Ebrahimian Abbasali, Ghasemian-Nik Hossein, Ghorbani Raheb, Fakhr-Movahedi Ali
Nursing Care Research Center, Semnan University of Medical Sciences, Semnan, Iran.
Student Research Committee, Nursing and Midwifery school, Semnan University of Medical Sciences, Semnan, Iran.
Indian J Crit Care Med. 2018 Aug;22(8):575-579. doi: 10.4103/ijccm.IJCCM_47_18.
The capacity completeness are one of the serious problems in the bed's managements of the critical care units in a crisis and disaster situation. Reverse triage can help to hospital surge capacity in this situations.
The aim of this study was to develop a reverse triage system based on Modified Sequential Organ Failure Assessment (MSOFA) for increasing critical care surge capacity.
This study was a prospective design that performed on the medical patients in critical care unit.
The MSOFA score for each patient was calculated in admission time and be continued until discharging time from critical care unit.
The Cox regression method was used to determine the relative risk values. At last, the patients were divided into three levels for reverse triage.
Four hundred and twenty patients were participated in this study. The mean of patients' MSOFA scores in the 1 day of admission in Critical Care was 5.40 ± 3.8. The relative risk of internal patients discharge from critical care was (8.2%). Death relative risks were <25%, higher than 70% and between 25.1% and 69.9% for three color level of green, black, and red, respectively.
The MSOFA scores can contribute to the design a leveling system for discharging patients from critical care unit. Based on this system, the members of the caring team can predict the final health status of the patient.
在危机和灾难情况下，重症监护病房床位管理中的容量完整性是严重问题之一。逆向分诊有助于在这种情况下提高医院的应对能力。
本研究的目的是开发一种基于改良序贯器官衰竭评估（MSOFA）的逆向分诊系统，以提高重症监护应对能力。
本研究是一项针对重症监护病房内科患者的前瞻性设计。
在患者入院时计算每位患者的MSOFA评分，并持续至其从重症监护病房出院。
采用Cox回归方法确定相对风险值。最后，将患者分为三个级别进行逆向分诊。
420名患者参与了本研究。重症监护第1天患者的MSOFA评分均值为5.40±3.8。重症监护病房内患者出院的相对风险为（8.2%）。绿色、黑色和红色三个颜色级别的死亡相对风险分别<25%、高于70%和介于25.1%至69.9%之间。
MSOFA评分有助于设计一种用于重症监护病房患者出院的分级系统。基于该系统，护理团队成员可以预测患者的最终健康状况。
