水平异常和多次手术均是291例住院烧伤患儿发生医院感染的独立危险因素（比值比分别为2.27、2.66、4.08、2.92，95%置信区间分别为1.22~4.21、1.03~6.87、1.07~15.49、1.15~7.42， P<0.05）。预测模型的ROC曲线显示，建模组和验证组的ROC曲线下面积分别为0.81（95%置信区间为0.78~0.84）和0.81（95%置信区间为0.76~0.85）；校准曲线显示，建模组和验证组的预测模型校准曲线均在理想曲线附近；临床决策曲线显示，建模组和验证组的预测模型阈值概率分别在5%~70%和1%~46%范围内。 结论 烧伤患儿感染的主要病原菌是来自于创面分泌物的金黄色葡萄球菌。基于独立危险因素——Ⅲ度烧伤、血清白蛋白水平异常、深静脉置管和多次手术所构建的列线图预测模型具有较好的准确性，可方便地用于住院烧伤患儿发生医院感染的预测。 Abstract:Objective To analyze the epidemiological characteristics of hospitalized children with burns who developed nosocomial infection, and screen their independent risk factors, based on which, a risk prediction model was established and evaluated. Methods A retrospective cohort study was conducted. From May 2010 to April 2023, 417 children with burns who met the inclusion criteria were admitted to the First Affiliated Hospital of the Air Force Medical University, including 248 males and 169 females, aged ≤14 years. Statistics on the composition and source distribution of pathogenic bacteria in children were detected. According to the occurrence of nosocomial infection, the children were divided into infected group (216 cases) and uninfected group (201 cases), and the children gender, age, total area of burns, presence of full-thickness burns, cause of the injury, and season of the injury of the children in the 2 groups were collected, as well as presence of an abnormal serum albumin level, delayed resuscitation, combination of inhalation injury at admission, and early shock, tracheotomy, admission to the intensive care unit, and deep venous catheterization after post-hospitalization, and more or less times (>2 times being more and ≤2 times being less) of surgeries, indwelling catheter days, and length of hospitalization stay on post-hospitalization. The burned children were divided into modeling group (291 cases) and validation group (126 cases) according to the ratio of 7∶3, and the data of the 2 groups were recorded as before. Data were statistically analyzed with Mann-Whitney U test, chi-square test, and Fisher's exact probability test. The least absolute value selection and shrinkage operator (LASSO) regression analysis was used to reduce the risk factors of nosocomial infection in the children in modeling group. Multivariate logistic regression analysis was used to further screen the above screened risk factors, and the nomogram prediction model was drawn based on the further screened independent risk factors. The Bootstrap method was used for internal validation of the aforementioned predictive models, and the receiver operator characteristic (ROC) curves, calibration curves, and clinical decision curves of the predictive models were plotted in modeling group and validation group in order to assess its discriminative power, calibration, and clinical utility, respectively. Results A total of 245 strains of pathogenic bacteria were detected, with Staphylococcus aureus (101 strains, accounting for 41%), Pseudomonas aeruginosa (54 strains, accounting for 22%), and Acinetobacter baumannii (33 strains, accounting for 13%) dominating, and the wound secretions were the most frequent source of pathogenic bacteria (211 strains, accounting for 86%), followed by blood (10 strains, accounting for 4%), and sputum (5 strains, accounting for 2%). There were statistically significant differences between infected group and non-infected group in the total burn area, indwelling catheter days, length of hospitalization stay, presence of full-thickness burns, combined with inhalation injury, and deep vein catheterization, and more or less times of surgeries (with Zvalues of -2.32, -3.29, and -3.85, respectively, with χ 2 values of 26.36, 7.03, 10.13, and 10.53, respectively, P<0.05); there was