Al-Salman Jameela, Sanad Salem Alsabea Aysha, Alkhawaja Safa, Al Balooshi Alia Mohammed, Alalawi Maryam, Abdulkarim Ebrahim Batool, Hasan Zainaldeen Jenan, Al Sayyad Adel Salman
Senior Infectious Disease consultant King Hamad American medical Mission Salmaniya medical complex Associate professor of medicine, Arabian Gulf University.
Emergency medicine resident, Emergency Department, Salmaniya medical complex.
J Infect Public Health. 2023 Nov;16(11):1773-1777. doi: 10.1016/j.jiph.2023.09.002. Epub 2023 Sep 9.
While most COVID-19 cases have uncomplicated infection, a small proportion has the potential to develop life-threatening disease, as such development of a prediction tool using patients baseline characteristics at the time of diagnosis should aid in early identification of high-risk groups and devise pertinent management. Hence, we set up this retrospective study to determine preadmission triaging tool to predict the development of severe COVID-19 in the Kingdom of Bahrain MATERIALS AND METHODS: A retrospective study was conducted from 1 September 2020 to 30 November 2020 with enrolment of all SARS-CoV-2 PCR-confirmed persons aged ≥ 14 years who attended Al-Shamil Field Hospital (SFH) in the Kingdom of Bahrain for triaging and assessment with recording of the following parameters: systolic blood pressure, heart rate, respiratory rate, temperature, the alert, verbal, pain, unresponsive neurological score, age, oxygen saturation, comorbidities, Body Mass Index (BMI), duration of symptoms and living with immunocompromised populations to develop our local adjusted MEWS as predictor for ICU admission & for consideration of suitable isolation at home. Follow up data of all patients was obtained from the electronic medical records system including CXR findings, treatments/medications received, need of oxygen supplements /intubation, needs of ICU care, and the outcome (death /discharged alive) IBM SPSS statistic version 21 program was used for data analysis.
Our study showed that using the locally developed adjusted MEWS score, there was an significant association between high value of this adjusted MEWS score and abnormal radiographic finding (49.7 % Vs. 17 % for patients with high score Vs. those with low score respectively). Out of the 181 patients with high scores on adjusted MEWS; 38.7 % required oxygen via nasal cannula, 14.4 % required face mask and 8.3 % non-rebreather mask; this proportion was significantly higher than their counterpart patients who score low on adjusted MEWS (20.9 %, 7.7 %, 4.8 %respectively) with statistically significance difference between the two groups (p value of 0.00, 0.00,.004 respectively) Requirement of ICU admission was significantly higher among patients with high score in comparison to those with low score (14.4 % vs. 3 %) with significant p value (0.00) But higher score value was not associated significantly with increase mortality rate among COVID patients.
Development of our new Adjusted MEWS score system by adding the additional elements of age, oxygen saturation, comorbidities, Body Mass Index (BMI) and duration of symptoms found to be very useful predictor tool for preadmission triaging of COVID patients based on their risk assessment to help clinician to decide on the appropriate placement to different level of isolation facilities.
虽然大多数新冠病毒病(COVID-19)病例感染情况不复杂,但一小部分有发展为危及生命疾病的可能,因此开发一种利用患者诊断时基线特征的预测工具应有助于早期识别高危人群并制定相关管理措施。因此,我们开展了这项回顾性研究,以确定用于预测巴林王国严重COVID-19发展的入院前分诊工具。
于2020年9月1日至2020年11月30日进行了一项回顾性研究,纳入所有年龄≥14岁、经严重急性呼吸综合征冠状病毒2(SARS-CoV-2)聚合酶链反应(PCR)确诊、前往巴林王国沙米尔野战医院(SFH)进行分诊和评估的患者,并记录以下参数:收缩压、心率、呼吸频率、体温、警觉、语言、疼痛、无反应神经学评分、年龄、血氧饱和度、合并症、体重指数(BMI)、症状持续时间以及是否与免疫功能低下人群共同生活,以制定我们本地调整后的改良早期预警评分(MEWS),作为重症监护病房(ICU)入院预测指标以及考虑在家中进行适当隔离的依据。所有患者的随访数据均从电子病历系统中获取,包括胸部X线检查结果、接受的治疗/药物、是否需要吸氧/插管、是否需要ICU护理以及结局(死亡/存活出院)。使用IBM SPSS统计软件21版程序进行数据分析。
我们的研究表明,使用本地开发的调整后MEWS评分,该调整后MEWS评分高值与异常影像学表现之间存在显著关联(高分患者与低分患者的异常影像学表现分别为49.7%对17%)。在181例调整后MEWS评分高的患者中,38.7%需要经鼻导管吸氧,14.4%需要面罩吸氧,8.3%需要非重复呼吸面罩吸氧;这一比例显著高于调整后MEWS评分低的对应患者(分别为20.9%、7.7%、4.8%),两组之间存在统计学显著差异(p值分别为0.00、0.00、0.004)。高分患者的ICU入院需求显著高于低分患者(14.4%对3%),p值显著(0.00)。但较高的评分值与COVID患者死亡率增加无显著关联。
通过添加年龄、血氧饱和度、合并症、体重指数(BMI)和症状持续时间等额外因素开发的新调整后MEWS评分系统,被发现是基于风险评估对COVID患者进行入院前分诊的非常有用的预测工具,有助于临床医生决定将患者安置到不同级别的隔离设施中。