Clinical Characteristics of Mild/moderate COVID-19 Patients with a Prolonged Negative Conversion Time of SARS-CoV-2 Nucleic Acid Detection

Clinical Characteristics of Mild/moderate COVID-19 Patients with a Prolonged Negative Conversion Time of SARS-CoV-2 Nucleic Acid Detection | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article Clinical Characteristics of Mild/moderate COVID-19 Patients with a Prolonged Negative Conversion Time of SARS-CoV-2 Nucleic Acid Detection Ya Yang, Xiaogang Hu, Lirong Xiong, Peishu Fu, Wei Feng, Wei Li, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-68406/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Feb, 2021 Read the published version in BMC Infectious Diseases → Version 1 posted 10 You are reading this latest preprint version Abstract Background: The impact of COVID-19 has been devastating on a global scale. Our study aimed to identify factors in predicting prolonged negative conversion time (NCT) of SARS-CoV-2 RNA in mild/moderate COVID-19 patients. Methods: The clinical features and treatment outcomes were retrospectively analyzed from 32 hospitalized mild/moderate COVID-19 patients. Then univariate and multivariate analysis were used to predict in the factors of prolonged NCT of SARS-CoV-2 RNA. Results: The general clinical symptoms were cough (78.1%), fever (75%), diarrhea (68.8%), expectoration (56.3%), and nausea (37.5%). More than 40% of the patients had decreased erythrocyte, hemoglobin and leucocyte and 93.8% patients were detected in abnormalities of chest CT. The median NCT of SARS-CoV-2 RNA was 19.5 days (IQR: 14.25–25). Univariate analysis found fever, nausea, diarrhea and abnormalities in chest CTs were positively associated with prolonged NCT of viral RNA (P<0.05). The multivariate Cox proportional hazard model revealed that fever [Exp (B), 0.284; 95% CI, 0.114‑0.707; P＜0.05] and nausea [Exp (B), 0.257; 95%CI, 0.096‑0.689; P＜0.05] were two significant independent factors. Conclusions: Fever, nausea, diarrhea and abnormalities in chest CT are potential factors for predicting prolonged NCT of viral RNA. Moreover, Fever and nausea were two significant independent factors in prolonged NCT of viral RNA in mild/moderate COVID-19 patients. Infectious Diseases COVID-19 SARS-CoV-2 Clinical characteristics Negative conversion time Figures Figure 1 Figure 2 Background In December 2019, novel pneumonia of unknown causes was reported in Wuhan, Hubei province in China. On February 11, 2020, the World Health Organization (WHO) officially named the disease as Coronavirus Disease 2019 (COVID-19), which caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Following the initial outbreak, COVID-19 has become a global public health emergency of international concern [ 1 ]. There had been 23 million confirmed cases, and 800,000 confirmed deaths by 23 August 2020 spreaded across 216 countries and territories[ 2 ]. The number of COVID-19 patients has increased exponentially, causing devastation on a global scale [ 3 ]. Many studies have focused on the epidemiological, clinical symptoms, laboratory tests, and radiological characteristics of patients since the COVID-19 outbreak. Current epidemiological investigations show that the incubation period of COVID-19 ranges from one to fourteen days, with the majority of cases being three to seven days. The SARS-CoV-2 is mainly transmitted through respiratory droplets and by fomites [ 4 ]. Moreover, SARS-CoV-2 has also been isolated from anal/rectal swabs, stool specimens, and urine, suggesting fecal-oral transmission [ 5 ]. The main clinical symptoms of COVID-19 include fever, myalgia, dry cough, dyspnea, fatigue and diarrhea. Laboratory tests have shown that most patients had decreased white blood cell counts, increased C-reactive protein, and increased serum sedimentation rates. Computed tomograms (CT) examination showed multiple plaque shadows and interstitial changes in the early stage, which had then developed into various ground glass shadows and infiltration shadows in both lungs in the later stage. COVID-19 patients also could be asymptomatic with no associated clinical manifestations, but the SARS-CoV-2 RNA test was positive. According to the severity of the disease, COVID-19 patients were were divided into asymptomatic, mild/moderate and severe cases. Without timely treatment, mild/moderate patients will develop into severe cases, increasing the fatality rate. It is very important to control the disease progression of mild/moderate patients. The standard of cure is the relief of symptoms and two successive negative viral nucleic acid in the “Diagnosis and Treatment Scheme of New Coronavirus Infected Pneumonia” (trial version 7)[ 6 ]. The negative conversion of SARS-CoV-2 RNA was essential in the discharge criteria during hospitalization [ 7 , 8 ]. The negative conversion time (NCT) of SARS-CoV-2 RNA is closely related to clinical manifestation and disease progression in COVID-19 patients. Hu et al. reported that NCT of SARS-CoV-2 RNA occurred in 14 days (IQR: 10–18). Older age and chest tightness were independently associated with delayed clearance of SARS-CoV-2 RNA in hospitalized patients [ 9 ]. The COVID-19 patients with digestive symptoms are more likely to test positive for viral RNA in a stool sample and have a longer delay before viral clearance than patients with only respiratory symptoms [ 10 ]. Preliminary clinical treatment showed that some drugs, such as chloroquine, effectively potentiated virus clearance in COVID-19 patients [ 11 ]. However, there is limited data regarding the potential predictors of NCT in mild/moderate COVID-19 patients. Therefore, it was necessary to identify systematically factors associated with prolonged NCT in mild/moderate COVID-19 patients. This study analyzed clinical characteristics of mild/moderate COVID-19 patients with prolonged NCT of SARS-CoV-2 RNA, which provide a useful references for disease progression and treatment of COVID-19. Methods Subjects and data collection The clinical data and laboratory test results were analyzed retrospectively from 32 mild/moderate COVID-19 patients admitted to the Public Health Medical Center and Prevention of Chongqing from January 31 to February 28, 2020. All patients were identified to be nucleic acid positive for SARS-CoV-2 and were convalescent before hospital discharge. Data was collected and recorded from each patient, which included demographic and clinical information (gender, age, smoking history, and comorbidities), clinical manifestations (fever, coughing, expectoration, anhelation, myalgia, nausea and vomiting, diarrhea, osphyalgia, etc.), and laboratory test results (standard blood counts, procalcitonin, C-reactive protein, blood biochemistry, coagulation function, and myocardial enzyme spectrum, etc). The normal range of laboratory examination is the standard of Reference Range Values for National Practice for Clinical Testing (4th Edition) published by People's Medical Publishing House[ 12 ]. Chest CT and therapeutic drug use were also documented. Then, the factors associated with NCT of SARS-CoV-2 RNA in upper respiratory specimens were analyzed. Therapeutic strategies Strategies of treatment for COVID-19 patients included antiviral treatment and symptomatic treatment. The primary treatment strategy for COVID-19 is combined antiviral therapy, which mainly comprises interferon-α2b（IFN-α2b） and lopinavir / ritonavir, or IFN-α2b and ribavirin. When SARS-CoV-2 RNA was still detectable after 19 days of drug combination therapy, chloroquine phosphate was added to the antiviral treatment. Definitions of basic concepts Sputum and throat swab specimens were collected from patients. RT-PCR assay was used to detect genes of SARS-CoV-2, which were performed twice in every 24 h period. Patients with consecutive positive nucleic acid tests were confirmed as SARS-CoV-2 infection. The standard of negative conversion is two successive negative viral nucleic acid detection tests in 24 h minimum sampling intervals. The term convalescent patients refer to recovered afebrile patients without respiratory symptoms who had two successive (minimum 24 h sampling interval) negative results for SARS-CoV-2 RNA from oropharyngeal swabs by RT-PCR. Statistical analysis Normally distributed continuous variables are summarized as the mean mean (standard deviation, SD), otherwise, median (interquartile range, IQR) was used to describe. Categorical variables are expressed using numbers and percentages. Cox regression analysis was used to analyze the factors. First, univariate analysis was performed, and the indicators with statistical significance were analyzed for Kaplan-Meier survival analysis. The Log Rank method was used to compare the differences between groups. A Cox proportional hazard model was used for multivariate analysis. IBM SPSS Statistics 26 was used for statistical analysis and survival image rendering. P<0.05 was considered to indicate a statistically significant difference. Results The relationship between demographic and clinical information and NCT of SARS-CoV-2 RNA Of these patients, males accounted for 43.8% (14) of confirmed cases, and 56.3% (18) were females. The median age of males and females was 34.00 (29.00, 47.00) years and 43.00 (37.75, 57.25) years respectively, suggesting that middle-aged people were more susceptible to infection than other age groups. A total of 12.5% of patients were smokers. More than a quarter of patients (34%) had underlying diseases, including cardiovascular and cerebrovascular diseases (25%), gastrointestinal disease (15.6%), respiratory disease (12.5%), endocrine disease (9.3%), a neurological disorder (3.1%) and urinary disease (3.1%). All patient data were analyzed using the Cox regression analysis for univariate analysis. However, we found that no demographic or clinical information had a significant positive association with NCT of viral RNA in patients (P > 0.05, Table 1 ). Table 1 The relationship between demographic and clinical information and NCT of SARS-CoV-2 RNA in 32 patients with COVID-19 Factors Count n (%) p value Exp(B) 95.0% Cl for Exp(B) lower limit detection limits Total 32(100) Age in years, median (IQR) Male 34.00 (29.00, 47.00) Female 43.00 (37.75, 57.25) Age breakdown ༜45 21(65.6) 0.636 1.190 0.579 2.446 ༞45 12(37.5) Sex Male 14(43.8) 0.689 1.325 0.398 4.411 Female 18(56.3) Smoking 4(12.5) 0.988 0.992 0.343 2.868 Underlying diseases Hypertension 3(9.4) 0.710 1.257 0.376 4.197 Diabetes 1(3.1) 0.110 5.750 0.671 49.244 Coronary heart disease 1(3.1) 0.252 3.373 0.421 26.993 Viral hepatitis type B 2(6.3) 0.399 0.536 0.126 2.282 Kidney stone 1(3.1) 0.880 1.169 0.155 8.786 Hyperlipemia 2(6.3) 0.199 0.550 0.221 1.370 Gout 1(3.1) 0.593 0.578 0.078 4.305 Cerebral hemorrhage 1(3.1) 0.593 0.578 0.078 4.305 Obstructive sleep apnea syndrome(OSAS) 2(6.3) 0.593 0.578 0.078 4.305 Appendicectomy 2(6.3) 0.545 1.874 0.245 14.352 Head trauma 1(3.1) 0.545 1.874 0.245 14.352 Thyroid adenoma 1(3.1) 0.110 5.750 0.671 49.244 Chronic bronchitis 1(3.1) 0.110 5.750 0.671 49.244 Depression 1(3.1) 0.075 7.340 0.820 65.691 Pneumonia 1(3.1) 0.258 0.312 0.042 2.342 Appendicitis 1(3.1) 0.258 0.312 0.042 2.342 Data are shown as n (%) or IQR unless specified otherwise. The Log Rank method was used to compare