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Background <p>Non-typhoidal <i>Salmonella</i> (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.</p> Methods <p>Data were collected during a prospective cohort study in children (&gt; 28 days—&lt; 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.</p> Results <p>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 &lt; 30% ranged from 2.4 to 3.9 per 100 children.</p> Conclusion <p>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 &lt; 30%. External validation studies are needed to investigate generalizability.</p> Trial registration <p>DeNTS study, clinicaltrials.gov: NCT04473768 (registration 16/07/2020) and TreNTS study, clinicaltrials.gov: NCT04850677 (registration 20/04/2021).</p>

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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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月27日

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  • 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

摘要

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).