西印度一家三级医院对COVID-19患者分诊的影响:对一系列病例的回顾性分析

Ashish Jain, P. Rijhwani, S. Jain, Ravi Jain, Anchin Kalia, Pallaavi Goel, Nimish Mathur, Anand B. Jain, Divyansh Gupta
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引用次数: 1

摘要

导言:评估2019冠状病毒病(COVID-19)的临床严重程度并进行适当的护理分级无疑是成功管理COVID-19患者的关键因素之一。在结束的大流行浪潮期间,按照当局规定的既定标准对病例进行了分类和治疗。其他分诊标准也包括在当代国际指南中,但这一假设从未得到检验,是否有哪一套比另一套更好。材料与方法:本研究为165例COVID-19死亡患者的病例系列。所有患者根据临床疾病严重程度进行分类,并在确诊后由入院医生决定进入指定的护理区。我们从患者医疗记录中收集回顾性数据,并分析病史、合并症、血液学调查、器官功能检查、胸部计算机断层扫描和护理点生物标志物检测(d -二聚体、降钙素原、NT-proBNP、Trop-T)。采用XLstat软件对这些数据进行分析,比较病房和ICU患者各变量的差异。结果:在对死亡患者病例系列的分析中,我们发现住院患者和ICU患者在初始人口统计学和生物标志物变量以及危险因素方面没有显著差异。糖尿病是最常见的合并症。病区和ICU的死亡率(5.89 vs 6.67%, p值:0.44)在两个队列中也相似。结论:在这个病例系列中,我们可以得出结论,两个队列在入院时在人口统计学和实验室参数概况方面具有可比性。临床意义:该分析使我们得出结论,在该地区第二波疫情到来之前,我们需要适当修改现有的COVID-19患者“分诊标准”。
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Impact of Triaging for COVID-19 Patients in a Tertiary Care Hospital in West India: A Retrospective Analysis of a Case Series
Ab s t r Ac t Introduction: Assessing the clinical severity of coronavirus disease-2019 (COVID-19) and triaging to appropriate levels of care is certainly one of the key elements in the success of managing COVID-19 patients. During the concluded wave of the pandemic, cases were categorized and cared for with set criteria prescribed by authorities. Other triaging criteria were included in contemporary international guidelines, but this hypothesis was never tested if anyone set is ever better than the other. Materials and methods: This is a case series of 165 deceased patients of COVID-19. All patients were categorized as per clinical disease severity and admitted to the designated care area after confirmation of SARS-CoV-2 infection as decided by the admitting doctors. We collected retrospective data from patient medical records and analyzed for medical history, comorbidity profiles, hematology investigations, organ function tests, computed tomography of the thorax, and point-of-care biomarker test (D-dimer, procalcitonin, NT-proBNP, Trop-T). These data were analyzed to compare the differences between the variables of ward and ICU patients by using XLstat software. Results: In this analysis of deceased patients’ case series, we found that there was no significant difference among the patients admitted to ward and ICU for initial demographic and biomarker variables and risk factors. Diabetes was the most commonly found comorbidity. The mortality rate among the ward and ICU (5.89 vs 6.67%, p value: 0.44) was also similar among both the cohorts. Conclusion: In this case series, we could conclude that both the cohorts were comparable at admission on demographic and laboratory parameter profile. Clinical significance: This analysis led us to the conclusion that our existing “triage criteria” for COVID-19 patients will need appropriate modification before the second wave sets in the region.
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