the differences between groups, p < 0.05 was considered to indicate a statistically significant difference (indicated by *). The relationship between clinical manifestation and NCT of SARS-CoV-2 RNA The median duration from disease onset to hospital admission was 3.5 (IQR: 2–6) days, with a median of 20 days from illness onset to hospital discharge (IQR: 15.25–26) and the median time from positive to negative conversion of SARS-CoV-2 RNA was 19.5 days (IQR: 14.25–25). The majority of the patients showed an initial symptom of fever (75%), but a quarter of the patients were afebrile, alerting the need for the caution of atypical cases. In addition to fever, other clinical symptoms mainly included fatigue (78.1%), expectoration (56.3%), diarrhea (68.8%), nausea (37.5%), anhelation (34.4%), and throat discomfort (34.4%). Clinical manifestations of the study population are summarized in Table 2 . Table 2 The relationship between clinical manifestation and NCT of SARS-CoV-2 RNA in 32 patients with COVID-19 Factors Count n (%) p value Exp(B) 95.0% Cl for Exp(B) lower limit detection limits Total 32(100) Fever 24(75.0) 0.050* 0.431 0.186 1.000 Cough 25(78.1) 0.564 0.779 0.334 1.818 Expectoration 18(56.3) 0.335 0.707 0.349 1.431 Anhelation 11(34.4) 0.714 0.871 0.416 1.822 Throat discomfort 11(34.4) 0.669 0.852 0.409 1.775 Headache and dizziness 7(21.9) 0.323 0.650 0.277 1.526 Myodynia 7(21.9) 0.123 0.491 0.199 1.213 Osphyalgia 2(6.3) 0.341 0.495 0.117 2.103 Diarrhea 22(68.8) 0.007* 0.318 0.138 0.733 Ventosity 2(6.3) 0.524 0.622 0.145 2.677 Nausea 12(37.5) 0.002* 0.262 0.112 0.613 Vomiting 3(9.4) 0.314 2.161 0.482 9.686 Muscular stiffness 5(15.6) 0.235 0.559 0.214 1.460 Chills 2(6.3) 0.126 3.288 0.716 15.105 Fatigue 9(28.1) 0.509 0.768 0.350 1.683 Snot 3(9.4) 0.123 0.387 0.113 1.329 Insomnia 5(15.6) 0.444 0.678 0.250 1.836 Chest tightness 5(15.6) 0.978 1.014 0.385 2.670 Bitter taste and thirst 4(12.5) 0.703 1.231 0.422 3.588 Data are shown as n (%) unless specified otherwise. The Log Rank method was used to compare the differences between groups, p < 0.05 was considered to indicate a statistically significant difference (indicated by *). The Cox regression analysis was used for univariate analysis; we found that fever, nausea, and diarrhea were a significant positive association with NCT of viral RNA in patients (P < 0.005, Table 2 ). The KaplanMeier curves revealed that fever, nausea, and diarrhea had a significantly prolonged NCT of SARS-CoV-2 RNA compared with the normality’s group (P < 0.05; Fig. 1 A, B, C). The relationship between laboratory findings and NCT of SARS-CoV-2 RNA As shown in Table 1 , the laboratory inspection section showed that 43.8% of the patients developed leucopenia, and 28.1% of patients had lymphocytopenia. The hemoglobin, platelets, and albumin levels were lower in 53.1%, 37.5%, and 34.4% of patients, respectively. The levels of procalcitonin, C-reactive protein, total bilirubin, direct bilirubin, creatinine, lactic dehydrogenase were increased in 9.4%, 40.6%, 40.6%, 46.9%, 25%, and 21.9% of patienst, respectively. All patient data were analyzed using the Cox regression analysis for univariate analysis. Still, there were no significant findings with a positive association with NCT of viral RNA in patients (P > 0.005, Table 3 ). Table 3 The relationship between laboratory findings and NCT of SARS-CoV-2 RNA in 32 patients with COVID-19 Factors Count n (%) p value Exp(B) 95.0% Cl for Exp(B) lower limit detection limits Total 32(100) Leukocyte count decrease (↓) 14(43.8) 0.176 0.612 0.301 1.246 Neutrophil count decrease (↓) 8(25) 0.661 0.836 0.375 1.864 Neutrophil percentage decrease (↓) 9(28.1) 0.171 0.581 0.267 1.263 Lymphocyte count decrease (↓) 12(37.5) 0.959 1.019 0.494 2.102 Lymphocyte percentage decrease (↓) 9(28.1) 0.529 1.275 0.598 2.718 Erythrocyte count decrease (↓) 24(75) 0.942 1.031 0.453 2.349 Hemoglobin decrease (↓) 17(53.1) 0.678 0.858 0.417 1.765 packcd cell volume (↓) 20(62.5) 0.722 1.140 0.554 2.344 Platelet count decrease (↓) 12(37.5) 0.140 1.823 0.820 4.052 Procalcitonin increase (↑) 3(9.4) 0.536 1.477 0.429 5.091 C-Reactive Protein increase (↑) 13(40.6) 0.492 1.302 0.614 2.761 Total Protein (↓) 21(65.6) 0.934 1.032 0.494 2.155 Albumin decrease (↓) 11(34.4) 0.824 0.920 0.442 1.917 Total bilirubin increase (↑) 13(40.6) 0.297 1.465 0.715 3.000 Direct bilirubin increase (↑) 15(46.9) 0.339 1.411 0.697 2.859 Creatinine increase (↑) 8(25) 0.936 0.968 0.433 2.163 Lactic dehydrogenase increase (↑) 7(21.9) 0.993 1.004 0.433 2.327 D-Dimer increase (↑) 2(6.3) 0.783 1.227 0.286 5.260 Data are shown as n (%) unless specified otherwise. The Log Rank method was used to compare the differences between groups, p < 0.05 was considered to indicate a statistically significant difference (indicated by *). The relationship between radiological findings and NCT of SARS-CoV-2 RNA Ground-glass opacity (GGO) and high-density shadow were the typical radiological findings on chest CT scan. Abnormalities in chest CT were detected in 93.8% of patients. A total of 87.5% of patients had ground-grass opacities over bilateral lungs, which was the most common pattern of CT changes and corresponded to pathological diffuse alveolar damage [ 13 ]. We analyzed the univariate analysis using the Cox regression and found that abnormalities in chest CT were a significant positive association with NCT of viral RNA in patients (P < 0.005, Table 4 ). The Kaplan Meier curves revealed that abnormalities in chest CT had a significantly prolonged NCT of SARS-CoV-2 RNA compared with normality’s group (P < 0.05; Fig. 1 D). Table 4 The relationship between radiological findings a and NCT of SARS-CoV-2 RNA in 32 patients with COVID-19 Factors Count n (%) p value Exp(B) 95.0% Cl for Exp(B) lower limit detection limits Total 32(100) Abnormal 30(93.8) 0.044* 0.209 0.046 0.957 Involved lung field Unilateral 8(25) 0.202 0.570 0.241 1.350 Bilateral 22(68.8) 0.503 1.314 0.591 2.920 Radiological characteristics Ground-grass opacities 28(87.5) 0.940 0.960 0.331 2,782 High-density shadow 17(53.1) 0.083 0.536 0.265 1.086 Data are shown as n (%) unless specified otherwise. The Log Rank method was used to compare the differences between groups, p < 0.05 was considered to indicate a statistically significant difference (indicated by *). a How many patients have the following lesion location. Taking antiviral medications during hospitalization All patients received antiviral therapy during hospitalization. All 32 patients were treated with IFN-α2b. Utilization rates of opinavir/ritonavir, ribavirin, and chloroquine phosphate were treated in 84.4%, 46.9%, and 40.6% of patients, respectively. The proportion of patients receiving combined treatment using IFN-α2b plus lopinavir/ritonavir, IFN-α2b plus ribavirin, IFN-α2b plus lopinavir/ritonavir plus ribavirin, and IFN-α2b plus chloroquine phosphate were 75%, 12.5%, 12.5%, 40.6%, respectively (Fig. 2 ). Predictors of NCT We had summarized the results of the univariate analysis that fever, nausea, diarrhea, and abnormalities in chest CT had a significantly prolonged NCT of SARS-CoV-2 RNA. To analyze factors on NCT of SARS-CoV-2 RNA systematically, the multivariate Cox's proportional hazard model was used to analyze the multivariate analyses. We revealed that fever [Exp (B), 0.284; 95% CI, 0.1140.707; P < 0.005] and nausea [Exp (B), 0.257; 95%CI, 0.0960.689; P < 0.005] were independent factors in prolonged NCT of SARS-CoV-2 RNA in patients with COVID-19 (Table 5 ). Table 5 Independent factors of negative conversion time by the multivariate Cox's proportional hazard model Factors p value Exp(B) 95.0% CI for Exp(B) lower limit detection limits Fever 0.007* 0.284 0.114 0.707 Nausea 0.007* 0.257 0.096 0.689 Diarrhea 0.376 0.648 0.248 1.692 CT imaging 0.150 0.299 0.058 1.550 A Cox proportional hazard model was used for multivariate analysis, p < 0.05 was considered to indicate a statistically significant difference (indicated by *). Discussion COVID-19 is a global pandemic that has rapidly spread worldwide since reported in December 2019. A negative nucleic acid test of SARS-CoV-2 is the standard for a cure of COVID-19. To investigate the timeline of RNA negative conversion of COVID-19 patients, this study retrospectively analyzed clinical characteristics in a cohort of mild/moderate hospitalized patients in Chongqing, China. We found that fever, nausea, diarrhea, and abnormalities in chest CT were correlated to a prolonged NCT of SARS-CoV-2 RNA. More importantly, fever and nausea were the independent factors predicting NCT of mild/moderate COVID-19 patients. Fever, a respiratory manifestation, is the most commonly reported symptom in patients infected with SARS-CoV-2 [ 14 , 15 ]. Accordingly, fever may be a clinical sign of poor prognosis in patients and response to the release of inflammatory mediators such as cytokines and chemokines [ 16 ] [ 17 ]. These inflammatory mediators cause tissue damage and organ dysfunction by stimulating toxic oxygen derivatives suggesting that the NCT of SARS-CoV-2 RNA may be prolonged in patients [ 18 , 19 ]. Chest CT has a high sensitivity to detect lung abnormalities, which is quite helpful in the early diagnosis of the disease. The “Diagnosis and Treatment Scheme for Coronavirus Disease (Trial Version 7)” recommended that a CT examination serves as the diagnostic basis for COVID-19. For chest imaging in patients with COVID-19, the early manifestation was multiple plaque shadows and interstitial changes. The later development was multiple ground glass shadows and infiltration shadows in both lungs. In severe cases, lung consolidation can occur, presenting as “white lung,” which may be related to the immunopathology. Most studies have suggested that a dysregulated/exuberant innate responses are the primary cause of coronavirus-mediated pathology [ 20 ]. Many cytokines or chemokines are involved in the immune storm after the infection of coronavirus,which eventually leads to lung injury and acute respiratory distress syndrome [ 21 ]. The improvement of chest CT was after that of body temperature. Still, it preceded the negative conversion of nucleic acid tests, suggesting that abnormalities in chest CT could indirectly reflect the persistence of SARS-CoV-2 RNA in patients with COVID-19. Our study found that abnormalities in chest CT could prolong the NCT of patients with COVID-19. Therefore, the improvement of chest CT as soon as possible has an essential effect on shortening NCT in patients with COVID-19 and promoting patients to be discharged more rapidly. Although COVID-19 most commonly presents with respiratory symptoms, such as cough and shortness of breath [ 14 , 22 , 23 ], there is evidence that the illness can also present with nonrespiratory symptoms, most notably digestive symptoms such as diarrhea, diminished appetite, nausea, and vomiting [ 24 – 26 ]. Diarrhea appeared to be the most common GI complaint [ 27 ], followed by nausea and vomiting [ 22 ]. SARS-CoV-2 RNA was detected in stool samples from COVID-19 patients for the first time, first reported in the United States [ 28 ]. Viral RNA was still positive in gastrointestinal specimens even after levels could not be detected in respiratory samples [ 27 ], implying direct infectivity of the virus on the