26 Derivation and validation of a clinical decision rule to discriminate bacteremia from contaminants among children with a positive blood culture in the emergency department
Notice bibliographique
Résumé
Abstract Background Blood cultures are commonly performed to rule out bacteremia in children seen in the emergency department (ED), which if missed, can progress to sepsis and even death. While a true bacteremia is potentially life-threatening and requires urgent treatment, many cases of positive blood cultures are contaminants leading to unnecessary antibiotic exposures and hospitalizations. Objectives We aimed to derive and validate a clinical decision rule to discriminate bacteremia from contaminants among children seen in the ED with a preliminary positive blood culture. Design/Methods This study includes two retrospective cohorts of children with positive blood cultures from a Canadian paediatric ED from January 2018 until May 2024. The primary outcome was true bacteremia defined using two-step standardized approach based on the bacteria involved and the clinical outcome assessment adjudicated by two reviewers. Predictors of bacteremia were derived from a literature review and a consensus of experts. We used Classification and Regression Tree models to derive a highly sensitive clinical decision rule to distinguish between true bacteremia and contamination. The validity was assessed by measuring the proportion of children with true bacteremia classified at high or moderate risk by the clinical decision rule (sensitivity) and the proportion of contaminants classified at low risk by the rule (specificity). For participants discharged home at the index visit, the clinical utility of the rule was measured by comparing the clinical decision rule to the treating physician's management. Results A total of 574 children, including 285 cases of bacteremia were included in the derivation phase, and 173 (including 83 bacteremia) in the validation cohort. Derived from the final selected model, we were able to classify children into three categories (high, moderate and low risk). Children at high risk of bacteremia were identified based on the initial Gram stain (Gram positive bacteria in pair or chain, or all Gram negative bacteria). In the absence of high-risk Gram stain criteria, children were at moderate risk if they had any one of three risks factors (Culture positive in less than 17 hours; Internal devices; Suspicion of osteo-articular infection). Children without any of the four criteria were classified as low risk. This clinical decision rule demonstrated a sensitivity of 100% (95%CI: 98-100%) and specificity of 65% (95%CI: 59-70%) in the derivation cohort. In the validation cohort, the clinical decision rule demonstrated a sensitivity of 99% (95%CI: 94-100%) and a specificity of 60% (95%CI: 50-70%). Applying the rule to the 43 children initially discharged in the validation cohort would decrease the number of admissions from 34 to 21 without missing a true bacteremia case. Conclusion We created a highly sensitive clinical decision rule to identify true bacteremia among children seen in the ED with a preliminary positive blood culture. The use of this clinical decision rule will decrease unnecessary testing and antibiotics in a subset of patients while ensuring treatment of children at high risk of true bacteremia.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».