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| 新生儿急性呼吸窘迫综合征病情严重程度的影响因素及列线图预测模型构建与评价 |
| Construction and Evaluation of the Factors Influencing the Severity of Neonatal Acute Respiratory Distress Syndrome and the Nomogram Prediction Model |
| 投稿时间：2024-06-18 修订日期：2024-06-18 |
| DOI： |
| 中文关键词: 蒙特勒诊断标准 新生儿 急性呼吸窘迫综合征 列线图预测模型 病情程度 |
| 英文关键词: Montreux diagnostic criteria Neonate Acute respiratory distress syndrome Nomogram prediction model Degree of illness |
| 基金项目:江苏省妇幼健康科研项目（F201850）；徐州市卫生健康委科技项目（XWKYHT20230058） |
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| 中文摘要: |
| 目的 探讨基于蒙特勒诊断标准的新生儿急性呼吸窘迫综合征（NARDS）病情严重程度的影响因素，构建预测风险的列线图模型。方法 分析2019年1月至2023年7月我院新生儿重症监护病房收治的165例符合蒙特勒诊断标准NARDS的临床资料。根据氧指数分为轻度组、中重度组，例数分别为67例和98例。收集所有新生儿的临床资料，采用多因素Logistic回归分析NARDS病情严重程度的相关因素。根据多因素Logistic回归分析结果，采用R语言rms包构建列线图预测模型。结果 多因素Logistic回归分析结果显示：新生儿早发败血症、初产、辅助通气时间、血清中性粒细胞（NEU）、降钙素原（PCT）、C反应蛋白（CRP）水平为NARDS病情严重程度的独立危险因素（P＜0.05）.列线图模型预测概率与实际概率贴合度良好。结论 预防围生期感染、重视孕妇的产前保健、避免不必要的辅助通气、定期监测NEU、PCT、CRP等生物标志物，有助于降低重症 NARDS 的风险。基于上述因素建立的列线图预测模型对NARDS病情严重程度具有良好的预测价值。 |
| 英文摘要: |
| Objective:To explore the influencing factors of the severity of neonatal acute respiratory distress syndrome (NARDS) based on Montreux diagnostic criteria, and construct a nomogram model to predict the risk. Methods:The clinical data of 165 child patients with Montreux diagnostic criteria for NARDS admitted to the neonatal intensive care unit of our hospital from January 2019 to July 2023 were analyzed. Child patients were divided into mild group, moderate group and severe group according to the oxygen index, the number of cases was 67, 57 and 41 cases respectively. The clinical data of all newborns were collected, the related factors affecting the severity of NARDS were analyzed by multivariate Logistic regression analysis, the rms package in R language was used to construct a nomogram prediction model according to the results of multivariate Logistic regression analysis.Results: Premature neonatal septicemia, primiparity, auxiliary ventilation time, serum neutrophil count(NEU), procalcitonin(PCT), C-reactive protein(CRP) levels were independent risk factors affecting the severity of NARDS (P<0.05), the nomogram model prediction curve was in good agreement with the ideal curve.Conclusion: Prevention of perinatal infection, attention to prenatal care of pregnant women, avoidance of unnecessary assisted ventilation, and regular monitoring of inflammatory markers such as NEU, PCT and CRP can help reduce the risk of severe NARDS. The nomogram prediction model base on the above factors has a high predictive value for the severity of NARDS. |
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