OBJECTIVE: Most inpatient pediatric arrests are preventable by early recognition/treatment of deterioration. Children with cardiac disease have the highest arrest rates; however, early warning scoring systems have not been validated in this population. The objective of this study was to validate the Cardiac Children's Hospital Early Warning Score (C-CHEWS) tool in inpatient pediatric cardiac patients. The associated escalation of care algorithm directs: routine care (score 0-2), increased assessment/intervention (3-4), or cardiac intensive care unit (CICU) consult/transfer (≥5). DESIGN: Sensitivity and specificity were estimated based on retrospective review of patients that experienced unplanned CICU transfer/arrest (n = 64) and a comparison sample (n = 248) of admissions. The previously validated Pediatric Early Warning Score (PEWS) tool was used for comparison. Patients' highest C-CHEWS scores were compared with calculated PEWS scores. Area under the receiver operating characteristic (AUROC) curve was calculated for PEWS and C-CHEWS to measure discrimination. RESULTS: The AUROC curve for C-CHEWS was 0.917 compared with PEWS 0.785 (P < .001). The algorithm AUROC curve was 0.902 vs. PEWS of 0.782. C-CHEWS algorithm sensitivity was 96.9 (score ≥ 2), 79.7 (≥4), and 67.2 (≥5) vs. PEWS of 81.1(≥2), 37.5 (≥4), and 23.4 (≥5). C-CHEWS specificity was 58.1 (≥2), 85.5 (≥4), and 93.6 (≥5) vs. PEWS of 81.1 (≥2), 94.8 (≥4) and 97.6 (≥5). Lead time of elevated C-CHEWS scores (≥2) was a median of 9.25 hours prior to event vs. PEWS, which was 2.25 hours and lead time for critical C-CHEWS scores (≥5) was 2 hours vs. 0 hours for PEWS (P < .001). CONCLUSIONS: C-CHEWS has excellent discrimination to identify deterioration in children with cardiac disease and performed significantly better than PEWS both as an ordinal variable and when choosing cut points to maximize AUROC. C-CHEWS has a higher sensitivity than PEWS at all cut points.
OBJECTIVE: Most inpatient pediatric arrests are preventable by early recognition/treatment of deterioration. Children with cardiac disease have the highest arrest rates; however, early warning scoring systems have not been validated in this population. The objective of this study was to validate the Cardiac Children's Hospital Early Warning Score (C-CHEWS) tool in inpatient pediatric cardiac patients. The associated escalation of care algorithm directs: routine care (score 0-2), increased assessment/intervention (3-4), or cardiac intensive care unit (CICU) consult/transfer (≥5). DESIGN: Sensitivity and specificity were estimated based on retrospective review of patients that experienced unplanned CICU transfer/arrest (n = 64) and a comparison sample (n = 248) of admissions. The previously validated Pediatric Early Warning Score (PEWS) tool was used for comparison. Patients' highest C-CHEWS scores were compared with calculated PEWS scores. Area under the receiver operating characteristic (AUROC) curve was calculated for PEWS and C-CHEWS to measure discrimination. RESULTS: The AUROC curve for C-CHEWS was 0.917 compared with PEWS 0.785 (P < .001). The algorithm AUROC curve was 0.902 vs. PEWS of 0.782. C-CHEWS algorithm sensitivity was 96.9 (score ≥ 2), 79.7 (≥4), and 67.2 (≥5) vs. PEWS of 81.1(≥2), 37.5 (≥4), and 23.4 (≥5). C-CHEWS specificity was 58.1 (≥2), 85.5 (≥4), and 93.6 (≥5) vs. PEWS of 81.1 (≥2), 94.8 (≥4) and 97.6 (≥5). Lead time of elevated C-CHEWS scores (≥2) was a median of 9.25 hours prior to event vs. PEWS, which was 2.25 hours and lead time for critical C-CHEWS scores (≥5) was 2 hours vs. 0 hours for PEWS (P < .001). CONCLUSIONS:C-CHEWS has excellent discrimination to identify deterioration in children with cardiac disease and performed significantly better than PEWS both as an ordinal variable and when choosing cut points to maximize AUROC. C-CHEWS has a higher sensitivity than PEWS at all cut points.
Authors: Craig G Rusin; Sebastian I Acosta; Lara S Shekerdemian; Eric L Vu; Aarti C Bavare; Risa B Myers; Lance W Patterson; Ken M Brady; Daniel J Penny Journal: J Thorac Cardiovasc Surg Date: 2016-04-16 Impact factor: 5.209
Authors: Juliana de Oliveira Freitas Miranda; Climene Laura de Camargo; Carlito Lopes Nascimento; Daniel Sales Portela; Alan Monaghan Journal: Rev Lat Am Enfermagem Date: 2017-07-10
Authors: Rob Trubey; Chao Huang; Fiona V Lugg-Widger; Kerenza Hood; Davina Allen; Dawn Edwards; David Lacy; Amy Lloyd; Mala Mann; Brendan Mason; Alison Oliver; Damian Roland; Gerri Sefton; Richard Skone; Emma Thomas-Jones; Lyvonne N Tume; Colin Powell Journal: BMJ Open Date: 2019-05-05 Impact factor: 2.692
Authors: Javier Urbano; Jorge López; Rafael González; Sarah N Fernández; María José Solana; Blanca Toledo; Ángel Carrillo; Jesús López-Herce Journal: Intensive Care Med Exp Date: 2016-06-03