摘要
目的探讨改良早期预警评分联合血糖水平变化预测急诊患者危重程度和预后的应用价值。方法将我院201i年1月一2013年12月急诊科接诊的4269例患者随机分为实验组2233例、对照组2036例,对照组患者进行改良早期预警评分,实验组患者进行改良早期预警评分联合血糖水平变化评分,追踪送入专科病房和重症监护病房患者的预后,观察两种方法预测患者危重程度和预后的准确率。结果4269例患者中,门诊治疗好转离院968例(22.7%)、留院观察1561例(36.6%)、专科病房住院1259例(29.50)、ICU住院312例(7.31%)、抢救无效死亡169例(3.96%)。以入住重症监护病房及院前抢救为预测指标,实验组与对照组ROC曲线下面积差异有统计学意义(P〈0.05);以死亡为预测指标,实验组与对照组ROC曲线下面积差异有统计学意义(P〈0.05)。结论改良早期预警评分联合血糖水平变化综合评分,能更好地反映危重患者的病情、快速评估其危重级别,值得临床推广应用。
Objective To investigate the applicated value of modified early warning score combined with blood glucose levels in the assessment of diseases severity and prognosis among emergency patients. Methods 4 269 emergency patients in our hospital from Jan 2011 to Dec 2013 were randomly divided into the observation group and the control group. The control group were evaluated by the modified early warning score, and the observation group were evaluated by the modified early warning score combined with blood glucose levels. The prognosis of the patients were tracked after they were transfered into the wards and the ICU. The accuracy of the assessment on the diseases severity and prognosis were evaluated. Results Among all 4 269 cases, 968(22.7%) recovered from outpatient service, 1 561(36.6%) waited for watching, 1 259(29.5%) transfered into the wards, 312(7.31%) got into the ICU, and 169(3.96%) died. The areas of ROC between the observation group and the control group showed statistically significant difference according to the cases in the ICU and the rescue pre-hosptial(P〈0.05). The areas of ROC between the observation group and the control group showed statistically significant difference according to the death(P〈0.05). Conclusion The combination of modified early warning score and blood glucose levels could predict the severity of diseases and the prognosis of emergency patients more accurately, and worth to be promoted in the clinical,
出处
《中国实用乡村医生杂志》
2014年第13期29-31,共3页
Chinese Practical Journal of Rural Doctor
关键词
改良早期预警评分
血糖
急诊患者
危重程度
预后
预测
modified early warning score
blood glucose levels
emergency patients
diseases severity
prognosis
prediction