107 Addition of CRP and Respiratory Viral Testing for Risk-Stratification of Febrile Young Infants
Notice bibliographique
Résumé
Abstract Primary Subject area Emergency Medicine - Paediatric Background Febrile young infants are frequently brought for medical attention. Although most have viral illnesses, approximately 10% have serious bacterial infections (SBIs) including urinary tract infections, bacteremia or bacterial meningitis. Risk-stratification must have high sensitivity given the consequences of a missed SBI diagnosis. The most widely used risk-stratification criteria rely upon the serum white blood cell count (WBC) and urinalysis (UA), but predate the widespread use of CRP and respiratory virus testing (RVT), both of which offer enhanced ability to detect high-risk infants. CRP and RVT have never been evaluated together or in combination with traditional biomarkers, particularly for the detection invasive bacterial infections (IBI), bacteremia and meningitis. Objectives Compare the diagnostic utility of CRP and RVT in combination with WBC and UA for risk-stratification of febrile young infants. Design/Methods This was a retrospective study of healthy term febrile infants ≤ 90 days old evaluated in an urban tertiary Pediatric Emergency Department from 2010-2018. Only infants with both blood and urine cultures were included. Test characteristics for detecting SBI and IBI were calculated for tests individually and in composite. Results Of 3461 included infants, 442 (12.7%) had SBIs and 56 (1.6%) had IBIs. Overall use of CRP (25%) and RVT (78%) increased over time, and 698 (22%) infants had complete testing with UA, WBC, CRP and RVT. When considering individual diagnostic tests (Table 1), risk of SBI with a normal CRP (1.4%), negative UA (0.18%) or positive RVT (2.6%) was lower than with a normal WBC (6.7%) alone. Risk of IBI was lowest among infants with a positive RVT (0.19%; vs 0.57%, 0.59%, 0.70% for CRP, UA, WBC respectively), and RVT performed best for detection of IBI (Sn 0.857; NPV 0.996). When risk-stratifying infants using tests in combination (Table 2), 43/3339 (1.3%) infants had a SBI despite meeting low-risk criteria with a normal WBC and UA (Sn 0.900; NPV 0.980), compared to 4/698 (0.57%) with a normal WBC, UA, CRP and positive RVT (Sn 0.951; NPV 0.981). IBI was present in 10/3339 (0.3%) infants stratified as low-risk by a normal WBC and UA (Sn 0.818; NPV 0.995), compared to 0/698 (0%) with a normal WBC, UA, CRP and positive RVT (Sn 1.00; NPV 1.00). Subanalysis restricted only to infants with complete testing yielded similar results. Conclusion This is the first study to compare use of CRP and RVT in addition to traditional biomarkers for febrile young infants. Use of these widely available tests in combination may improve risk-stratification to reduce unnecessary invasive testing and hospitalizations. Prospective efficacy and cost-effectiveness studies are warranted.
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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 | 0,001 |
| 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 ».