intestinal tract. Current research shows that the primary target organ of COVID-19 is the lung, but clinical evidence suggests that the gastrointestinal tract may be another viral target organ. The SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) has been found in both upper and lower gastrointestinal tract where its expression level was nearly 100 times higher than that of respiratory organs [ 29 , 30 ]. Patients with symptoms of the digestive system have more viruses in their gut [ 10 ], and maybe more likely to cause direct damage to the intestinal mucosa. Our research found that digestive symptoms, including nausea and diarrhea, are the factors of NCT of COVID-19 patients, suggesting that patients with gastrointestinal symptoms should seek medical care to avoid delayed diagnosis and prolong treatment time. Chinese experts recommend that patients diagnosed as mild, moderate, and severe cases of COVID-19 pneumonia and without contraindications to chloroquine, be treated with 500 mg of chloroquine twice a day for ten days[ 31 ]. In our study, when SARS-CoV-2 RNA was still detectable after 19 days of drug combination therapy, chloroquine was added to the antiviral treatment. Thirteen patients were treated with chloroquine and a median duration of viral shedding of 6.0 (IQR: 5.0–7.0) days. Therefore, these results suggest that chloroquine may play a role in reducing viral load and shortening the time of virus negative transition. Other studies have also confirmed the role of chloroquine in promoting virus negative conversion and shortening the disease course. Other studies have also confirmed the role of chloroquine in promoting virus negative conversion, shortening the course of the disease [ 11 ] and reducing/eliminating viral load in COVID-19 patients [ 32 ]. However, we did not conduct a randomized controlled study to evaluate the efficacy of chloroquine and most infections with COVID-19 were self-limited, about 15% of infected adults developed severe pneumonia that required treatment [ 22 , 33 ], the numerical reduction in time to clinical improvement in those treated with chloroquine requires confirmation in more extensive studies. There are several limitations to our study. First, the sample size of this study is not large enough. Second, we have not conducted randomized controlled trials, so we cannot determine the therapeutic effect of chloroquine on COVID-19 and its impact on shortening the time of negative viral conversion. Conclusion In conclusion, our study suggests that fever, nausea, diarrhea and abnormalities in chest CT hve a significantly prolonged NCT of SARS-CoV-2 RNA in mild/moderate COVID-19 patients. More importantly, fever and nausea are the independent factors in predicting NCT of SARS-CoV-2 RNA. Meanwhile, we should pay attention to gastrointestinal symptoms and provide timely treatment. This study provide a useful references for disease progression and treatment of COVID-19. Abbreviations COVID-19: Coronavirus disease 2019; SARS-CoV-2: Severe Acute Respiratory Syndrome Coronavirus-2; NCT: Negative conversion time; RT-PCR: Reverse Transcription-polymerase Chain Reaction; CT: Computerized tomography; IFN-α2b: Interferon-α2b; IQR: Interquartile range; GGO: Ground-glass opacities. Declarations Ethics approval and consent to participate This study was conducted following the Declaration of Helsinki. It was approved by the Ethics Commission of Chongqing Public Health Medical Center (ethics approval registration number:2020-043-01-KY) and written informed consent was waived in consideration of the emergency of infectious disease. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The authors received no specific funding for this work. Authors’ contributions FS, LZ, YY and XH conceived and designed the project and had roles in the data analysis, data interpretation, literature search, and writing of the manuscript. LX, PF, WF and WL had roles in data collection, data interpretation, iterature search, and writing of the manuscript. LZ had roles in clinical management and data collection, and had full access to all of the data in the study and take responsibility for the integrity of the data. The authors read and approved the final manuscript. Acknowledgements We would like to thank all physicians that participated in this study for patient enrollment and follow-up. Author details 1 Department of Pharmacy, The First Affiliated Hospital of Army Medical University, Chongqing,400038, China. 2 Department of pharmacy, Chongqing University Cancer Hospital, Chongqing, 400030, China. 3Department of Tuberculosis, Chongqing Public Health Medical Center, Chongqing, 400036, China. References Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, Zhao X, Huang B, Shi W, Lu R, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med. 2020;382(8):727–33. World Health Organisation (WHO). Novel Coronavirus . (2019- nCoV ) situation reports : https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/] . Reuben RC, Danladi MMA, Pennap GR. Is the COVID-19 pandemic masking the deadlier Lassa fever epidemic in Nigeria? Journal of clinical virology: the official publication of the Pan American Society for Clinical Virology. 2020;128:104434. Wu F, Zhao S, Yu B, Chen YM, Wang W, Song ZG, Hu Y, Tao ZW, Tian JH, Pei YY, et al. A new coronavirus associated with human respiratory disease in China. Nature. 2020;579(7798):265–9. Ling Y, Xu SB, Lin YX, Tian D, Zhu ZQ, Dai FH, Wu F, Song ZG, Huang W, Chen J, et al. Persistence and clearance of viral RNA in 2019 novel coronavirus disease rehabilitation patients. Chin Med J. 2020;133(9):1039–43. National Health Commission of China. New coronavirus pneumonia prevention and control program ( 7th edn ). Mar 4. 2020. http://www.nhc.gov.cn/yzygj/s7653p/202003/46c 9294a7dfe4cef80dc7f5912eb1989.shtml?spm=C73544894212.P59511941341.0.0. Chan JF, Yip CC, To KK, Tang TH, Wong SC, Leung KH, Fung AY, Ng AC, Zou Z, Tsoi HW, et al: Improved Molecular Diagnosis of COVID-19 by the Novel, Highly Sensitive and Specific COVID-19-RdRp/Hel Real-Time Reverse Transcription-PCR Assay Validated In Vitro and with Clinical Specimens . Journal of clinical microbiology 2020, 58(5). Chu DKW, Pan Y, Cheng SMS, Hui KPY, Krishnan P, Liu Y, Ng DYM, Wan CKC, Yang P, Wang Q, et al. Molecular Diagnosis of a Novel Coronavirus (2019-nCoV) Causing an Outbreak of Pneumonia. Clinical chemistry. 2020;66(4):549–55. Hu X, Xing Y, Jia J, Ni W, Liang J, Zhao D, Song X, Gao R, Jiang F. Factors associated with negative conversion of viral RNA in patients hospitalized with COVID-19. Sci Total Environ. 2020;728:138812. Han C, Duan C, Zhang S, Spiegel B, Shi H, Wang W, Zhang L, Lin R, Liu J, Ding Z, et al. Digestive Symptoms in COVID-19 Patients With Mild Disease Severity: Clinical Presentation, Stool Viral RNA Testing, and Outcomes. Am J Gastroenterol. 2020;115(6):916–23. Gao J, Tian Z, Yang X. Breakthrough: Chloroquine phosphate has shown apparent efficacy in treatment of COVID-19 associated pneumonia in clinical studies. Bioscience trends. 2020;14(1):72–3. National Practice for Clinical Testing (4th Edition).Beijing: People's Medical Publishing House. (2015). Chong S, Kim TS, Cho EY. Herpes simplex virus pneumonia: high-resolution CT findings. Br J Radiol. 2010;83(991):585–9. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, et al: Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus - Infected Pneumonia in Wuhan , China . Jama 2020. Chen H, Lin C, Fan Z, Yu W, Cao M, Ke C, Jiao X. Serum cytokines and clinical features in patients with fever and thrombocytopenia syndrome. Clin Chim Acta. 2019;494:22–30. Liu Y, Freed DC, Li L, Tang A, Li F, Murray EM, Adler SP, McVoy MA, Rupp RE, Barrett D, et al: A Replication-Defective Human Cytomegalovirus Vaccine Elicits Humoral Immune Responses Analogous to Those with Natural Infection . Journal of virology 2019, 93(23). Korish AA, Arafa MM. Propolis derivatives inhibit the systemic inflammatory response and protect hepatic and neuronal cells in acute septic shock. The Brazilian journal of infectious diseases: an official publication of the Brazilian Society of Infectious Diseases. 2011;15(4):332–8. Mittal M, Siddiqui MR, Tran K, Reddy SP, Malik AB. Reactive oxygen species in inflammation and tissue injury. Antioxid Redox Signal. 2014;20(7):1126–67. Channappanavar R, Zhao J, Perlman S. T cell-mediated immune response to respiratory coronaviruses. Immunol Res. 2014;59(1–3):118–28. Huang KJ, Su IJ, Theron M, Wu YC, Lai SK, Liu CC, Lei HY. An interferon-gamma-related cytokine storm in SARS patients. Journal of medical virology. 2005;75(2):185–94. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507–13. Xu XW, Wu XX, Jiang XG, Xu KJ, Ying LJ, Ma CL, Li SB, Wang HY, Zhang S, Gao HN, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series. Bmj. 2020;368:m606. Chan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, Xing F, Liu J, Yip CC, Poon RW, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514–23. Pan L, Mu M, Yang P, Sun Y, Wang R, Yan J, Li P, Hu B, Wang J, Hu C, et al. Clinical Characteristics of COVID-19 Patients With Digestive Symptoms in Hubei, China: A Descriptive, Cross-Sectional, Multicenter Study. Am J Gastroenterol. 2020;115(5):766–73. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020;382(18):1708–20. Xiao F, Tang M, Zheng X, Liu Y, Li X, Shan H. Evidence for Gastrointestinal Infection of SARS-CoV-2. Gastroenterology. 2020;158(6):1831–3. e1833. Holshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, Bruce H, Spitters C, Ericson K, Wilkerson S, Tural A, et al. First Case of 2019 Novel Coronavirus in the United States. N Engl J Med. 2020;382(10):929–36. Kovacevic T, Miljkovic B, Mikov M, Stojisavljevic Satara S, Dragic S, Momcicevic D, Kovacevic P. The Effect of Hypoalbuminemia on the Therapeutic Concentration and Dosage of Vancomycin in Critically Ill Septic Patients in Low-Resource Countries. Dose-response: a publication of International Hormesis Society. 2019;17(2):1559325819850419. Lamers MM, Beumer J, van der Vaart J, Knoops K, Puschhof J, Breugem TI, Ravelli RBG, Paul van Schayck J, Mykytyn AZ, Duimel HQ, et al. SARS-CoV-2 productively infects human gut enterocytes. Science. 