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Identification of delayed diagnosis of paediatric appendicitis in administrative data: a multicentre retrospective validation study.
Michelson, Kenneth A; Bachur, Richard G; Dart, Arianna H; Chaudhari, Pradip P; Cruz, Andrea T; Grubenhoff, Joseph A; Reeves, Scott D; Monuteaux, Michael C; Finkelstein, Jonathan A.
Afiliação
  • Michelson KA; Division of Emergency Medicine, Boston Children's Hospital, Boston, MA, USA kenneth.michelson@childrens.harvard.edu.
  • Bachur RG; Division of Emergency Medicine, Boston Children's Hospital, Boston, MA, USA.
  • Dart AH; Division of Emergency Medicine, Boston Children's Hospital, Boston, MA, USA.
  • Chaudhari PP; Division of Emergency and Transport Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA.
  • Cruz AT; Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
  • Grubenhoff JA; Section of Pediatric Emergency Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
  • Reeves SD; Children's Hospital Colorado, Aurora, CO, USA.
  • Monuteaux MC; Division of Pediatric Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
  • Finkelstein JA; Division of Emergency Medicine, Boston Children's Hospital, Boston, MA, USA.
BMJ Open ; 13(2): e064852, 2023 02 28.
Article em En | MEDLINE | ID: mdl-36854600
OBJECTIVE: To derive and validate a tool that retrospectively identifies delayed diagnosis of appendicitis in administrative data with high accuracy. DESIGN: Cross-sectional study. SETTING: Five paediatric emergency departments (EDs). PARTICIPANTS: 669 patients under 21 years old with possible delayed diagnosis of appendicitis, defined as two ED encounters within 7 days, the second with appendicitis. OUTCOME: Delayed diagnosis was defined as appendicitis being present but not diagnosed at the first ED encounter based on standardised record review. The cohort was split into derivation (2/3) and validation (1/3) groups. We derived a prediction rule using logistic regression, with covariates including variables obtainable only from administrative data. The resulting trigger tool was applied to the validation group to determine area under the curve (AUC). Test characteristics were determined at two predicted probability thresholds. RESULTS: Delayed diagnosis occurred in 471 (70.4%) patients. The tool had an AUC of 0.892 (95% CI 0.858 to 0.925) in the derivation group and 0.859 (95% CI 0.806 to 0.912) in the validation group. The positive predictive value (PPV) for delay at a maximal accuracy threshold was 84.7% (95% CI 78.2% to 89.8%) and identified 87.3% of delayed cases. The PPV at a stricter threshold was 94.9% (95% CI 87.4% to 98.6%) and identified 46.8% of delayed cases. CONCLUSIONS: This tool accurately identified delayed diagnosis of appendicitis. It may be used to screen for potential missed diagnoses or to specifically identify a cohort of children with delayed diagnosis.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Apendicite Tipo de estudo: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Child / Humans Idioma: En Revista: BMJ Open Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Apendicite Tipo de estudo: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Child / Humans Idioma: En Revista: BMJ Open Ano de publicação: 2023 Tipo de documento: Article