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生化参数作为重症 COVID-19 患者的预后标志物

Biochemical Parameters as Prognostic Markers in Severely Ill COVID-19 Patients.

作者信息

Pitamberwale Anjali, Mahmood Tariq, Ansari Azmat Kamal, Ansari Shabana Andleeb, Limgaokar Kirti, Singh Lalit, Karki Geeta

机构信息

Biochemistry, Fergusson College, Pune, Maharashtra, IND.

Biochemistry, Teerthankar Mahaveer Medical College and Research Centre, Moradabad, Uttar Pradesh, IND.

出版信息

Cureus. 2022 Aug 30;14(8):e28594. doi: 10.7759/cureus.28594. eCollection 2022 Aug.

Abstract

Background Prognostication plays a pivotal role in critical care medicine. Its importance is indisputable in the management of coronavirus disease 2019 (COVID-19), as the presentation of this disease may vary from docile, self-limiting symptoms to lethal conditions. Amid the COVID-19 pandemic, much emphasis was initially placed on molecular and serological testing. However, it was realized later that routine laboratory tests also provide key information in terms of the severity of the disease and thus could be used to predict the outcome of these patients. Methodology The aim of our study was to evaluate the biochemical parameters as prognostic markers in severely ill COVID-19 patients. We carried out a retrospective, case-control study. The study population was comprised of all severely ill COVID-19 patients admitted between October 2020 and January 2021 at our level 3 COVID hospital. Cases were defined as the patients who expired despite treatment and all resuscitative measures as per the standard operating procedures (SOPs) of our COVID intensive care unit (ICU) while controls were defined as the patients that were transferred out of the COVID ICU for further recovery. The detailed history, findings of physical examination, vitals recorded by point of care testing (POCT) devices at our ICU, clinical diagnosis, and the results of the biochemical analysis were recorded in a specially designed pro forma. The biochemical parameters recorded at the time of admission were compared between the groups of controls and cases in order to evaluate their role as predictors of mortality using appropriate statistical methods. P-values less than 0.05 were considered statistically significant. For all the parameters that showed a statistically significant difference, receiver operating characteristics (ROC) analysis was done to assess the utility of biochemical parameters as predictors of mortality or survival. Areas under the curve (AUCs) of 0.6 to 0.7, 0.7 to 0.8, 0.8 to 0.9, and >0.9 were considered acceptable, fair, good, and excellent for discrimination, respectively. Results Of the 178 severely ill COVID-19 patients enrolled in the study, 86 were controls and 92 were cases (52% mortality). Serum urea (p<0.0001), creatinine (p=0.0019), aspartate transaminase (AST) (p=0.0104), lactate dehydrogenase (LDH) (p=0.0001), procalcitonin (PCT) (p=0.0344), and interleukin 6 (IL-6) (p=0.0311) levels were significantly higher (p<0.05), while total protein (p=0.0086), albumin (p<0.0001), and indirect bilirubin (p=0.0147) levels were significantly lower (p<0.05) in cases as compared to controls. The difference was statistically insignificant (p>0.05) for serum sodium, potassium, total and direct bilirubin, globulin, alanine transaminase (ALT), alkaline phosphatase (ALP), D-dimer, and ferritin. On ROC analysis, urea was fair (AUC=0.721), creatinine (AUC=0.698) and IL-6 (AUC=0.698) were acceptable predictors of mortality, while albumin (AUC=0.698) was an acceptable predictor of survival in severely ill COVID-19 patients during their intensive care stay. Conclusion Understanding the pathophysiological changes associated with the severity of COVID-19 in terms of an alteration of biochemical parameters is a pressing priority. Our study highlights the importance of routine laboratory tests in predicting outcomes in severely ill COVID-19 patients.

摘要

背景

预后评估在重症医学中起着关键作用。其重要性在2019冠状病毒病(COVID-19)的管理中无可争议,因为这种疾病的表现可能从温和的、自限性症状到致命情况不等。在COVID-19大流行期间,最初非常强调分子和血清学检测。然而,后来人们意识到常规实验室检查在疾病严重程度方面也提供了关键信息,因此可用于预测这些患者的预后。

方法

我们研究的目的是评估生化参数作为重症COVID-19患者预后标志物的作用。我们进行了一项回顾性病例对照研究。研究人群包括2020年10月至2021年1月期间在我们的三级COVID医院收治的所有重症COVID-19患者。病例定义为尽管按照我们COVID重症监护病房(ICU)的标准操作程序(SOPs)进行了治疗和所有复苏措施仍死亡的患者,而对照定义为转出COVID ICU以进一步康复的患者。详细病史、体格检查结果、我们ICU中即时检验(POCT)设备记录的生命体征、临床诊断以及生化分析结果记录在专门设计的表格中。比较对照组和病例组入院时记录的生化参数,以便使用适当的统计方法评估它们作为死亡率预测指标的作用。P值小于0.05被认为具有统计学意义。对于所有显示出统计学显著差异的参数,进行了受试者工作特征(ROC)分析,以评估生化参数作为死亡率或生存率预测指标的效用。曲线下面积(AUC)为0.6至0.7、0.7至0.8、0.8至0.9和>0.9分别被认为在区分方面是可接受的、一般的、良好的和优秀的。

结果

在纳入研究的178例重症COVID-19患者中,86例为对照组,92例为病例组(死亡率52%)。与对照组相比,病例组的血清尿素(p<0.0001)、肌酐(p=0.0019)、天冬氨酸转氨酶(AST)(p=0.0104)、乳酸脱氢酶(LDH)(p=0.0001)、降钙素原(PCT)(p=0.0344)和白细胞介素6(IL-6)(p=0.0311)水平显著更高(p<0.05),而总蛋白(p=0.0086)、白蛋白(p<0.0001)和间接胆红素(p=0.0147)水平显著更低(p<0.05)。血清钠、钾、总胆红素和直接胆红素、球蛋白丙氨酸转氨酶(ALT)、碱性磷酸酶(ALP)、D-二聚体和铁蛋白的差异无统计学意义(p>0.05)。在ROC分析中,尿素是一般的死亡率预测指标(AUC=0.721),肌酐(AUC=0.698)和IL-6(AUC=0.698)是可接受的死亡率预测指标,而白蛋白(AUC=0.698)是重症COVID-19患者在重症监护期间生存的可接受预测指标。

结论

从生化参数改变的角度了解与COVID-19严重程度相关的病理生理变化是当务之急。我们的研究强调了常规实验室检查在预测重症COVID-19患者预后方面的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0a2/9521622/8bdda7b30380/cureus-0014-00000028594-i01.jpg

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