The PAWS score: validation of an early warning scoring system for the initial assessment of children in the emergency department

被引:74
|
作者
Egdell, P. [1 ]
Finlay, L. [2 ]
Pedley, D. K. [3 ]
机构
[1] Sunderland Royal Hosp, Emergency Dept, Sunderland SR4 7TP, Tyne & Wear, England
[2] Dumfries & Galloway Royal Infirm, Dept Paediat, Dumfries, Scotland
[3] Dumfries & Galloway Royal Infirm, Emergency Dept, Dumfries, Scotland
关键词
D O I
10.1136/emj.2007.054965
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Objective: To devise a physiology-based scoring system for assessment of children presenting to the emergency department (ED) and to validate the system retrospectively. Study design: Age-dependent physiological parameters designed to reflect the cardiovascular, respiratory and neurological status of patients presenting to the ED were included in a scoring system called the Paediatric Advanced Warning Score (PAWS). A retrospective pilot evaluation was performed to validate PAWS. Setting and patients: PAWS scores were calculated retrospectively for 46 consecutive children who required admission from the ED to the paediatric intensive care unit (PICU) and for 49 control children who were admitted from the ED to the general paediatric ward. Main outcome measures: To validate the PAWS score, we determined if this score was able to identify patients who require admission to the PICU and were therefore significantly unwell. Results: The PAWS score area under the receiver operating characteristic curve was 0.86. Using a trigger score of 3 or above, PAWS was able to identify patients requiring PICU admission with a sensitivity of 70% and a specificity of 90%. Conclusions: This pilot study has shown that a physiology-based scoring system can help to identify children in the ED requiring PICU admission. Future prospective validation of PAWS is necessary to assess its ability to identify all children in need of urgent assessment in the ED.
引用
收藏
页码:745 / 749
页数:5
相关论文
共 50 条
  • [41] The REDS score: a new scoring system to risk-stratify emergency department suspected sepsis: a derivation and validation study
    Sivayoham, Narani
    Blake, Lesley A.
    Tharimoopantavida, Shafi E.
    Chughtai, Saad
    Hussain, Adil N.
    Cecconi, Maurizio
    Rhodes, Andrew
    [J]. BMJ OPEN, 2019, 9 (08):
  • [42] Lactate improves the predictive ability of the National Early Warning Score 2 in the emergency department
    Durantez-Fernandez, Carlos
    Martin-Conty, Jose L.
    Polonio-Lopez, Begona
    Castro Villamor, Miguel Angel
    Maestre-Miquel, Clara
    Vinuela, Antonio
    Lopez-Izquierdo, Raul
    Mordillo-Mateos, Laura
    Fernandez Mendez, Felipe
    Jorge Soto, Cristina
    Martin-Rodriguez, Francisco
    [J]. AUSTRALIAN CRITICAL CARE, 2022, 35 (06) : 677 - 683
  • [43] Implementing an electronic observation and early warning score chart in the emergency department: a feasibility study
    Pullinger, Richard
    Wilson, Sarah
    Way, Rob
    Santos, Mauro
    Wong, David
    Clifton, David
    Birks, Jacqueline
    Tarassenko, Lionel
    [J]. EUROPEAN JOURNAL OF EMERGENCY MEDICINE, 2017, 24 (06) : E11 - E16
  • [44] Prediction of Pediatric Patient Admission/Discharge in the Emergency Department Irish Pediatric Early Warning Score, Pediatric Observation Priority Score, and Irish Children's Triage System
    Hannon, Colm
    Roland, Damian
    O'Sullivan, Ronan
    [J]. PEDIATRIC EMERGENCY CARE, 2022, 38 (06) : E1320 - E1326
  • [45] Early clinical outcome prediction based on the initial National Early Warning Score plus Lactate (News plus L) Score among adult emergency department patients
    Jo, Sion
    Jeong, Taeoh
    Park, Boyoung
    [J]. EMERGENCY MEDICINE JOURNAL, 2023, 40 (06) : 444 - 450
  • [46] The uptake of an early warning system in an Australian emergency department: a pilot study
    Considine, Julie
    Lucas, Elspeth
    Wunderlich, Bart
    [J]. CRITICAL CARE AND RESUSCITATION, 2012, 14 (02) : 135 - 141
  • [47] An Early Warning System for Patients in Emergency Department based on Machine Learning
    Hsu, Ying-Feng
    Matsuoka, Morito
    [J]. 2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2021), 2021, : 1196 - 1201
  • [48] Use of a Modified Early Warning Score to Predict Early Clinical Deterioration in Admitted Emergency Department Patients
    Glick, J.
    Harrington, D.
    Greenwood, J.
    Shofer, F.
    [J]. ANNALS OF EMERGENCY MEDICINE, 2017, 70 (04) : S119 - S119
  • [49] THE USE OF EARLY WARNING SCORES IN THE EMERGENCY DEPARTMENT
    Day, Alison
    Oldroyd, Carol
    [J]. JOURNAL OF EMERGENCY NURSING, 2010, 36 (02) : 154 - 155
  • [50] Early Warning Software for Emergency Department Crowding
    Jalmari Tuominen
    Teemu Koivistoinen
    Juho Kanniainen
    Niku Oksala
    Ari Palomäki
    Antti Roine
    [J]. Journal of Medical Systems, 47