Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care.
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...
| Huvudupphovsmän: | , , , , , , , , |
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| Materialtyp: | Journal article |
| Språk: | English |
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BMJ Publishing Group
2015
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| _version_ | 1826302180658774016 |
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| author | Verbakel, J Lemiengre, M De Burghgraeve, T De Sutter, A Aertgeerts, B Bullens, D Shinkins, B Van den Bruel, A Buntinx, F |
| author_facet | Verbakel, J Lemiengre, M De Burghgraeve, T De Sutter, A Aertgeerts, B Bullens, D Shinkins, B Van den Bruel, A Buntinx, F |
| author_sort | Verbakel, J |
| collection | OXFORD |
| description | 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. TRIAL REGISTRATION NUMBER: NCT02024282. |
| first_indexed | 2024-03-07T05:43:39Z |
| format | Journal article |
| id | oxford-uuid:e673aac3-bf84-4ce1-82df-0f9f1ef5355b |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:43:39Z |
| publishDate | 2015 |
| publisher | BMJ Publishing Group |
| record_format | dspace |
| spelling | oxford-uuid:e673aac3-bf84-4ce1-82df-0f9f1ef5355b2022-03-27T10:31:14ZValidating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e673aac3-bf84-4ce1-82df-0f9f1ef5355bEnglishSymplectic Elements at OxfordBMJ Publishing Group2015Verbakel, JLemiengre, MDe Burghgraeve, TDe Sutter, AAertgeerts, BBullens, DShinkins, BVan den Bruel, ABuntinx, FOBJECTIVE: 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. TRIAL REGISTRATION NUMBER: NCT02024282. |
| spellingShingle | Verbakel, J Lemiengre, M De Burghgraeve, T De Sutter, A Aertgeerts, B Bullens, D Shinkins, B Van den Bruel, A Buntinx, F Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. |
| title | Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. |
| title_full | Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. |
| title_fullStr | Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. |
| title_full_unstemmed | Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. |
| title_short | Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care. |
| title_sort | validating a decision tree for serious infection diagnostic accuracy in acutely ill children in ambulatory care |
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