D-Dimer, ferritin, and lactate dehydrogenase (LDH) as predictors of mortality in hospitalized COVID-19 patients.

IF 1.4 4区 医学 Q4 INFECTIOUS DISEASES Journal of Infection in Developing Countries Pub Date : 2024-09-30 DOI:10.3855/jidc.18833
Fierna D Hanafi, Tenri Esa, Asvin Nurulita, Andi A Mumang
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Abstract

Introduction: Several laboratory parameters may be predictors of coronavirus disease 2019 (COVID-19) mortality. This study aimed to analyze the potential of D-dimer, ferritin, and lactate dehydrogenase (LDH) to predict mortality in severe COVID-19 patients.

Methodology: A retrospective cohort study, including 147 patients, was examined using secondary data from medical records of hospitalized COVID-19 patients. D-dimer, ferritin, and LDH levels were obtained from the patients' blood analysis on first hospitalization. Patients were then categorized into a survival group (97 patients) and a non-survival group (50 patients) based on final outcome. Proportions and means were analyzed using Chi square and Mann-Whitney tests. Further, the correlation and accuracy were analyzed using partial correlations test and receiver operating characteristic curve analysis. The combination of multiple predictors was also analyzed.

Results: The non-survival group had significantly higher levels of D-dimer (32.11 ± 13.05 vs. 9.57 ± 16.65; p < 0.001), ferritin (1719.84 ± 539.52 vs. 808.83 ± 664.81; p < 0.001), and LDH (1782.92 ± 1537.92 vs. 622.848 ± 274.79; p < 0.001) than the survival group. These parameters also had a moderate correlation with mortality (r > 0.500) and robust sensitivity and specificity for predicting mortality, especially ferritin (AUC = 0.906; sensitivity = 92.3%; specificity = 87.5%; p < 0.001), and the combination of ferritin and LDH with or without D-dimer (AUC = 0.959; sensitivity = 100%; specificity = 87.5%; p < 0.001).

Conclusions: The levels of these parameters are significantly higher, have robust sensitivity and specificity, and can be used as predictors of mortality.

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D-二聚体、铁蛋白和乳酸脱氢酶(LDH)是预测 COVID-19 住院患者死亡率的指标。
导言:一些实验室参数可预测冠状病毒病2019(COVID-19)的死亡率。本研究旨在分析D-二聚体、铁蛋白和乳酸脱氢酶(LDH)预测重症COVID-19患者死亡率的潜力:一项回顾性队列研究利用 COVID-19 住院患者病历中的二手数据对 147 名患者进行了研究。D-二聚体、铁蛋白和 LDH 水平来自患者首次住院时的血液分析。然后根据最终结果将患者分为存活组(97 例)和非存活组(50 例)。采用卡方检验和曼-惠特尼检验对比例和均值进行分析。此外,还使用偏相关检验和接收者操作特征曲线分析法对相关性和准确性进行了分析。此外,还对多个预测因素的组合进行了分析:非存活组的 D-二聚体(32.11 ± 13.05 vs. 9.57 ± 16.65;P < 0.001)、铁蛋白(1719.84 ± 539.52 vs. 808.83 ± 664.81;P < 0.001)和 LDH(1782.92 ± 1537.92 vs. 622.848 ± 274.79;P < 0.001)水平明显高于存活组。这些参数与死亡率也有中度相关性(r > 0.500),预测死亡率的灵敏度和特异性也很高,尤其是铁蛋白(AUC = 0.906;灵敏度 = 92.3%;特异性 = 87.5%;p < 0.001),以及铁蛋白和 LDH 与或不与 D-二聚体的组合(AUC = 0.959;灵敏度 = 100%;特异性 = 87.5%;p < 0.001):这些参数的水平明显较高,具有很高的灵敏度和特异性,可用作预测死亡率的指标。
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来源期刊
CiteScore
3.70
自引率
5.30%
发文量
239
审稿时长
4-8 weeks
期刊介绍: The Journal of Infection in Developing Countries (JIDC) is an international journal, intended for the publication of scientific articles from Developing Countries by scientists from Developing Countries. JIDC is an independent, on-line publication with an international editorial board. JIDC is open access with no cost to view or download articles and reasonable cost for publication of research artcles, making JIDC easily availiable to scientists from resource restricted regions.
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