2020;369(6499):50–4. Multicenter collaboration group of Department of Science and Technology of Guangdong Province and Health Commission of Guangdong Province for Chloroquine in the treatment of novel coronavirus pneumonia. Expert consensus on chloroquine phosphate for the treatment of novel coronavirus pneumonia . Zhonghua Jie He He Hu Xi Za Zhi. 2020 March 12;43(3):185–188. doi: 10.3760/cma.j.issn.1001-0939.2020.03.009 . Gautret P, Lagier JC, Parola P, Hoang VT, Meddeb L, Mailhe M, Doudier B, Courjon J, Giordanengo V, Vieira VE, et al: Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial . International journal of antimicrobial agents 2020:105949. Wu Z, McGoogan JM: Characteristics of and Important Lessons From the Coronavirus Disease 2019 ( COVID - 19 ) Outbreak in China : Summary of a Report of 72314 Cases From the Chinese Center for Disease Control and Prevention . Jama 2020. Cite Share Download PDF Status: Published Journal Publication published 03 Feb, 2021 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Major revision 08 Nov, 2020 Review # 2 received at journal 07 Nov, 2020 Reviewer # 2 agreed at journal 04 Oct, 2020 Reviewer # 1 agreed at journal 02 Oct, 2020 Review # 1 received at journal 02 Oct, 2020 Editor assigned by journal 17 Sep, 2020 Reviewers invited by journal 17 Sep, 2020 Submission checks completed at journal 16 Sep, 2020 Editor invited by journal 15 Sep, 2020 First submitted to journal 28 Aug, 2020 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-68406","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":2410811,"identity":"b71543c6-6482-4fe8-8842-ba27d475ebf5","order_by":0,"name":"Ya Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of Army Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ya","middleName":"","lastName":"Yang","suffix":""},{"id":2410812,"identity":"be55a372-99d2-4361-9378-1bb2c05d3164","order_by":1,"name":"Xiaogang Hu","email":"","orcid":"","institution":"Chongqing university cancer hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaogang","middleName":"","lastName":"Hu","suffix":""},{"id":2410813,"identity":"190fa2c6-b2b5-41e6-991a-afdb43cdc622","order_by":2,"name":"Lirong Xiong","email":"","orcid":"","institution":"The First Affiliated Hospital of Army Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lirong","middleName":"","lastName":"Xiong","suffix":""},{"id":2410814,"identity":"f35f36de-5631-4148-8705-32082f360377","order_by":3,"name":"Peishu Fu","email":"","orcid":"","institution":"The First Affiliated Hospital of Army Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Peishu","middleName":"","lastName":"Fu","suffix":""},{"id":2410815,"identity":"bf4f8276-6b9e-44a1-a17e-2a8a838f592e","order_by":4,"name":"Wei Feng","email":"","orcid":"","institution":"The First Affiliated Hospital of Army Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Feng","suffix":""},{"id":2410816,"identity":"72a0977f-625a-466e-84be-59dfd43fecfb","order_by":5,"name":"Wei Li","email":"","orcid":"","institution":"The First Affiliated Hospital of Army Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Li","suffix":""},{"id":2410817,"identity":"70525dec-b586-4196-877c-508fe0c8418d","order_by":6,"name":"Liwen Zhang","email":"","orcid":"","institution":"Chongqing Public Health Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Liwen","middleName":"","lastName":"Zhang","suffix":""},{"id":2410818,"identity":"271091c1-cc57-40e7-9470-269a4c3d8746","order_by":7,"name":"Fengjun Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYBAC9gYgIQFmNTY+/ECMFp4DMC08h5uNJYjWAgYS6W0CPERpYe89/MKCoS5xu+TDNqB1dnK6DYS08JxLs5BgOJy4c3Zi24MChmRjswMEtNhL5JgZSDAcSNxwO7EdzNhGSAuP/BuQlrrEDTcPtknwEKVFgsf4gQQDc+KGG4zEauHJMQP6+rDxhjOJwEA2IMIvPOxnjD8DHSa74fjxhw8/VNjJEdQCBGzSkv9gbAPCykGA+SNR6WQUjIJRMApGLgAAhM8/olvq5BEAAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of Army Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Fengjun","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2020-08-29 10:47:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-68406/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-68406/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-021-05851-z","type":"published","date":"2021-02-03T15:00:42+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":2515694,"identity":"a461e6aa-a4b4-4765-8c93-710301ae2f75","added_by":"auto","created_at":"2020-09-21 15:39:39","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":241159,"visible":true,"origin":"","legend":"Kaplan-Meier curves for NCT of SARS-CoV-2 RNA according to clinical characteristics of COVID-19 patients.\nA: Fever was positively associated with NCT of viral RNA in patients [Exp (B), 0.431; 95% CI, 0.186 1.000; P=0.035]; B: Diarrhea was positively associated with NCT of viral RNA in patients [Exp (B), 0.262; 95% CI, 0.112 0.613; P=0.002]; C: Diarrhea was positively associated with NCT of viral RNA in patients [Exp (B), 0.318; 95% CI, 0.138 0.733; P=0.007]; D: Abnormalities in chest CTs were positively associated with NCT of viral RNA in patients [Exp (B), 0.209; 95% CI, 0.046 0.957; P=0.044].\n ","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-68406/v1/Fig.1.jpg"},{"id":2515695,"identity":"526e3cf0-84ad-4a8d-ae53-5609c7edec9f","added_by":"auto","created_at":"2020-09-21 15:39:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":548933,"visible":true,"origin":"","legend":"Using of antiviral medications during hospitalization in 32 patients with COVID-19 ","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-68406/v1/Fig.2.jpg"},{"id":13594385,"identity":"4aa4383d-6596-4c1f-88ea-640c1f46874c","added_by":"auto","created_at":"2021-09-17 05:20:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":892532,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-68406/v1/f290bef8-7a6b-43dc-8f08-d3234f9a2878.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eClinical Characteristics of Mild/moderate COVID-19 Patients with a Prolonged Negative Conversion Time of SARS-CoV-2 Nucleic Acid Detection\u003c/p\u003e","fulltext":[{"header":"Background","content":" \u003cp\u003eIn December 2019, novel pneumonia of unknown causes was reported in Wuhan, Hubei province in China. On February 11, 2020, the World Health Organization (WHO) officially named the disease as Coronavirus Disease 2019 (COVID-19), which caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Following the initial outbreak, COVID-19 has become a global public health emergency of international concern [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. There had been 23\u0026nbsp;million confirmed cases, and 800,000 confirmed deaths by 23 August 2020 spreaded across 216 countries and territories[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The number of COVID-19 patients has increased exponentially, causing devastation on a global scale [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMany studies have focused on the epidemiological, clinical symptoms, laboratory tests, and radiological characteristics of patients since the COVID-19 outbreak. Current epidemiological investigations show that the incubation period of COVID-19 ranges from one to fourteen days, with the majority of cases being three to seven days. The SARS-CoV-2 is mainly transmitted through respiratory droplets and by fomites [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, SARS-CoV-2 has also been isolated from anal/rectal swabs, stool specimens, and urine, suggesting fecal-oral transmission [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The main clinical symptoms of COVID-19 include fever, myalgia, dry cough, dyspnea, fatigue and diarrhea. Laboratory tests have shown that most patients had decreased white blood cell counts, increased C-reactive protein, and increased serum sedimentation rates. Computed tomograms (CT) examination showed multiple plaque shadows and interstitial changes in the early stage, which had then developed into various ground glass shadows and infiltration shadows in both lungs in the later stage. COVID-19 patients also could be asymptomatic with no associated clinical manifestations, but the SARS-CoV-2 RNA test was positive.\u003c/p\u003e \u003cp\u003eAccording to the severity of the disease, COVID-19 patients were were divided into asymptomatic, mild/moderate and severe cases. Without timely treatment, mild/moderate patients will develop into severe cases, increasing the fatality rate. It is very important to control the disease progression of mild/moderate patients. The standard of cure is the relief of symptoms and two successive negative viral nucleic acid in the \u0026ldquo;Diagnosis and Treatment Scheme of New Coronavirus Infected Pneumonia\u0026rdquo; (trial version 7)[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The negative conversion of SARS-CoV-2 RNA was essential in the discharge criteria during hospitalization [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The negative conversion time (NCT) of SARS-CoV-2 RNA is closely related to clinical manifestation and disease progression in COVID-19 patients. Hu et al. reported that NCT of SARS-CoV-2 RNA occurred in 14 days (IQR: 10\u0026ndash;18). Older age and chest tightness were independently associated with delayed clearance of SARS-CoV-2 RNA in hospitalized patients [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The COVID-19 patients with digestive symptoms are more likely to test positive for viral RNA in a stool sample and have a longer delay before viral clearance than patients with only respiratory symptoms [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Preliminary clinical treatment showed that some drugs, such as chloroquine, effectively potentiated virus clearance in COVID-19 patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, there is limited data regarding the potential predictors of NCT in mild/moderate COVID-19 patients.\u003c/p\u003e \u003cp\u003eTherefore, it was necessary to identify systematically factors associated with prolonged NCT in mild/moderate COVID-19 patients. This study analyzed clinical characteristics of mild/moderate COVID-19 patients with prolonged NCT of SARS-CoV-2 RNA, which provide a useful references for disease progression and treatment of COVID-19.\u003c/p\u003e "},{"header":"Methods","content":"\u003ch2\u003eSubjects and data collection\u003c/h2\u003e\n\u003cp\u003eThe clinical data and laboratory test results were analyzed retrospectively from 32 mild/moderate COVID-19 patients admitted to the Public Health Medical Center and Prevention of Chongqing from January 31 to February 28, 2020.\u0026nbsp;All patients were identified to be nucleic acid positive for SARS-CoV-2 and were convalescent before hospital discharge.\u003c/p\u003e\n\u003cp\u003eData was collected and recorded from each patient, which included demographic and clinical information (gender, age, smoking history, and comorbidities), clinical manifestations (fever, coughing, expectoration, anhelation, myalgia, nausea and vomiting, diarrhea, osphyalgia, etc.), and laboratory test results (standard blood counts, procalcitonin, C-reactive protein, blood biochemistry, coagulation function, and myocardial enzyme spectrum, etc). The normal range of laboratory examination is the standard of Reference Range Values for National Practice for Clinical Testing (4th Edition) published by People's Medical Publishing House[\u003ca href=\"#_ENREF_12\"\u003e12\u003c/a\u003e]. Chest CT and therapeutic drug use were also documented. Then,\u0026nbsp;the factors associated with NCT of SARS-CoV-2 RNA in upper respiratory specimens were analyzed.\u003c/p\u003e\n\u003ch2\u003eTherapeutic strategies\u003c/h2\u003e\n\u003cp\u003eStrategies of treatment for COVID-19 patients included antiviral treatment and symptomatic treatment. The primary treatment strategy for COVID-19 is combined antiviral therapy, which mainly comprises interferon-\u0026alpha;2b（IFN-\u0026alpha;2b） and lopinavir / ritonavir, or IFN-\u0026alpha;2b and ribavirin. When SARS-CoV-2 RNA was still detectable after 19 days of drug combination therapy, chloroquine phosphate was added to the antiviral treatment.