Comparative study between MEWS score, APACHE Ⅱ score and combination of the two scoring systems to predict the emergency medicine prognosis
10.3760/cma.j.issn.1672-7088.2015.03.003
- VernacularTitle:改良早期预警评分、急性生理与慢性健康评分及两评分联合应用预测急诊内科患者预后能力的对比研究
- Author:
Ping LI
;
Lan DING
;
Tingting WEI
;
Ming HOU
- Publication Type:Journal Article
- Keywords:
Modified Early Warning Score;
Acute Physiology and Chronic Health Evaluation;
Prognosis
- From:
Chinese Journal of Practical Nursing
2015;31(3):166-168
- CountryChina
- Language:Chinese
-
Abstract:
Objective We sought to compare the ability of MEWS score,APACHE Ⅱ score and combination of the two scoring systems to predict the prognosis of patients in emergency medical department.Methods During January to March 2014,640 patients in emergency medical department who met the criteria were set as the research object.The patients admission was the starting point for clinic observation.The relevant data were collected for carrying on the MEWS and APACHE Ⅱ ratings,tracking the patients' prognosis.The corresponding predictors for prognosis of patients such as sensitivity,specificity,positive predictive value,negative predictive value and ROC curve by MEWS score,APACHE Ⅱ score and combination of the two scoring systems were compared.Results The area under the receiver operating characteristic curve was 0.93,0.79 and 0.93 with MEWS score,APACHE Ⅱ score and combination of the two scoring systems.The comparison of either of the two scoring systems showed significant difference.When death was named as the prediction factor,the sensitivity,specificity,positive predictive value and negative predictive value were 76.92％,91.70％,51.02％,97.23％ for MEWS score; 83.08％,62.80％,20.15％ and 97.04％ for APACHE Ⅱ score; 92.31％,86.43％,43.48％ and 97.58％ for combination of the two scoring systems.Conclusions Combination of the MEWS and APACHE Ⅱ scoring systems can be used to predict the prognosis of patients in emergency medical department.It posesses high sensitivity,specificity,positive predictive value and negative predictive value,which indicating a high predictive capability.
