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肺部实变 B 线比例可预测足月出生婴儿出生后不久的呼吸支持需求。

Proportion of confluent B-Lines predicts respiratory support in term infants shortly after birth.

机构信息

Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, No. 128, Shenyang Rd, Yangpu District, Shanghai, 200082, China.

Department of Neonatology, Fuyang Women and Children's Hospital, Fuyang, China.

出版信息

Respir Res. 2024 Aug 13;25(1):307. doi: 10.1186/s12931-024-02944-6.

Abstract

OBJECTIVE

To develop and evaluate the predictive value of a simplified lung ultrasound (LUS) method for forecasting respiratory support in term infants.

METHODS

This observational, prospective, diagnostic accuracy study was conducted in a tertiary academic hospital between June and December 2023. A total of 361 neonates underwent LUS examination within 1 h of birth. The proportion of each LUS sign was utilized to predict their respiratory outcomes and compared with the LUS score model. After identifying the best predictive LUS sign, simplified models were created based on different scan regions. The optimal simplified model was selected by comparing its accuracy with both the full model and the LUS score model.

RESULTS

After three days of follow-up, 91 infants required respiratory support, while 270 remained healthy. The proportion of confluent B-lines demonstrated high predictive accuracy for respiratory support, with an area under the curve (AUC) of 89.1% (95% confidence interval [CI]: 84.5-93.7%). The optimal simplified model involved scanning the R/L 1-4 region, yielding an AUC of 87.5% (95% CI: 82.6-92.3%). Both the full model and the optimal simplified model exhibited higher predictive accuracy compared to the LUS score model. The optimal cut-off value for the simplified model was determined to be 15.9%, with a sensitivity of 76.9% and specificity of 91.9%.

CONCLUSIONS

The proportion of confluent B-lines in LUS can effectively predict the need for respiratory support in term infants shortly after birth and offers greater reliability than the LUS score model.

摘要

目的

开发和评估简化肺部超声(LUS)方法对预测足月婴儿呼吸支持的预测价值。

方法

本观察性、前瞻性诊断准确性研究于 2023 年 6 月至 12 月在一家三级学术医院进行。共有 361 名新生儿在出生后 1 小时内接受 LUS 检查。利用每个 LUS 征象的比例预测其呼吸结局,并与 LUS 评分模型进行比较。在确定最佳预测 LUS 征象后,基于不同的扫描区域创建简化模型。通过比较其与全模型和 LUS 评分模型的准确性来选择最佳简化模型。

结果

在三天的随访后,91 名婴儿需要呼吸支持,而 270 名婴儿健康。连续 B 线的比例对呼吸支持具有较高的预测准确性,曲线下面积(AUC)为 89.1%(95%置信区间:84.5-93.7%)。最佳简化模型涉及扫描 R/L 1-4 区,AUC 为 87.5%(95%置信区间:82.6-92.3%)。全模型和最佳简化模型的预测准确性均高于 LUS 评分模型。简化模型的最佳截断值确定为 15.9%,灵敏度为 76.9%,特异性为 91.9%。

结论

LUS 中连续 B 线的比例可以有效地预测足月婴儿出生后不久呼吸支持的需求,其可靠性优于 LUS 评分模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cb4/11323528/7fee7f650f5c/12931_2024_2944_Fig1_HTML.jpg

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