\u003c/p\u003e\n\u003ch2\u003eDefinitions of basic concepts\u003c/h2\u003e\n\u003cp\u003eSputum and throat swab specimens were collected from patients. RT-PCR assay was used to detect genes of SARS-CoV-2, which were performed twice in every 24 h period. Patients with consecutive positive nucleic acid tests were confirmed as SARS-CoV-2 infection. The standard of negative conversion\u0026nbsp;is two successive negative viral nucleic acid detection tests in 24 h minimum sampling intervals. The term convalescent patients refer to recovered afebrile patients without respiratory symptoms who had two successive (minimum 24 h sampling interval) negative results for SARS-CoV-2 RNA from oropharyngeal swabs by RT-PCR.\u003c/p\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eNormally distributed continuous variables are summarized as the mean mean (standard deviation, SD), otherwise, median (interquartile range, IQR) was used to describe. Categorical variables are expressed using numbers and percentages. Cox regression analysis was used to analyze the factors. First, univariate analysis was performed, and the indicators with statistical significance were analyzed for Kaplan-Meier survival analysis. The Log Rank method was used to compare the differences between groups. A Cox proportional hazard model was used for multivariate analysis. IBM SPSS Statistics 26 was used for statistical analysis and survival image rendering. P\u0026lt;0.05 was considered to indicate a statistically significant difference.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eThe relationship between demographic and clinical information and NCT of SARS-CoV-2 RNA\u003c/h2\u003e\n\u003cp\u003eOf these patients, males accounted for 43.8% (14) of confirmed cases, and 56.3% (18) were females. The median age of males and females was 34.00 (29.00, 47.00) years and 43.00 (37.75, 57.25) years respectively, suggesting that middle-aged people were more susceptible to infection than other age groups. A total of 12.5% of patients were smokers. More than a quarter of patients (34%) had underlying diseases, including cardiovascular and cerebrovascular diseases (25%), gastrointestinal disease (15.6%), respiratory disease (12.5%), endocrine disease (9.3%), a neurological disorder (3.1%) and urinary disease (3.1%). All patient data were analyzed using the Cox regression analysis for univariate analysis. However, we found that no demographic or clinical information had a significant positive association with NCT of viral RNA in patients (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe relationship between demographic and clinical information and NCT of SARS-CoV-2 RNA in 32 patients with COVID-19\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFactors\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCount\u003c/p\u003e\n\u003cp\u003en (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e95.0% Cl for Exp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003elower limit\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003edetection limits\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32(100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge in years, median (IQR)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e34.00 (29.00, 47.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e43.00 (37.75, 57.25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge breakdown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e༜45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21(65.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.636\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.190\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.579\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.446\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e༞45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12(37.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14(43.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.689\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.325\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.398\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.411\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18(56.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4(12.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.988\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.992\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.343\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.868\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUnderlying diseases\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3(9.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.710\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.257\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.376\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.197\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.750\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.671\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.244\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoronary\u0026nbsp;heart\u0026nbsp;disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.252\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.373\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.421\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.993\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eViral hepatitis type B\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.399\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.536\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.126\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.282\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKidney stone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.880\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.169\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.155\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.786\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHyperlipemia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.199\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.550\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.221\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.370\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGout\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.593\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.578\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.078\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.305\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCerebral hemorrhage\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.593\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.578\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.078\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.305\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObstructive sleep apnea syndrome(OSAS)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.593\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.578\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.078\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.305\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAppendicectomy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.545\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.874\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.245\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.352\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHead trauma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.545\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.874\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.245\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.352\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThyroid adenoma\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.750\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.671\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.244\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChronic bronchitis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.750\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.671\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.244\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDepression\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.075\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.340\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.820\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65.691\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePneumonia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.258\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.312\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.342\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAppendicitis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.258\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.312\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.342\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eData are shown as n (%) or IQR unless specified otherwise.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eThe Log Rank method was used to compare the differences between groups, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate a statistically significant difference (indicated by *).\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003eThe relationship between clinical manifestation and NCT of SARS-CoV-2 RNA\u003c/h2\u003e\n\u003cp\u003eThe median duration from disease onset to hospital admission was 3.5 (IQR: 2\u0026ndash;6) days, with a median of 20 days from illness onset to hospital discharge (IQR: 15.25\u0026ndash;26) and the median time from positive to negative conversion of SARS-CoV-2 RNA was 19.5 days (IQR: 14.25\u0026ndash;25). The majority of the patients showed an initial symptom of fever (75%), but a quarter of the patients were afebrile, alerting the need for the caution of atypical cases. In addition to fever, other clinical symptoms mainly included fatigue (78.1%), expectoration (56.3%), diarrhea (68.8%), nausea (37.5%), anhelation (34.4%), and throat discomfort (34.4%). Clinical manifestations of the study population are summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe relationship between clinical manifestation and NCT of SARS-CoV-2 RNA in 32 patients with COVID-19\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFactors\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCount\u003c/p\u003e\n\u003cp\u003en (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e95.0% Cl for Exp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003elower limit\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003edetection limits\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32(100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFever\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24(75.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.050*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.431\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.186\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCough\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25(78.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.564\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.779\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.334\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.818\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eExpectoration\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18(56.