SARS-CoV-2 基因特异性 Ct 值与 COVID-19 相关住院死亡率之间的关系。

Frontiers in epidemiology Pub Date : 2024-04-26 eCollection Date: 2024-01-01 DOI:10.3389/fepid.2024.1375975
Mpho L Sikhosana, Richard Welch, Alfred Musekiwa, Zinhle Makatini, Joy Ebonwu, Lucille Blumberg, Waasila Jassat
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引用次数: 0

摘要

背景:由于目前还没有特异性的SARS-CoV-2预后病毒生物标志物来预测疾病的严重程度,因此人们对使用SARS-CoV-2聚合酶链反应(PCR)的周期阈值(Ct)来预测疾病进展产生了兴趣:本研究评估了 COVID-19 住院病例的院内死亡率与 SARS-CoV-2 特异基因靶标的 Ct 值之间的关系:从国家监测系统中获取了 2020 年 4 月至 2022 年 7 月期间豪滕省 COVID-19 住院病例的临床数据,并与实验室数据进行了关联。研究期间分为几个流行波:Asp614Gly/波1(2020 年 6 月 7 日至 8 月 22 日);beta/波2(2020 年 11 月 15 日至 2021 年 2 月 6 日);delta/波3(2021 年 5 月 9 日至 9 月 18 日)和 omicron/波4(2021 年 11 月 21 日至 2022 年 1 月 22 日)。根据检测平台(罗氏-ORF基因;GeneXpert-N2基因;雅培-RdRp基因),SARS-CoV-2特异基因的Ct值数据被归类为低值(Ct 30):有记录的病例为 1205 例:836例(69.4%;第1波)、122例(10.1%;第2波)、21例(1.7%;第3波)和11例(0.9%;第4波)。病例的平均年龄(±SD)为 49 岁(±18),662 人(54.9%)为女性。共记录了 296 例(24.6%)死亡病例:241 例(81.4%;第 1 波)、27 例(9.1%;第 2 波)、6 例(2%;第 3 波)和 2 例(0.7%;第 4 波)(P 30):尽管在 Ct 值为 1 的病例中,与 COVID19 相关的死亡几率较高,但在 Ct 值为 2 的病例中,与 COVID19 相关的死亡几率较低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association between SARS-CoV-2 gene specific Ct values and COVID-19 associated in-hospital mortality.

Background: Since there are currently no specific SARS-CoV-2 prognostic viral biomarkers for predicting disease severity, there has been interest in using SARS-CoV-2 polymerase chain reaction (PCR) cycle-threshold (Ct) values to predict disease progression.

Objective: This study assessed the association between in-hospital mortality of hospitalized COVID-19 cases and Ct-values of gene targets specific to SARS-CoV-2.

Methods: Clinical data of hospitalized COVID-19 cases from Gauteng Province from April 2020-July 2022 were obtained from a national surveillance system and linked to laboratory data. The study period was divided into pandemic waves: Asp614Gly/wave1 (7 June-22 Aug 2020); beta/wave2 (15 Nov 2020-6 Feb 2021); delta/wave3 (9 May-18 Sept 2021) and omicron/wave4 (21 Nov 2021-22 Jan 2022). Ct-value data of genes specific to SARS-CoV-2 according to testing platforms (Roche-ORF gene; GeneXpert-N2 gene; Abbott-RdRp gene) were categorized as low (Ct < 20), mid (Ct20-30) or high (Ct > 30).

Results: There were 1205 recorded cases: 836(69.4%; wave1), 122(10.1%;wave2) 21(1.7%; wave3) and 11(0.9%;in wave4). The cases' mean age(±SD) was 49 years(±18), and 662(54.9%) were female. There were 296(24.6%) deaths recorded: 241(81.4%;wave1), 27 (9.1%;wave2), 6 (2%;wave3), and 2 (0.7%;wave4) (p < 0.001). Sample distribution by testing platforms was: Roche 1,033 (85.7%), GeneXpert 169 (14%) and Abbott 3 (0.3%). The median (IQR) Ct-values according to testing platform were: Roche 26 (22-30), GeneXpert 38 (36-40) and Abbott 21 (16-24). After adjusting for sex, age and presence of a comorbidity, the odds of COVID-19 associated death were high amongst patients with Ct values 20-30[adjusted Odds Ratio (aOR) 2.25; 95% CI: 1.60-3.18] and highest amongst cases with Ct-values <20 (aOR 3.18; 95% CI: 1.92-5.27), compared to cases with Ct-values >30.

Conclusion: Although odds of COVID19-related death were high amongst cases with Ct-values <30, Ct values were not comparable across different testing platforms, thus precluding the comparison of SARS-CoV-2 Ct-value results.

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