Teresa A Williams1, Hideo Tohira2, Judith Finn3, Gavin D Perkins4, Kwok M Ho5. 1. Prehospital Resuscitation and Emergency Care Research Unit, School of Nursing, Midwifery and Paramedicine, Curtin University, GPO Box U1987, Perth, WA, Australia; St John Ambulance Western Australia, Belmont 6104, WA, Australia; Department of Intensive Care, Royal Perth Hospital, Perth, WA, Australia; Discipline of Emergency Medicine, University of Western Australia, Perth, WA, Australia. Electronic address: Teresa.Williams@curtin.edu.au. 2. Prehospital Resuscitation and Emergency Care Research Unit, School of Nursing, Midwifery and Paramedicine, Curtin University, GPO Box U1987, Perth, WA, Australia; Discipline of Emergency Medicine, University of Western Australia, Perth, WA, Australia. Electronic address: hideo.tohira@curtin.edu.au. 3. Prehospital Resuscitation and Emergency Care Research Unit, School of Nursing, Midwifery and Paramedicine, Curtin University, GPO Box U1987, Perth, WA, Australia; St John Ambulance Western Australia, Belmont 6104, WA, Australia; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia. Electronic address: Judith.Finn@curtin.edu.au. 4. Critical Care Medicine, Warwick Medical School, University of Warwick, Coventry, UK; Heart of England NHS Foundation Trust, Bordesley Green East, Birmingham, UK. Electronic address: G.D.Perkins@warwick.ac.uk. 5. Department of Intensive Care, Royal Perth Hospital, Perth, WA, Australia; School of Population Health, University of Western Australia, Perth, WA, Australia. Electronic address: kwok.ho@health.wa.gov.au.
Abstract
AIM: To examine whether early warning scores (EWS) can accurately predict critical illness in the prehospital setting and affect patient outcomes. METHODS: We searched bibliographic databases for comparative studies that examined prehospital EWS for patients transported by ambulance in the prehospital setting. The ability of the different EWS, including pre-alert protocols and physiological-based EWS, to predict critical illness (sensitivity, odds ratio [OR], area under receiver operating characteristic [AUROC] curves) and hospital mortality was summarised. Study quality was assessed using the Newcastle-Ottawa Scale. RESULTS: Eight studies were identified. Two studies compared the use of EWS to standard practice using clinical judgement alone to identify critical illness: the pooled diagnostic OR and summary AUROC for EWS were 10.9 (95%CI 4.2-27.9) and 0.78 (95%CI 0.74-0.82), respectively. A study of 144,913 patients reported age and physiological variables predictive of critical illness: AUROC in the independent validation sample was 0.77, 95% CI 0.76-0.78. The high-risk patients stratified by the national early warning score (NEWS) were significantly associated with a higher risk of both mortality and intensive care admission. Data on comparing between different EWS were limited; the Prehospital Early Sepsis Detection (PRESEP) score predicted occurrence of sepsis better than the Modified EWS (AUROC 0.93 versus 0.77, respectively). CONCLUSION: EWS in the prehospital setting appeared useful in predicting clinically important outcomes, but the significant heterogeneity between different EWS suggests that these positive promising findings may not be generalisable. Adequately powered prospective studies are needed to identify the EWS best suited to the prehospital setting.
AIM: To examine whether early warning scores (EWS) can accurately predict critical illness in the prehospital setting and affect patient outcomes. METHODS: We searched bibliographic databases for comparative studies that examined prehospital EWS for patients transported by ambulance in the prehospital setting. The ability of the different EWS, including pre-alert protocols and physiological-based EWS, to predict critical illness (sensitivity, odds ratio [OR], area under receiver operating characteristic [AUROC] curves) and hospital mortality was summarised. Study quality was assessed using the Newcastle-Ottawa Scale. RESULTS: Eight studies were identified. Two studies compared the use of EWS to standard practice using clinical judgement alone to identify critical illness: the pooled diagnostic OR and summary AUROC for EWS were 10.9 (95%CI 4.2-27.9) and 0.78 (95%CI 0.74-0.82), respectively. A study of 144,913 patients reported age and physiological variables predictive of critical illness: AUROC in the independent validation sample was 0.77, 95% CI 0.76-0.78. The high-risk patients stratified by the national early warning score (NEWS) were significantly associated with a higher risk of both mortality and intensive care admission. Data on comparing between different EWS were limited; the Prehospital Early Sepsis Detection (PRESEP) score predicted occurrence of sepsis better than the Modified EWS (AUROC 0.93 versus 0.77, respectively). CONCLUSION: EWS in the prehospital setting appeared useful in predicting clinically important outcomes, but the significant heterogeneity between different EWS suggests that these positive promising findings may not be generalisable. Adequately powered prospective studies are needed to identify the EWS best suited to the prehospital setting.
Authors: Benjamin Vandendriessche; Mustafa Abas; Thomas E Dick; Kenneth A Loparo; Frank J Jacono Journal: IEEE Trans Biomed Eng Date: 2017-03-17 Impact factor: 4.538
Authors: A Redondo-González; M Varela-Patiño; J Álvarez-Manzanares; J R Oliva-Ramos; R López-Izquierdo; C Ramos-Sánchez; J M Eiros Journal: Rev Esp Quimioter Date: 2018-06-28 Impact factor: 1.553
Authors: Francisco Martín-Rodríguez; Raúl López-Izquierdo; Carlos Del Pozo Vegas; Juan F Delgado-Benito; Carmen Del Pozo Pérez; Virginia Carbajosa Rodríguez; Agustín Mayo Iscar; José Luis Martín-Conty; Carlos Escudero Cuadrillero; Miguel A Castro-Villamor Journal: Emerg Med Int Date: 2019-07-01 Impact factor: 1.112