Koeller Eva, Robertson Sarah E, Garbern Stephanie Chow, Monk Grace, Nasrin Sabiha, Alam Nur H, Levine Adam C
Warren Alpert Medical School of Brown University, Brown University, Providence, Rhode Island, USA.
Brown University School of Public Health, Brown University, Providence, Rhode Island, USA.
J Ultrasound Med. 2019 Mar;38(3):685-693. doi: 10.1002/jum.14752. Epub 2018 Oct 5.
Diarrhea is one of the most common and deadly conditions affecting children, causing over 525,000 deaths annually, largely in resource-limited settings. Appropriate treatment depends on accurate determination of dehydration status. This study evaluated the accuracy of a new model using clinical and ultrasound measurements for predicting dehydration status in children with acute diarrhea.
The Dehydration: Assessing Kids Accurately (DHAKA) study was a prospective cohort study of children under 5 years of age with acute diarrhea presenting to the International Centre for Diarrhoeal Disease Research in Dhaka, Bangladesh. Clinical signs and sonographic measurements of the aorta-to-inferior vena cava ratio were recorded. Percent weight change with rehydration was used to classify dehydration severity. Logistic regression was used to create a combined DHAKA-US model based on clinical and sonographic measurements. Area under the curve and calibration slope were used to assess the model's accuracy and compare it to the original DHAKA score model.
A total of 850 children were enrolled, with 736 included in the final analysis. The combined DHAKA-US model showed equivalent discrimination with the original DHAKA score, with an area under the curve of 0.79 for both models for severe dehydration (95% confidence interval, 0.74-0.84), as well as similar classification (48% versus 50% correctly classified) and calibration (calibration slopes of 0.900 versus 0.904 for presence of any dehydration).
Adding sonographic measurements to the DHAKA score had no effect on discrimination, classification, or calibration when compared to the original DHAKA score. Clinical signs alone may be the most important predictors of dehydration status in children with diarrhea in limited resource settings.
腹泻是影响儿童的最常见且致命的病症之一,每年导致超过52.5万人死亡,主要发生在资源有限的地区。恰当的治疗取决于对脱水状态的准确判定。本研究评估了一种使用临床和超声测量来预测急性腹泻患儿脱水状态的新模型的准确性。
“脱水:准确评估儿童”(DHAKA)研究是一项针对孟加拉国达卡国际腹泻病研究中心就诊的5岁以下急性腹泻儿童的前瞻性队列研究。记录临床体征以及主动脉与下腔静脉比值的超声测量结果。使用补液后体重变化百分比对脱水严重程度进行分类。基于临床和超声测量结果,采用逻辑回归创建了一个综合的DHAKA-US模型。曲线下面积和校准斜率用于评估该模型的准确性,并将其与原始的DHAKA评分模型进行比较。
共纳入850名儿童,最终分析纳入736名。综合的DHAKA-US模型与原始的DHAKA评分显示出同等的判别能力,两个模型对于重度脱水的曲线下面积均为0.79(95%置信区间,0.74 - 0.84),分类情况也相似(正确分类率分别为48%和50%),校准情况也相近(存在任何脱水时的校准斜率分别为0.900和0.904)。
与原始的DHAKA评分相比,在DHAKA评分中加入超声测量对判别、分类或校准均无影响。在资源有限的环境中,仅临床体征可能是腹泻患儿脱水状态的最重要预测指标。