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.335\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.707\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.349\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.431\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAnhelation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11(34.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.714\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.871\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.416\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.822\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThroat discomfort\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11(34.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.669\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.852\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.409\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.775\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeadache and dizziness\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7(21.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.323\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.650\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.277\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.526\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMyodynia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7(21.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.123\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.491\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.199\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.213\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOsphyalgia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.341\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.495\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.117\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.103\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiarrhea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22(68.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.007*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.318\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.138\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.733\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVentosity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.524\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.622\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.145\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.677\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNausea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12(37.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.002*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.262\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.112\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.613\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVomiting\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3(9.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.314\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.161\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.482\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.686\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMuscular stiffness\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5(15.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.235\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.559\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.214\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.460\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChills\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.126\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.288\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.716\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.105\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFatigue\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9(28.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.509\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.768\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.350\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.683\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSnot\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3(9.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.123\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.387\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.113\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.329\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsomnia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5(15.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.444\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.678\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.250\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.836\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChest tightness\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5(15.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.978\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.385\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.670\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBitter taste and thirst\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4(12.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.703\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.231\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.422\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.588\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eData are shown as n (%) unless specified otherwise.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eThe Log Rank method was used to compare the differences between groups, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate a statistically significant difference (indicated by *).\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe Cox regression analysis was used for univariate analysis; we found that fever, nausea, and diarrhea were a significant positive association with NCT of viral RNA in patients (P\u0026thinsp;\u0026lt;\u0026thinsp;0.005, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The KaplanMeier curves revealed that fever, nausea, and diarrhea had a significantly prolonged NCT of SARS-CoV-2 RNA compared with the normality\u0026rsquo;s group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA, B, C).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eThe relationship between laboratory findings and NCT of SARS-CoV-2 RNA\u003c/h2\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, the laboratory inspection section showed that 43.8% of the patients developed leucopenia, and 28.1% of patients had lymphocytopenia. The hemoglobin, platelets, and albumin levels were lower in 53.1%, 37.5%, and 34.4% of patients, respectively. The levels of procalcitonin, C-reactive protein, total bilirubin, direct bilirubin, creatinine, lactic dehydrogenase were increased in 9.4%, 40.6%, 40.6%, 46.9%, 25%, and 21.9% of patienst, respectively. All patient data were analyzed using the Cox regression analysis for univariate analysis. Still, there were no significant findings with a positive association with NCT of viral RNA in patients (P\u0026thinsp;\u0026gt;\u0026thinsp;0.005, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe relationship between laboratory findings and NCT of SARS-CoV-2 RNA in 32 patients with COVID-19\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFactors\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCount\u003c/p\u003e\n\u003cp\u003en (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e95.0% Cl for Exp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003elower limit\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003edetection limits\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32(100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLeukocyte count decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14(43.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.612\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.301\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.246\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutrophil count decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8(25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.661\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.836\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.375\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.864\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutrophil percentage decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9(28.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.171\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.581\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.267\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.263\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLymphocyte count decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12(37.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.959\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.494\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.102\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLymphocyte percentage decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9(28.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.529\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.275\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.598\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.718\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eErythrocyte count decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24(75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.942\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.031\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.453\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.349\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHemoglobin decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17(53.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.678\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.858\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.417\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.765\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003epackcd cell \u0026nbsp;volume (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20(62.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.722\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.140\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.554\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.344\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePlatelet count decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12(37.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.140\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.823\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.820\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.052\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProcalcitonin increase (\u0026uarr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3(9.