key: cord-0685246-yqg2tvuv authors: Liu, Ke; Yang, Xiuli; Feng, Chen; Chen, Mei; Zhang, Chuantao; Wang, Yuelian title: Clinical features and independent predictors for recurrence of positive SARS‐CoV‐2 RNA: A propensity score‐matched analysis date: 2021-11-18 journal: J Med Virol DOI: 10.1002/jmv.27450 sha: 12ad1b019efa8717f0ce31dad070cedbb2e55ff9 doc_id: 685246 cord_uid: yqg2tvuv Patients with COVID‐19 may be recurrence positive for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) RNA after being cured and discharged from the hospital. The aim of this study was to explore independent influencing factors as markers for predicting positive SARS‐CoV‐2 RNA recurrence. The study included 601 COVID‐19 patients who were cured and discharged from the Public and Health Clinic Centre of Chengdu from January 2020 to March 2021, and the recurrence positive of patients within 6 weeks after SARS‐CoV‐2 RNA turned negative was followed up. We used propensity score matching to eliminate the influence of confounding factors, and multivariate Logistic regression analysis was used to determine the independent influencing factors for positive SARS‐CoV‐2 RNA recurrence. Multivariate Logistic regression showed that the elevated serum potassium (odds ratio [OR] = 6.537, 95% confidence interval [CI]: 1.864–22.931, p = 0.003), elevated blood chlorine (OR = 1.169, 95% CI: 1.032–1.324, p = 0.014) and elevated CD3(+)CD4(+) count (OR = 1.003, 95% CI: 1.001–1.004, p < 0.001) were identified as independent risk factors for positive SARS‐CoV‐2 RNA recurrence (p < 0.05). The difference in virus shedding duration (OR = 1.049, 95% CI: 1.000–1.100, p = 0.05) was borderline statistically significant. For sensitivity analysis, we included virus shedding duration as a categorical variable in the model again and found that the OR value related to recurrence positively increased with delayed virus shedding duration, and the trend test showed a statistical difference (P trend = 0.03). Meanwhile, shortening of activated partial prothrombinase time (OR = 0.908, 95% CI: 0.824–1.000, p = 0.049) was identified as an independent protection factor for SARS‐CoV‐2 RNA recurrence positive. We have identified independent factors that affect the recurrence of SARS‐CoV‐2 RNA positive. It is recommended that doctors pay attention to these indicators when first admitted to the hospital. The novel coronavirus pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become an international public health emergency since late 2019. According to COVID-19 data published by the World Health Organization (https://www.who.int/data), as of May 2021, there have been over 170 million cumulative confirmed worldwide and over 3.8 million cumulative deaths. 1 With the international epidemic prevention and control, most of the patients have been discharged after treatment. However, in some regions and countries, some discharged COVID-19 patients have positive retest results for SARS-CoV-2 RNA, which has attracted the attention of researchers from all circles. [2] [3] [4] [5] At present, the mechanism of recurrent positive SARS-CoV-2 RNA is not clear. A systematic review and meta-analysis of 14 studies showed that the incidence of recurrent SARS-CoV-2 RNA positivity is estimated to be 14.8%, and patients with younger age and longer onset time have a greater risk of recurrent SARS-CoV-2 RNA positivity. 6 The cause of recurrent SARS-CoV-2 RNA positivity may be related to false-negative test results at the time of discharge, host status, virological factors, reinfection or immunosuppression, etc. 7, 8 However, these possible reasons have not been confirmed by a large number of clinical studies. Studies have shown that SARS-CoV-2 RNA recurrence-positive patients may have more severe immune suppression when they are admitted to the hospital. 9 Patients with low levels of Immunoglobulin G and Immunoglobulin M (IgM) are more likely to face the risk of recurring SARS-CoV-2 RNA test results being positive. 10 At the same time, another study confirmed that an increase in IgM antibodies against SARS-CoV-2 will be more conducive to clearing the virus. 11 Moreover, the study by Wong et al. 12 showed that patients with recurrent SARS-CoV-2 RNA positivity did not show COVID-19 symptoms or signs during the entire quarantine period after discharge from the hospital. Meanwhile, in another study involving 123 recurrent SARS-CoV-2 RNA positivity patients, it was found that there were generally fewer related clinical symptoms during the recurrence period, which may be related to the higher proportion of asymptomatic or mild symptoms in patients at the first episode. 