statistically significant difference in cause of the injury between the two groups ( P<0.05). All clinical characteristics of children with burns in the modeling and validation groups were similar ( P>0.05). The six risk factors obtained from the LASSO regression analysis were full-thickness burns, deep vein catheterization, abnormal serum albumin level, multiple surgeries, indwelling catheter days, and length of hospitalization stay; the multivariate logistic regression analysis showed that full-thickness burns, abnormal serum albumin level, deep vein catheterization, and multiple surgeries were the independent risk factors for the occurrence of nosocomial infection in burned children (with odds ratios of 2.27, 2.66, 4.08, and 2.92, respectively, with 95% confidence intervals of 1.22-4.21, 1.03-6.87, 1.07-15.49, and 1.15-7.42, respectively, P<0.05). The ROC curves of the prediction models showed that, the areas under the ROC curves of the modeling and validation groups were 0.81 (with 95% confidence interval of 0.78-0.84) and 0.81 (with 95% confidence interval of 0.76-0.85), respectively; the calibration curves showed that, the calibration curves of the prediction models of modeling and validation groups were around the ideal curves; the clinical decision curves showed that, the threshold probability values of the prediction models in modeling and validation groups were in the ranges of 5% to 70% and 1% to 46%, respectively. Conclusions The main pathogen of infection in children with burns is Staphylococcus aureus from wound secretions. A nomogram risk prediction model constructed based on independent risk factors such as full-thickness burns, abnormal serum albumin level, deep venous catheterization, and multiple surgeries has good accuracy and can be easily used to predict the occurrence of nosocomial infections in hospitalized children with burns. -
Key words:
- Burns /
- Child /
- Nomograms /
- Inflammation /
- Cross infection /
- Risk factors
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1 291例住院烧伤患儿发生医院感染的LASSO回归分析。1A.LASSO回归模型筛选变量过程图；1B.LASSO回归交叉验证曲线，最小λ值处对应6个非零系数变量，分别为Ⅲ度烧伤、血清白蛋白异常、深静脉置管、多次手术、留置导尿管天数和住院天数，这些变量即为烧伤患儿发生医院感染的危险因素
注：λ为惩罚系数；图1A、1B上方横坐标为最小绝对值压缩和选择算法（LASSO）回归中系数非零的变量数，不同颜色曲线代表不同变量，从上至下分别为是否存在深静脉置管、是否存在Ⅲ度烧伤、留置导尿管天数、住院天数、血清白蛋白是否异常、年龄、性别、烧伤总面积、致伤原因、致伤季节、是否行延迟复苏、是否存在早期休克、是否合并吸入性损伤、有无气管切开、是否入住重症监护病房、手术次数多少（手术次数≤2次为少，>2次为多）；图1A和图1B中左右2条纵向虚线均分别代表均方差最小时的λ值和最小λ值的一个标准误，红点为目标参量均值
3 建模组（291例）和验证组（126例）住院烧伤患儿发生医院感染风险预测模型的评估。3A、3B、3C.分别为建模组的受试者操作特征曲线、校准曲线和临床决策曲线；3D、3E、3F.分别为验证组的受试者操作特征曲线、校准曲线和临床决策曲线
表1 感染组和未感染组住院烧伤患儿临床特征比较
表1. Comparison of clinical characteristics of hospitalized children with burns in infected and uninfected groups
组别 例数 性别（例） 年龄（例） 烧伤总面积［%TBSA， M（ Q 1， Q 3）］ Ⅲ度烧伤（例） 致伤原因（例） 致伤季节（例） 入院后早期休克（例） 男 女 0~1岁 2~3岁 4~7岁 8~14岁 是 否 火焰 热液 电 其他 春 夏 秋 冬 是 否 感染组 216 131 85 73 81 29 33 20（10，30） 191 25 46 160 6 4 64 47 38 67 149 67 未感染组 201 117 84 85 63 35 18 25（13，35） 135 66 23 175 1 2 59 45 28 69 123 78 统计量值 χ 2=0.17 χ 2=7.61 Z=-2.32 χ 2=26.36 — χ 2=1.25 χ 2=2.45 P值 0.684 0.055 0.020 0.001 0.004 0.74 0.117 注：TBSA为体表总面积，ICU为重症监护病房；致伤原因中的其他指蒸气、炽热金属，“—”表示无此项，血清白蛋白水平指入院时指标，手术次数≤2次为少，>2次为多 
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表2 建模组和验证组住院烧伤患儿临床特征比较
表2. Comparison of clinical characteristics of hospitalized children with burns in modeling and validation groups
组别 例数 性别（例） 年龄（例） 烧伤总面积［%TBSA， M（ Q 1， Q 3）］ Ⅲ度烧伤（例） 致伤原因（例） 致伤季节（例） 早期休克（例） 男 女 0~1岁 2~3岁 4~7岁 8~14岁 是 否 火焰 热液 电 其他 春 夏 秋 冬 是 否 建模组 291 171 120 108 99 49 35 20（12，34） 230 61 46 235 5 5 83 71 43 94 193 98 验证组 126 77 49 50 45 15 16 20（10，35） 96 30 23 100 2 1 40 21 23 42 79 47 统计量值 χ 2=0.12 χ 2=1.65 Z=-0.68 χ 2=0.27 — χ 2=3.39 χ 2=0.36 P值 0.734 0.647 0.498 0.605 0.903 0.335 0.547 注：TBSA为体表总面积，ICU为重症监护病房；致伤原因中的其他指蒸气、炽热金属，“—”表示无此项，血清白蛋白水平指入院时指标，手术次数≤2次为少，>2次为多
