Developing a clinical prediction model to modify empirical antibiotics for non-typhoidal Salmonella bloodstream infection in children under-five in the Democratic Republic of Congo.

IF 3 3区 医学 Q2 INFECTIOUS DISEASES BMC Infectious Diseases Pub Date : 2025-01-27 DOI:10.1186/s12879-024-10319-x
Bieke Tack, Daniel Vita, Jules Mbuyamba, Emmanuel Ntangu, Hornela Vuvu, Immaculée Kahindo, Japhet Ngina, Aimée Luyindula, Naomie Nama, Tito Mputu, Justin Im, Hyonjin Jeon, Florian Marks, Jaan Toelen, Octavie Lunguya, Jan Jacobs, Ben Van Calster
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Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Trial registration: DeNTS study, clinicaltrials.gov: NCT04473768 (registration 16/07/2020) and TreNTS study, clinicaltrials.gov: NCT04850677 (registration 20/04/2021).

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开发临床预测模型,修改刚果民主共和国五岁以下儿童非伤寒沙门氏菌血液感染的经验性抗生素。
背景:非伤寒沙门氏菌(NTS)经常引起撒哈拉以南非洲五岁以下儿童的血液感染,特别是在疟疾流行地区。由于耐药性日益增加,NTS通常不包括在严重发热性疾病的标准护理经验性抗生素中。我们开发了一个临床预测模型,以指导在耐药NTS比例高的环境中入院的儿童选择经验性抗生素(标准护理与替代抗生素)。方法:在一项儿童前瞻性队列研究中收集数据(bb0 28天)。结果:12.7%(295/2327)的入组儿童诊断出NTS血流感染。预测模型曲线下面积为0.79 (95%CI: 0.76 ~ 0.82),评分系统曲线下面积为0.78(0.85 ~ 0.80)。估计校准斜率分别为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%。结论:该模型预测NTS血流感染,并可以支持选择经验性抗生素,包括耐药NTS的覆盖范围,特别是决策阈值试验注册:dent研究,clinicaltrials.gov: NCT04473768(注册日期为2020年7月16日)和TreNTS研究,clinicaltrials.gov: NCT04850677(注册日期为2021年4月20日)。
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来源期刊
BMC Infectious Diseases
BMC Infectious Diseases 医学-传染病学
CiteScore
6.50
自引率
0.00%
发文量
860
审稿时长
3.3 months
期刊介绍: BMC Infectious Diseases is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of infectious and sexually transmitted diseases in humans, as well as related molecular genetics, pathophysiology, and epidemiology.
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