13 In this study, a retrospective clinical study was conducted to analyze the cases of 692 patients with COVID-19 who were cured and discharged from the Public and Health Clinic Centre of Chengdu from January 2020 to March 2021. A total of 601 patients were included in the analysis after excluding severe clinical data absence, death, and minor (age <18 years) patients (n = 91). Case data were collected, including demographic characteristics, clinical characteristics, laboratory results at admission, treatment plan, and clinical outcomes. All data were collected and checked independently by two physicians. According to the results of SARS-CoV-2 RNA recurrence in the follow-up period, we divided the patients into the recurrent group (n = 99) and nonrecurrent group (n = 502). To eliminate the influence of confounding factors to the greatest extent, a 1:1 propensity score matching (PSM) was conducted for the two groups of patients according to the baseline data. After matching, 94 cases were in the recurrent group and 94 cases were in the nonrecurrent group. We analyzed the potential influencing factors associated with the occurrence of recurrent SARS-CoV-2 RNA positivity in this result. This study was approved by the Institutional Ethics Committee of the Public and Health Clinic Centre of Chengdu. As this study is a retrospective clinical study and only involves the extraction of medical records, the need for informed consent of patients is waived. Continuous variables were presented as mean ± SD or median (interquartile range). Categorical variables were presented as numbers (proportion). We used Student's t-test, Mann-Whitney U test, χ 2 test, or Fisher's exact test to compare the differences between the two groups before PS matching. Student's t-test is used to test the significance of continuous variables that conform to the normal distribution between the two groups such as age, body mass index (BMI), etc., while Mann-Whitney U test is used to test the significance of continuous variables that do not conform to the normal distribution between the two groups. The χ 2 test or Fisher's exact test is used to test the significance of dichotomous variables between two groups, such as gender, clinical severity of disease. To eliminate the influence of confounders as much as possible, the variables with statistically significant differences in baseline data were used as independent predictors to calculate the propensity score. The caliper value was set to 0.01, and the 1:1 nearest neighbor matching method was used to match patients in the two groups separately. After PS matching, the differences between the two groups were compared by paired t-tests, Wilcoxon rank sum test or the McNemar test. The paired t-test is used to test the significance of continuous variables that conform to the normal distribution between the two groups such as age, BMI, etc., while the Wilcoxon rank sum test is used to test the significance of the continuous variables that do not conform to the normal distribution between the two groups. McNemar test is used to test the significance of dichotomous variables between two groups, such as gender, clinical severity of disease. The predictors of recurrent SARS-CoV-2 RNA positivity were determined by paired univariate and multivariate logistic regression models. We used a paired univariate logistic regression model to explore the variables related to recurrent SARS-CoV-2 RNA positivity, and calculated odds ratio (OR). Variance inflation factor (VIF) and tolerance were used to judge the multicollinearity among independent variables. To prevent over-fitting, five variables with statistical differences (p < 0.05) in the univariate model were selected to be included in paired multivariate logistic regression analysis to determine independent predictors related to Benjamini-Hochberg procedure was used to adjust for the false discovery rate for multiple testing. All statistical tests were twosided and p < 0.05 was considered statistically significant. All analyses were performed using SPSS software version 22.0. cases were successfully matched (Table 1) . After PS matching, the covariates between the two groups were not statistically significant The laboratory results of 188 COVID-19 patients after PS matching are listed in Table 2 The treatment of 188 COVID-19 patients after PS matching were listed in The results of univariate analysis are listed in duration in SARS-CoV-2 re-positive cases was 17 days at the initial hospitalization, which was significantly longer than the median time of 12 days in nonrepositive cases. The same result was also reported in the study of Ao et al. 10 The contribution of this study is that these potentially in- COVID-19) data. 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The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.