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Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care

(2015) BMJ OPEN. 5(8).
Author
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Abstract
Objective: Acute infection is the most common presentation of children in primary care with only few having a serious infection (eg, sepsis, meningitis, pneumonia). To avoid complications or death, early recognition and adequate referral are essential. Clinical prediction rules have the potential to improve diagnostic decision-making for rare but serious conditions. In this study, we aimed to validate a recently developed decision tree in a new but similar population. Design: Diagnostic accuracy study validating a clinical prediction rule. Setting and participants: Acutely ill children presenting to ambulatory care in Flanders, Belgium, consisting of general practice and paediatric assessment in outpatient clinics or the emergency department. Intervention: Physicians were asked to score the decision tree in every child. Primary outcome measures: The outcome of interest was hospital admission for at least 24 h with a serious infection within 5 days after initial presentation. We report the diagnostic accuracy of the decision tree in sensitivity, specificity, likelihood ratios and predictive values. Results: In total, 8962 acute illness episodes were included, of which 283 lead to admission to hospital with a serious infection. Sensitivity of the decision tree was 100% (95% CI 71.5% to 100%) at a specificity of 83.6% (95% CI 82.3% to 84.9%) in the general practitioner setting with 17% of children testing positive. In the paediatric outpatient and emergency department setting, sensitivities were below 92%, with specificities below 44.8%. Conclusions: In an independent validation cohort, this clinical prediction rule has shown to be extremely sensitive to identify children at risk of hospital admission for a serious infection in general practice, making it suitable for ruling out.
Keywords
FEBRILE CHILDREN, BACTERIAL-INFECTION, YOUNG-CHILDREN, SIGNS, SYMPTOMS, COHORT, FEVER

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MLA
Verbakel, Jan et al. “Validating a Decision Tree for Serious Infection: Diagnostic Accuracy in Acutely Ill Children in Ambulatory Care.” BMJ OPEN 5.8 (2015): n. pag. Print.
APA
Verbakel, J., Lemiengre, M., De Burghgraeve, T., De Sutter, A., Aertgeerts, B., Bullens, D. M., Shinkins, B., et al. (2015). Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. BMJ OPEN, 5(8).
Chicago author-date
Verbakel, Jan, Marieke Lemiengre, Tine De Burghgraeve, An De Sutter, Bert Aertgeerts, Dominique MA Bullens, Bethany Shinkins, Ann Van den Bruel, and Frank Buntinx. 2015. “Validating a Decision Tree for Serious Infection: Diagnostic Accuracy in Acutely Ill Children in Ambulatory Care.” Bmj Open 5 (8).
Chicago author-date (all authors)
Verbakel, Jan, Marieke Lemiengre, Tine De Burghgraeve, An De Sutter, Bert Aertgeerts, Dominique MA Bullens, Bethany Shinkins, Ann Van den Bruel, and Frank Buntinx. 2015. “Validating a Decision Tree for Serious Infection: Diagnostic Accuracy in Acutely Ill Children in Ambulatory Care.” Bmj Open 5 (8).
Vancouver
1.
Verbakel J, Lemiengre M, De Burghgraeve T, De Sutter A, Aertgeerts B, Bullens DM, et al. Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. BMJ OPEN. 2015;5(8).
IEEE
[1]
J. Verbakel et al., “Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care,” BMJ OPEN, vol. 5, no. 8, 2015.
@article{7237936,
  abstract     = {Objective: Acute infection is the most common presentation of children in primary care with only few having a serious infection (eg, sepsis, meningitis, pneumonia). To avoid complications or death, early recognition and adequate referral are essential. Clinical prediction rules have the potential to improve diagnostic decision-making for rare but serious conditions. In this study, we aimed to validate a recently developed decision tree in a new but similar population. 
Design: Diagnostic accuracy study validating a clinical prediction rule. 
Setting and participants: Acutely ill children presenting to ambulatory care in Flanders, Belgium, consisting of general practice and paediatric assessment in outpatient clinics or the emergency department. 
Intervention: Physicians were asked to score the decision tree in every child. 
Primary outcome measures: The outcome of interest was hospital admission for at least 24 h with a serious infection within 5 days after initial presentation. We report the diagnostic accuracy of the decision tree in sensitivity, specificity, likelihood ratios and predictive values. 
Results: In total, 8962 acute illness episodes were included, of which 283 lead to admission to hospital with a serious infection. Sensitivity of the decision tree was 100% (95% CI 71.5% to 100%) at a specificity of 83.6% (95% CI 82.3% to 84.9%) in the general practitioner setting with 17% of children testing positive. In the paediatric outpatient and emergency department setting, sensitivities were below 92%, with specificities below 44.8%. 
Conclusions: In an independent validation cohort, this clinical prediction rule has shown to be extremely sensitive to identify children at risk of hospital admission for a serious infection in general practice, making it suitable for ruling out.},
  articleno    = {e008657},
  author       = {Verbakel, Jan and Lemiengre, Marieke and De Burghgraeve, Tine and De Sutter, An and Aertgeerts, Bert and Bullens, Dominique MA and Shinkins, Bethany and Van den Bruel, Ann and Buntinx, Frank},
  issn         = {2044-6055},
  journal      = {BMJ OPEN},
  keywords     = {FEBRILE CHILDREN,BACTERIAL-INFECTION,YOUNG-CHILDREN,SIGNS,SYMPTOMS,COHORT,FEVER},
  language     = {eng},
  number       = {8},
  pages        = {8},
  title        = {Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care},
  url          = {http://dx.doi.org/10.1136/bmjopen-2015-008657},
  volume       = {5},
  year         = {2015},
}

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