翟秀玲, 王永霞, 丁卉, 张利兵, 李眉. 重症肺炎患儿俯卧位通气相关面部压力性损伤发生风险因素分析及列线图构建[J]. 实用临床医药杂志, 2024, 28(4): 102-106. DOI: 10.7619/jcmp.20232694
引用本文: 翟秀玲, 王永霞, 丁卉, 张利兵, 李眉. 重症肺炎患儿俯卧位通气相关面部压力性损伤发生风险因素分析及列线图构建[J]. 实用临床医药杂志, 2024, 28(4): 102-106. DOI: 10.7619/jcmp.20232694
ZHAI Xiuling, WANG Yongxia, DING Hui, ZHANG Libing, LI Mei. Risk factors analysis and nomogram construction of facial pressure injury related to ventilation in prone positioning in children with severe pneumonia[J]. Journal of Clinical Medicine in Practice, 2024, 28(4): 102-106. DOI: 10.7619/jcmp.20232694
Citation: ZHAI Xiuling, WANG Yongxia, DING Hui, ZHANG Libing, LI Mei. Risk factors analysis and nomogram construction of facial pressure injury related to ventilation in prone positioning in children with severe pneumonia[J]. Journal of Clinical Medicine in Practice, 2024, 28(4): 102-106. DOI: 10.7619/jcmp.20232694

重症肺炎患儿俯卧位通气相关面部压力性损伤发生风险因素分析及列线图构建

Risk factors analysis and nomogram construction of facial pressure injury related to ventilation in prone positioning in children with severe pneumonia

  • 摘要:
    目的 探讨重症肺炎患儿俯卧位通气相关面部压力性损伤的影响因素并构建列线图预测模型。
    方法 选取158例行俯卧位通气治疗的重症肺炎患儿作为研究对象,收集患儿的临床资料,根据是否发生面部压力性损伤将患儿分为损伤组31例和未损伤组127例。采用单因素分析和多因素Logistic回归分析探讨重症肺炎患儿俯卧位通气相关面部压力性损伤的影响因素; 采用受试者工作特征(ROC)曲线、一致性指数、Hosmer-Lemeshow拟合优度检验评估列线图模型对重症肺炎患儿俯卧位通气相关面部压力性损伤的预测效能。
    结果 单因素分析结果显示,损伤组年龄 < 3岁者占比、有并发症者占比、俯卧位通气时间、使用镇静药物者占比、营养状态不良者占比、未应用减压敷料者占比、医务人员未行俯卧位通气培训者占比高于或长于未损伤组,差异有统计学意义(P < 0.05)。多因素Logistic回归分析结果显示,年龄 < 3岁、有并发症、俯卧位通气时间长、未应用减压敷料、医务人员未行俯卧位通气培训均为重症肺炎患儿俯卧位通气相关面部压力性损伤的独立危险因素(P < 0.05), 据此构建列线图预测模型。该列线图模型的一致性指数为0.940, ROC曲线的曲线下面积为0.978(95%CI: 0.958~0.999), 预测重症肺炎患儿俯卧位通气相关面部压力性损伤的校准曲线趋近于理想曲线, Hosmer-Lemeshow拟合优度检验结果显示拟合良好(χ2=12.416, P < 0.05)。
    结论 本研究基于5个独立危险因素构建的列线图预测模型具有较高的风险识别能力, 可尽早识别重症肺炎俯卧位通气相关面部压力性损伤高危患儿。

     

    Abstract:
    Objective To investigate the influencing factors of facial pressure injury related to ventilation in prone positioning in children with severe pneumonia and to construct a nomogram prediction model.
    Methods A total of 158 children with severe pneumonia who underwent prone positioning ventilation were selected as research subjects. Clinical data were collected, and the children were divided into injury group (31 cases) and non-injury group (127 cases) based on whether facial pressure injury occurred. Univariate and multivariate Logistic regression analysis were used to explore the influencing factors of facial pressure injury related to prone positioning ventilation in children with severe pneumonia; the receiver operating characteristic (ROC) curve, consistency index, and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the predictive efficiency of the nomogram model for facial pressure injury related to prone positioning ventilation in children with severe pneumonia.
    Results Univariate analysis showed that the proportion of children aged < 3 years, the proportion of those with complications, ventilation time in prone positioning, the proportions of children with sedative drugs and poor nutritional status, no decompression dressings, and the proportions of children without prone positioning ventilation training for medical staff in the injury group were higher or longer than that in the non-injury group (P < 0.05). Multivariate Logistic regression analysis showed that age < 3 years, presence of complications, longer prone positioning ventilation time, no decompression dressings, and lack of prone positioning ventilation training for medical staff were independent risk factors for facial pressure injury related to prone positioning ventilation in children with severe pneumonia (P < 0.05), and a nomogram prediction model was constructed based on these factors. The consistency index of the nomogram model was 0.940, and the area under the ROC curve was 0.978 (95%CI, 0.958 to 0.999). The calibration curve of predicting facial pressure injury related to prone positioning ventilation in children with severe pneumonia approached the ideal curve, and the Hosmer-Lemeshow goodness-of-fit test showed good fitting (χ2=12.416, P < 0.05).
    Conclusion The nomogram prediction model constructed based on 5 independent risk factors in this study has high risk identification ability and can early identify high-risk children with facial pressure injury related to prone positioning ventilation in severe pneumonia.

     

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