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.536\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.477\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.429\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.091\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC-Reactive Protein increase (\u0026uarr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13(40.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.492\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.302\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.614\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.761\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal Protein (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21(65.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.934\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.032\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.494\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.155\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAlbumin decrease (\u0026darr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11(34.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.824\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.920\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.442\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.917\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal bilirubin increase (\u0026uarr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13(40.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.297\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.465\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.715\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDirect bilirubin increase (\u0026uarr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15(46.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.339\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.411\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.697\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.859\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCreatinine increase (\u0026uarr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8(25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.936\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.968\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.433\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.163\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLactic dehydrogenase increase (\u0026uarr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7(21.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.993\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.004\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.433\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.327\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eD-Dimer increase (\u0026uarr;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.783\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.227\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.286\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.260\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eData are shown as n (%) unless specified otherwise.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eThe Log Rank method was used to compare the differences between groups, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate a statistically significant difference (indicated by *).\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003eThe relationship between radiological findings and NCT of SARS-CoV-2 RNA\u003c/h2\u003e\n\u003cp\u003eGround-glass opacity (GGO) and high-density shadow were the typical radiological findings on chest CT scan. Abnormalities in chest CT were detected in 93.8% of patients. A total of 87.5% of patients had ground-grass opacities over bilateral lungs, which was the most common pattern of CT changes and corresponded to pathological diffuse alveolar damage [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eWe analyzed the univariate analysis using the Cox regression and found that abnormalities in chest CT were a significant positive association with NCT of viral RNA in patients (P\u0026thinsp;\u0026lt;\u0026thinsp;0.005, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The Kaplan Meier curves revealed that abnormalities in chest CT had a significantly prolonged NCT of SARS-CoV-2 RNA compared with normality\u0026rsquo;s group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe relationship between radiological findings\u003csup\u003ea\u003c/sup\u003e and NCT of SARS-CoV-2 RNA in 32 patients with COVID-19\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFactors\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCount\u003c/p\u003e\n\u003cp\u003en (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e95.0% Cl for Exp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003elower limit\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003edetection limits\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32(100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAbnormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30(93.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.044*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.209\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.046\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.957\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInvolved lung field\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUnilateral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8(25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.202\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.570\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.241\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.350\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBilateral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22(68.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.503\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.314\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.591\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.920\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRadiological characteristics\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGround-grass opacities\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28(87.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.940\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.960\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.331\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2,782\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh-density shadow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17(53.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.083\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.536\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.265\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.086\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eData are shown as n (%) unless specified otherwise.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eThe Log Rank method was used to compare the differences between groups, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate a statistically significant difference (indicated by *).\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003eHow many patients have the following lesion location.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003ch2\u003eTaking antiviral medications during hospitalization\u003c/h2\u003e\n\u003cp\u003eAll patients received antiviral therapy during hospitalization. All 32 patients were treated with IFN-\u0026alpha;2b. Utilization rates of opinavir/ritonavir, ribavirin, and chloroquine phosphate were treated in 84.4%, 46.9%, and 40.6% of patients, respectively. The proportion of patients receiving combined treatment using IFN-\u0026alpha;2b plus lopinavir/ritonavir, IFN-\u0026alpha;2b plus ribavirin, IFN-\u0026alpha;2b plus lopinavir/ritonavir plus ribavirin, and IFN-\u0026alpha;2b plus chloroquine phosphate were 75%, 12.5%, 12.5%, 40.6%, respectively (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003ePredictors of NCT\u003c/h2\u003e\n\u003cp\u003eWe had summarized the results of the univariate analysis that fever, nausea, diarrhea, and abnormalities in chest CT had a significantly prolonged NCT of SARS-CoV-2 RNA. To analyze factors on NCT of SARS-CoV-2 RNA systematically, the multivariate Cox's proportional hazard model was used to analyze the multivariate analyses. We revealed that fever [Exp (B), 0.284; 95% CI, 0.1140.707; P\u0026thinsp;\u0026lt;\u0026thinsp;0.005] and nausea [Exp (B), 0.257; 95%CI, 0.0960.689; P\u0026thinsp;\u0026lt;\u0026thinsp;0.005] were independent factors in prolonged NCT of SARS-CoV-2 RNA in patients with COVID-19 (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eIndependent factors of negative conversion time by the multivariate Cox's proportional hazard model\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eFactors\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e95.0% CI for Exp(B)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003elower limit\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003edetection limits\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFever\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.007*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.284\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.707\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNausea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.007*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.257\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.096\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.689\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiarrhea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.376\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.648\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.248\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.692\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCT imaging\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.150\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.299\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.058\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.550\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eA Cox proportional hazard model was used for multivariate analysis, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate a statistically significant difference (indicated by *).\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":" \u003cp\u003eCOVID-19 is a global pandemic that has rapidly spread worldwide since reported in December 2019. A negative nucleic acid test of SARS-CoV-2 is the standard for a cure of COVID-19. To investigate the timeline of RNA negative conversion of COVID-19 patients, this study retrospectively analyzed clinical characteristics in a cohort of mild/moderate hospitalized patients in Chongqing, China. We found that fever, nausea, diarrhea, and abnormalities in chest CT were correlated to a prolonged NCT of SARS-CoV-2 RNA. More importantly, fever and nausea were the independent factors predicting NCT of mild/moderate COVID-19 patients.