Tack Bieke, Vita Daniel, Mbuyamba Jules, Ntangu Emmanuel, Vuvu Hornela, Kahindo Immaculée, Ngina Japhet, Luyindula Aimée, Nama Naomie, Mputu Tito, Im Justin, Jeon Hyonjin, Marks Florian, Toelen Jaan, Lunguya Octavie, Jacobs Jan, Van Calster Ben
Department of Clinical Sciences, Institute of Tropical Medicine, Nationalestraat 155, 2000, Antwerp, Belgium.
Department of Microbiology, Immunology and Transplantation, KU Leuven, Louvain, Belgium.
BMC Infect Dis. 2025 Jan 27;25(1):122. doi: 10.1186/s12879-024-10319-x.
Non-typhoidal Salmonella (NTS) frequently cause bloodstream infection in children under-five in sub-Saharan Africa, particularly in malaria-endemic areas. Due to increasing drug resistance, NTS are often not covered by standard-of-care empirical antibiotics for severe febrile illness. We developed a clinical prediction model to orient the choice of empirical antibiotics (standard-of-care versus alternative antibiotics) for children admitted to hospital in settings with high proportions of drug-resistant NTS.
Data were collected during a prospective cohort study in children (> 28 days-< 5 years) admitted with severe febrile illness to Kisantu district hospital, DR Congo. The outcome variable was blood culture confirmed NTS bloodstream infection; the comparison group were children without NTS bloodstream infection. Predictors were selected a priori based on systematic literature review. The prediction model was developed with multivariable logistic regression; a simplified scoring system was derived. Internal validation to estimate optimism-corrected performance was performed using bootstrapping and net benefits were calculated to evaluate clinical usefulness.
NTS bloodstream infection was diagnosed in 12.7% (295/2327) of enrolled children. The area under the curve was 0.79 (95%CI: 0.76-0.82) for the prediction model, and 0.78 (0.85-0.80) for the scoring system. The estimated calibration slopes were 0.95 (model) and 0.91 (scoring system). At a decision threshold of 20% NTS risk, the prediction model and scoring system had 57% and 53% sensitivity, and 85% specificity. The net benefit for decisions thresholds < 30% ranged from 2.4 to 3.9 per 100 children.
The model predicts NTS bloodstream infection and can support the choice of empiric antibiotics to include coverage of drug-resistant NTS, in particular for decision thresholds < 30%. External validation studies are needed to investigate generalizability.
DeNTS study, clinicaltrials.gov: NCT04473768 (registration 16/07/2020) and TreNTS study, clinicaltrials.gov: NCT04850677 (registration 20/04/2021).
非伤寒沙门氏菌（NTS）经常导致撒哈拉以南非洲五岁以下儿童发生血流感染，尤其是在疟疾流行地区。由于耐药性不断增加，NTS通常不在针对严重发热性疾病的标准治疗经验性抗生素覆盖范围内。我们开发了一种临床预测模型，以指导在耐药NTS比例较高的环境中住院儿童经验性抗生素（标准治疗与替代抗生素）的选择。
在刚果民主共和国基桑图区医院对患有严重发热性疾病的儿童（>28天-<5岁）进行前瞻性队列研究期间收集数据。结果变量是血培养确诊的NTS血流感染；对照组是没有NTS血流感染的儿童。预测因素是根据系统文献综述预先选择的。使用多变量逻辑回归开发预测模型；得出一个简化的评分系统。使用自举法进行内部验证以估计乐观校正性能，并计算净效益以评估临床实用性。
在纳入的儿童中，12.7%（295/2327）被诊断为NTS血流感染。预测模型的曲线下面积为0.79（95%CI：0.76-0.82），评分系统的曲线下面积为0.78（0.85-0.80）。估计的校准斜率分别为0.95（模型）和0.91（评分系统）。在NTS风险为20%的决策阈值下，预测模型和评分系统的敏感性分别为57%和53%，特异性为85%。决策阈值<30%时，每100名儿童的净效益范围为2.4至3.9。
该模型可预测NTS血流感染，并可支持经验性抗生素的选择，包括对耐药NTS的覆盖，特别是对于决策阈值<30%的情况。需要进行外部验证研究以调查其普遍性。
DeNTS研究，clinicaltrials.gov：NCT04473768（注册日期2020年7月16日）和TreNTS研究，clinicaltrials.gov：NCT04850677（注册日期2021年4月20日）。
