A systematic review of neonatal treatment intensity scores and their potential application in low-resource setting hospitals for predicting mortality, morbidity and estimating resource use.
A systematic review of neonatal treatment intensity scores and their potential application in low-resource setting hospitals for predicting mortality, morbidity and estimating resource use.
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DOI：
10.1186/s13643-017-0649-6
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发表时间：
2017-12-07
影响因子：
3.7
通讯作者：
English M
中科院分区：
文献类型：
--
作者：
Aluvaala J;Collins GS;Maina M;Berkley JA;English M
治疗强度评分可以预测死亡率和估计资源使用情况。因此，在新生儿死亡率居高不下的低资源环境中，它们可能对基本的新生儿护理感兴趣。我们试图系统地审查新生儿治疗强度评分，以(1)评估在预测临床结果和估计资源利用方面的预测表现的证据水平，以及(2)评估所识别的模型在低资源环境下对新生儿护理决策的适用性。我们对PubMed、EMBASE(Ovid)、CINAHL、全球健康图书馆(Global Index，WHO)和谷歌学者进行了系统搜索，以确定截至2016年12月21日发表的研究。纳入的所有文章都使用治疗作为新生儿模型的预测因子。个别研究使用预测模型研究系统回顾的关键评估和数据提取核对表(CHARMS)进行评估。此外，评估、发展和评价建议的分级(等级)被用作一个指导框架，以评估预测研究结果的证据的确定性。共筛选出3249篇文献，纳入综述文献10篇。所有研究都是在新生儿重症监护病房进行的，样本量从22到9978，中位数为163。两篇文章报道了模型开发，而八篇文章报告了现有模型在新人口中的外部应用。由于已确定研究的实施和报告的异质性，荟萃分析是不可能的。根据受试者操作特征曲线下面积评估的辨别力报告了住院死亡率的中位数0.84(范围0.75-0.96，三项研究)，早期不良结果和晚期不良结果(分别为0.78和0.59，一项研究)。现有的新生儿治疗强度模型在预测死亡率和发病率方面显示出希望。然而，由于所有研究都有方法学上的限制，而且都是在重症监护中进行的，因此在资源匮乏的情况下，关于它们在基本新生儿护理中的表现的证据不太确定。然而，对于像肯尼亚这样的低资源环境，该方法可以进一步发展，因为与生理状态的测量相比，治疗数据可能更容易获得。PROSPERO CRD42016034205本文的在线版本(10.1186/s13643-0170649-6)包含补充材料，授权用户可以使用。
Treatment intensity scores can predict mortality and estimate resource use. They may therefore be of interest for essential neonatal care in low resource settings where neonatal mortality remains high. We sought to systematically review neonatal treatment intensity scores to (1) assess the level of evidence on predictive performance in predicting clinical outcomes and estimating resource utilisation and (2) assess the applicability of the identified models to decision making for neonatal care in low resource settings. We conducted a systematic search of PubMed, EMBASE (OVID), CINAHL, Global Health Library (Global index, WHO) and Google Scholar to identify studies published up until 21 December 2016. Included were all articles that used treatments as predictors in neonatal models. Individual studies were appraised using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). In addition, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was used as a guiding framework to assess certainty in the evidence for predicting outcomes across studies. Three thousand two hundred forty-nine articles were screened, of which ten articles were included in the review. All of the studies were conducted in neonatal intensive care units with sample sizes ranging from 22 to 9978, with a median of 163. Two articles reported model development, while eight reported external application of existing models to new populations. Meta-analysis was not possible due heterogeneity in the conduct and reporting of the identified studies. Discrimination as assessed by area under receiver operating characteristic curve was reported for in-hospital mortality, median 0.84 (range 0.75–0.96, three studies), early adverse outcome and late adverse outcome (0.78 and 0.59, respectively, one study). Existing neonatal treatment intensity models show promise in predicting mortality and morbidity. There is however low certainty in the evidence on their performance in essential neonatal care in low resource settings as all studies had methodological limitations and were conducted in intensive care. The approach may however be developed further for low resource settings like Kenya because treatment data may be easier to obtain compared to measures of physiological status. PROSPERO CRD42016034205 The online version of this article (10.1186/s13643-017-0649-6) contains supplementary material, which is available to authorized users.
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