Suppr超能文献

在无法进行超声孕周测定时,使用平板电脑应用简化孕周评分(T-SGAS)在出生时早期识别早产儿:一项验证研究方案

Early Identification of Preterm Neonates at Birth With a Tablet App for the Simplified Gestational Age Score (T-SGAS) When Ultrasound Gestational Age Dating Is Unavailable: Protocol for a Validation Study.

作者信息

Patel Archana B, Kurhe Kunal, Prakash Amber, Bhargav Savita, Parepalli Suchita, Fogleman Elizabeth V, Moore Janet L, Wallace Dennis D, Kulkarni Hemant, Hibberd Patricia L

机构信息

Lata Medical Research Foundation, Nagpur, Maharashtra, India.

RTI International, Research Triangle Park, NC, United States.

出版信息

JMIR Res Protoc. 2019 Mar 12;8(3):e11913. doi: 10.2196/11913.

Abstract

BACKGROUND

Although rates of preterm birth continue to increase globally, identification of preterm from low birth weight infants remains a challenge. The burden of low birth weight vs preterm is greatest in resource-limited settings, where gestational age (GA) prior to delivery is frequently not known because ultrasound in early pregnancy is not available and estimates of the date of the mother's last menstrual period (LMP) may not be reliable. An alternative option is to assess GA at birth to optimize referral and care of preterm newborns. We previously developed and pilot-tested a system to measure the simplified gestational age score (SGAS) based on 4 easily observable neonatal characteristics.

OBJECTIVE

The objective of this study is to adapt the scoring system as a tablet app (potentially scalable approach) to assess feasibility of use and to validate whether the scoring system accurately predicts prematurity by itself, over and above birth weight in a large sample of newborns.

METHODS

The study is based in Nagpur, India, at the Research Unit of the National Institute of Child Health and Human Development's Global Network for Women's and Children's Health Research. The Android tablet app for the SGAS (T-SGAS) displays de-identified photographs of skin, breasts, and genitalia across a range of GAs and line drawings of infant posture. Each item is associated with a score. The user is trained to choose the photograph or line drawing that most closely matches the newborn being evaluated, and the app determines the neonate's GA category (preterm or term) from the cumulative score. The validation study will be conducted in 3 second level care facilities (most deliveries in India occur in hospitals, and women known to be at risk of preterm birth are referred to second level care facilities). Within 24 hours of delivery, women and their babies who are stable will be enrolled in the study. Two auxiliary nurse midwives (ANMs) blinded to prior GA assessments will use the T-SGAS to estimate the GA status of the newborn. An independent data collector will abstract the GA from the ultrasound recorded in the hospital chart and record the date of the mother's LMP. Eligibility for analysis is determined by the ultrasound and LMP data being collected within 1 week of each other to have a rigorous assessment of true GA.

RESULTS

Publication of the results of the study is anticipated in 2019.

CONCLUSIONS

Until GA dating by ultrasound is universally available and easy to use in resource-limited settings, and where there are restrictions on ultrasound use due to their use for sex determination and abortion of female fetuses, this study will determine whether the T-SGAS app can accurately assess GA in risk categories at birth.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02408783; https://clinicaltrials.gov/ct2/show/NCT02408783 (Archived by Webcite at http://www.webcitation.org/75S2kmr3T).

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11913.

摘要

背景

尽管全球早产率持续上升,但从低出生体重婴儿中识别出早产儿仍然是一项挑战。在资源有限的环境中,低出生体重与早产的负担最为沉重,因为在这些地方,由于无法进行早孕超声检查,且母亲末次月经日期(LMP)的估算可能不可靠,所以分娩前的孕周(GA)常常未知。另一种选择是在出生时评估孕周,以优化对早产新生儿的转诊和护理。我们之前开发并进行了初步测试,建立了一个基于4种易于观察的新生儿特征来测量简化孕周评分(SGAS)的系统。

目的

本研究的目的是将该评分系统改编为平板电脑应用程序(一种可能具有可扩展性的方法),以评估其使用的可行性,并验证该评分系统能否在大量新生儿样本中独立于出生体重准确预测早产情况。

方法

该研究在印度那格浦尔的国家儿童健康与人类发展研究所全球妇女和儿童健康研究网络的研究单位进行。用于SGAS的安卓平板电脑应用程序(T-SGAS)展示了一系列孕周下皮肤、乳房和生殖器的匿名照片以及婴儿姿势的线条图。每个项目都有一个分数。对用户进行培训,使其选择与被评估新生儿最匹配的照片或线条图,应用程序根据累计分数确定新生儿的孕周类别(早产或足月)。验证研究将在3家二级护理机构进行(印度的大多数分娩在医院进行,已知有早产风险的妇女会被转诊至二级护理机构)。在分娩后24小时内,情况稳定的妇女及其婴儿将被纳入研究。两名对先前孕周评估不知情的辅助护士助产士(ANM)将使用T-SGAS来估计新生儿的孕周状态。一名独立的数据收集者将从医院病历中记录的超声检查中提取孕周,并记录母亲的LMP日期。分析的合格标准由彼此在1周内收集的超声和LMP数据确定,以便对真实孕周进行严格评估。

结果

预计该研究结果将于2019年发表。

结论

在资源有限的环境中,当超声孕周测定尚未普及且使用不便,以及因超声用于性别鉴定和女胎流产而对其使用有限制的情况下,本研究将确定T-SGAS应用程序能否在出生时准确评估高危类别中的孕周。

试验注册

ClinicalTrials.gov NCT02408783;https://clinicaltrials.gov/ct2/show/NCT02408783(由Webcite存档于http://www.webcitation.org/75S2kmr3T)。

国际注册报告识别码(IRRID):DERR1-10.2196/11913。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afbf/6434403/4dbde374ab28/resprot_v8i3e11913_fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验