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[1] ErdoğanH, SencanA. Analysis of the epidemiological features and treatment results of burn injuries in a burn center in Turkey[J]. J Burn Care Res, 2023:irad119. DOI: 10.1093/jbcr/irad119. [2] 潘选良, 朱志康, 沈涛, 等. 特重度烧伤患者发生脓毒症与死亡的流行病学特点和危险因素[J].中华烧伤与创面修复杂志,2023,39(6):558-564. DOI: 10.3760/cma.j.cn501225-20220806-00336. [3] 潘艳艳, 徐思达, 范友芬, 等. 特重度烧伤患者早期肠内营养不耐受的危险因素分析[J].中华烧伤杂志,2021,37(9):831-838. DOI: 10.3760/cma.j.cn501120-20210511-00180. [4] ChenK, LiuJ, WangX, et al. Epidemiological characteristics of paediatric burn patients in China from 2016 to 2019: a retrospective study[J]. BMJ Paediatr Open, 2023, 7(1):e001796. DOI: 10.1136/bmjpo-2022-001796. [5] YaoY, MaL, ChenL. Characteristics of injury mechanisms in children and differences between urban and rural areas in central China[J]. Eur J Trauma Emerg Surg, 2023,DOI: 10.1007/s00068-023-02320-x. [6] 陈华桂, 周秀萍. 儿童烧伤患者感染MRSA的耐药性及分子流行病学研究[J].国际检验医学杂志,2014(3):299-300,303. DOI: 10.3969/j.issn.1673-4130.2014.03.019. [7] 秦小锋, 赵宇辉. 大面积严重烧伤住院患者流行病学分析[J/CD].中华损伤与修复杂志(电子版),2021,16(5):417-426. DOI: 10.3877/cma.j.issn.1673-9450.2021.05.008. [8] ZhuZ, KongW, WangH, et al. Prevalence and predictors of scar contracture-associated re-hospitalisation among burn inpatients in China[J]. Sci Rep, 2021,11(1):14973. DOI: 10.1038/s41598-021-94432-w. [9] 中华人民共和国卫生部. 医院感染诊断标准(试行)[J].中华医学杂志,2001,81(5):314-320. DOI: 10.3760/j:issn:0376-2491.2001.05.027. [10] 李惠春, 丁圣刚, 卜笑松, 等. 儿童患者耐甲氧西林金黄色葡萄球菌的流行病学特征及耐药性分析[J].安徽医科大学学报,2019,54(4):651-655. DOI: 10.19405/j.cnki.issn1000-1492.2019.04.030. [11] 孙伟晶, 姚兴伟, 陈向军. 内蒙古地区1328例儿童烧伤流行病学调查[J].中华烧伤杂志,2012,28(3):229-230. DOI: 10.3760/cma.j.issn.1009-2587.2012.03.021. [12] 朱光君, 张宏, 朱立强, 等. 山西北部地区儿童热液烫伤流行病学调查[J].中国病案,2013,14(6):50-52. DOI: 10.3969/j.issn.1672-2566.2013.06.026. [13] 刘敏, 姚志慧, 白玉洁, 等. 2016-2018年某基层医院医院感染率调查[J].中华医院感染学杂志,2020,30(12):1899-1904. DOI: 10.11816/cn.ni.2020-191838. [14] RuanJ, XiM, XieW. Analysis of 12,661 pediatric burns in Wuhan institute of burns: a retrospective study of fifteen years[J]. Burns, 2021, 47(8):1915-1921. DOI: 10.1016/j.burns.2021.02.021. [15] ChenK, LiuJ, WangX, et al. Epidemiological characteristics of paediatric burn patients in China from 2016 to 2019: a retrospective study[J]. BMJ Paediatr Open, 2023, 7(1):e001796. DOI: 10.1136/bmjpo-2022-001796. [16] NakhaieS, SoboutiB, SalehiSH, et al. The role of serum albumin level during hospitalization as a predictor of complications and mortality in children with burns[J]. Med J Islam Repub Iran, 2023,37:41. DOI: 10.47176/mjiri.37.41. [17] YangY, ZhangX, ZhangJ, et al. Prediction models of surgical site infection after gastrointestinal surgery: a nationwide prospective cohort study[J/OL]. Int J Surg, (2023-10-05)[2023-11-11]. https://pubmed.ncbi.nlm.nih.gov/37800568/.DOI: 10.1097/JS9.0000000000000808.[published online ahead of print]. [18] SheridanRL, WeberJM. Mechanical and infectious complications of central venous cannulation in children: lessons learned from a 10-year experience placing more than 1000 catheters[J]. J Burn Care Res, 2006,27(5):713-718. DOI: 10.1097/01.BCR.0000238087.12064.E0. [19] GuanW, GongC, WuS, et al. Instant protection spray for anti-infection and accelerated healing of empyrosis[J]. Adv Mater, 2023:e2306589. DOI: 10.1002/adma.202306589. [20] CapoorMR, SarabahiS, TiwariVK, et al. Fungal infections in burns: diagnosis and management[J]. Indian J Plast Surg, 2010,43(Suppl):S37-42. DOI: 10.4103/0970-0358.70718. [21] 中国老年医学学会烧创伤分会. 烧伤儿童心理康复治疗全国专家共识(2020版)[J].中华烧伤杂志,2020,36(11):987-992. DOI: 10.3760/cma.j.cn501120-20200623-00321. -
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