Lloyd Lizel Georgi, Dramowski Angela, Bekker Adrie, Malou Nada, Ferreyra Cecilia, Van Weissenbruch Mirjam Maria
Department of Pediatrics and Child Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Foundation for Innovative New Diagnostics, Geneva, Switzerland.
Front Pediatr. 2022 Mar 11;10:830510. doi: 10.3389/fped.2022.830510. eCollection 2022.
Infection prediction scores are useful ancillary tests in determining the likelihood of neonatal hospital-acquired infection (HAI), particularly in very low birth weight (VLBW; <1,500 g) infants who are most vulnerable to HAI and have high antibiotic utilization rates. None of the existing infection prediction scores were developed for or evaluated in South African VLBW neonates.
We identified existing infection prediction scores through literature searches and assessed each score for suitability and feasibility of use in resource-limited settings. Performance of suitable scores were compared using a retrospective dataset of VLBW infants (2016-2017) from a tertiary hospital neonatal unit in Cape Town, South Africa. Sensitivity, specificity, predictive values, and likelihood ratios were calculated for each score.
Eleven infection prediction scores were identified, but only five were suitable for use in resource-limited settings (NOSEP1, Singh, Rosenberg, and Bekhof scores). The five selected scores were evaluated using data from 841 episodes of HAI in 659 VLBW infants. The sensitivity for the scores ranged between 3% (NOSEP1 ≥14; proven and presumed infection), to a maximum of 74% (Singh score ≥1; proven infection). The specificity of these scores ranged from 31% (Singh score ≥1; proven and presumed infection) to 100% (NOSEP1 ≥11 and ≥14, NOSEP-NEW-1 ≥11; proven and presumed infection).
Existing infection prediction scores did not achieve comparable predictive performance in South African VLBW infants and should therefore only be used as an adjunct to clinical judgment in antimicrobial decision making. Future studies should develop infection prediction scores that have high diagnostic accuracy and are feasible to implement in resource-limited neonatal units.
感染预测评分是辅助判定新生儿医院获得性感染(HAI)可能性的有用检查,尤其是对于极低出生体重(VLBW;<1500 g)的婴儿,他们最易发生HAI且抗生素使用率高。现有的感染预测评分均未针对南非VLBW新生儿制定或评估。
我们通过文献检索确定现有的感染预测评分,并评估每个评分在资源有限环境中使用的适用性和可行性。使用来自南非开普敦一家三级医院新生儿病房的VLBW婴儿(2016 - 2017年)回顾性数据集比较合适评分的性能。计算每个评分的敏感性、特异性、预测值和似然比。
确定了11个感染预测评分,但只有5个适用于资源有限的环境(NOSEP1、辛格、罗森伯格和贝霍夫评分)。使用659例VLBW婴儿841次HAI发作的数据对这5个选定的评分进行了评估。这些评分的敏感性在3%(NOSEP1≥14;确诊和疑似感染)至最高74%(辛格评分≥1;确诊感染)之间。这些评分的特异性范围从31%(辛格评分≥1;确诊和疑似感染)到100%(NOSEP1≥11和≥14,NOSEP - NEW - 1≥11;确诊和疑似感染)。
现有的感染预测评分在南非VLBW婴儿中未达到可比的预测性能,因此在抗菌决策中仅应用作临床判断的辅助手段。未来的研究应开发具有高诊断准确性且在资源有限的新生儿病房可行的感染预测评分。