\u003c/p\u003e \u003cp\u003eFever, a respiratory manifestation, is the most commonly reported symptom in patients infected with SARS-CoV-2 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Accordingly, fever may be a clinical sign of poor prognosis in patients and response to the release of inflammatory mediators such as cytokines and chemokines [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These inflammatory mediators cause tissue damage and organ dysfunction by stimulating toxic oxygen derivatives suggesting that the NCT of SARS-CoV-2 RNA may be prolonged in patients [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChest CT has a high sensitivity to detect lung abnormalities, which is quite helpful in the early diagnosis of the disease. The \u0026ldquo;Diagnosis and Treatment Scheme for Coronavirus Disease (Trial Version 7)\u0026rdquo; recommended that a CT examination serves as the diagnostic basis for COVID-19. For chest imaging in patients with COVID-19, the early manifestation was multiple plaque shadows and interstitial changes. The later development was multiple ground glass shadows and infiltration shadows in both lungs. In severe cases, lung consolidation can occur, presenting as \u0026ldquo;white lung,\u0026rdquo; which may be related to the immunopathology. Most studies have suggested that a dysregulated/exuberant innate responses are the primary cause of coronavirus-mediated pathology [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Many cytokines or chemokines are involved in the immune storm after the infection of coronavirus,which eventually leads to lung injury and acute respiratory distress syndrome [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The improvement of chest CT was after that of body temperature. Still, it preceded the negative conversion of nucleic acid tests, suggesting that abnormalities in chest CT could indirectly reflect the persistence of SARS-CoV-2 RNA in patients with COVID-19. Our study found that abnormalities in chest CT could prolong the NCT of patients with COVID-19. Therefore, the improvement of chest CT as soon as possible has an essential effect on shortening NCT in patients with COVID-19 and promoting patients to be discharged more rapidly.\u003c/p\u003e \u003cp\u003eAlthough COVID-19 most commonly presents with respiratory symptoms, such as cough and shortness of breath [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], there is evidence that the illness can also present with nonrespiratory symptoms, most notably digestive symptoms such as diarrhea, diminished appetite, nausea, and vomiting [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Diarrhea appeared to be the most common GI complaint [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], followed by nausea and vomiting [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. SARS-CoV-2 RNA was detected in stool samples from COVID-19 patients for the first time, first reported in the United States [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Viral RNA was still positive in gastrointestinal specimens even after levels could not be detected in respiratory samples [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], implying direct infectivity of the virus on the intestinal tract. Current research shows that the primary target organ of COVID-19 is the lung, but clinical evidence suggests that the gastrointestinal tract may be another viral target organ.\u003c/p\u003e \u003cp\u003eThe SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) has been found in both upper and lower gastrointestinal tract where its expression level was nearly 100 times higher than that of respiratory organs [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Patients with symptoms of the digestive system have more viruses in their gut [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and maybe more likely to cause direct damage to the intestinal mucosa. Our research found that digestive symptoms, including nausea and diarrhea, are the factors of NCT of COVID-19 patients, suggesting that patients with gastrointestinal symptoms should seek medical care to avoid delayed diagnosis and prolong treatment time.\u003c/p\u003e \u003cp\u003eChinese experts recommend that patients diagnosed as mild, moderate, and severe cases of COVID-19 pneumonia and without contraindications to chloroquine, be treated with 500\u0026nbsp;mg of chloroquine twice a day for ten days[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In our study, when SARS-CoV-2 RNA was still detectable after 19 days of drug combination therapy, chloroquine was added to the antiviral treatment. Thirteen patients were treated with chloroquine and a median duration of viral shedding of 6.0 (IQR: 5.0\u0026ndash;7.0) days. Therefore, these results suggest that chloroquine may play a role in reducing viral load and shortening the time of virus negative transition. Other studies have also confirmed the role of chloroquine in promoting virus negative conversion and shortening the disease course. Other studies have also confirmed the role of chloroquine in promoting virus negative conversion, shortening the course of the disease [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and reducing/eliminating viral load in COVID-19 patients [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, we did not conduct a randomized controlled study to evaluate the efficacy of chloroquine and most infections with COVID-19 were self-limited, about 15% of infected adults developed severe pneumonia that required treatment [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], the numerical reduction in time to clinical improvement in those treated with chloroquine requires confirmation in more extensive studies.\u003c/p\u003e \u003cp\u003eThere are several limitations to our study. First, the sample size of this study is not large enough. Second, we have not conducted randomized controlled trials, so we cannot determine the therapeutic effect of chloroquine on COVID-19 and its impact on shortening the time of negative viral conversion.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eIn conclusion, our study suggests that fever, nausea, diarrhea and abnormalities in chest CT hve a significantly prolonged NCT of SARS-CoV-2 RNA in mild/moderate COVID-19 patients. More importantly, fever and nausea are the independent factors in predicting NCT of SARS-CoV-2 RNA. Meanwhile, we should pay attention to gastrointestinal symptoms and provide timely treatment. This study provide a useful references for disease progression and treatment of COVID-19.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eCOVID-19: Coronavirus disease 2019; SARS-CoV-2: Severe Acute Respiratory Syndrome Coronavirus-2; NCT: Negative conversion time; RT-PCR: Reverse Transcription-polymerase Chain Reaction; CT: Computerized tomography; IFN-\u0026alpha;2b: Interferon-\u0026alpha;2b; IQR: Interquartile range; GGO: Ground-glass opacities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study was conducted following the Declaration of Helsinki. It was approved by the Ethics Commission of Chongqing Public Health Medical Center (ethics approval registration number:2020-043-01-KY) and written informed consent was waived in consideration of the emergency of infectious disease.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003eFS, LZ, YY and XH conceived and designed the project and had roles in the data analysis, data interpretation, literature search, and writing of the manuscript. LX, PF, WF and WL had roles in data collection, data interpretation, iterature search, and writing of the manuscript. LZ had roles in clinical management and data collection, and had full access to all of the data in the study and take responsibility for the integrity of the data. The authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe would like to thank all physicians that participated in this study for patient enrollment and follow-up.\u003c/p\u003e\n\u003ch2\u003eAuthor details\u003c/h2\u003e\n\u003cp\u003e1 Department of Pharmacy, The First Affiliated Hospital of Army Medical University, Chongqing,400038, China. 2 Department of pharmacy, Chongqing University Cancer Hospital, Chongqing, 400030, China. 3Department of Tuberculosis, Chongqing Public Health Medical Center, Chongqing, 400036, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e \u003cspan\u003eZhu N, Zhang D, Wang W, Li X, Yang B, Song J, Zhao X, Huang B, Shi W, Lu R, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med. 2020;382(8):727\u0026ndash;33.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eWorld Health Organisation (WHO). \u003cb\u003eNovel Coronavirus\u003c/b\u003e. (2019-\u003cb\u003enCoV\u003c/b\u003e) \u003cb\u003esituation reports\u003c/b\u003e: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/]\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eReuben RC, Danladi MMA, Pennap GR. Is the COVID-19 pandemic masking the deadlier Lassa fever epidemic in Nigeria? Journal of clinical virology: the official publication of the Pan American Society for Clinical Virology. 2020;128:104434.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eWu F, Zhao S, Yu B, Chen YM, Wang W, Song ZG, Hu Y, Tao ZW, Tian JH, Pei YY, et al. A new coronavirus associated with human respiratory disease in China. Nature. 2020;579(7798):265\u0026ndash;9.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLing Y, Xu SB, Lin YX, Tian D, Zhu ZQ, Dai FH, Wu F, Song ZG, Huang W, Chen J, et al. Persistence and clearance of viral RNA in 2019 novel coronavirus disease rehabilitation patients. Chin Med J. 2020;133(9):1039\u0026ndash;43.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNational Health Commission of China. \u003cb\u003eNew coronavirus pneumonia prevention and control program\u003c/b\u003e (\u003cb\u003e7th edn\u003c/b\u003e). Mar 4. 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.nhc.gov.cn/yzygj/s7653p/202003/46c\u003c/span\u003e\u003c/span\u003e9294a7dfe4cef80dc7f5912eb1989.shtml?spm=C73544894212.P59511941341.0.0.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChan JF, Yip CC, To KK, Tang TH, Wong SC, Leung KH, Fung AY, Ng AC, Zou Z, Tsoi HW, et al: \u003cb\u003eImproved Molecular Diagnosis of COVID-19 by the Novel, Highly Sensitive and Specific COVID-19-RdRp/Hel Real-Time Reverse Transcription-PCR Assay Validated In Vitro and with Clinical Specimens\u003c/b\u003e. \u003cem\u003eJournal of clinical microbiology\u003c/em\u003e 2020, 58(5).\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChu DKW, Pan Y, Cheng SMS, Hui KPY, Krishnan P, Liu Y, Ng DYM, Wan CKC, Yang P, Wang Q, et al. Molecular Diagnosis of a Novel Coronavirus (2019-nCoV) Causing an Outbreak of Pneumonia. Clinical chemistry. 2020;66(4):549\u0026ndash;55.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eHu X, Xing Y, Jia J, Ni W, Liang J, Zhao D, Song X, Gao R, Jiang F. Factors associated with negative conversion of viral RNA in patients hospitalized with COVID-19. Sci Total Environ. 2020;728:138812.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eHan C, Duan C, Zhang S, Spiegel B, Shi H, Wang W, Zhang L, Lin R, Liu J, Ding Z, et al. Digestive Symptoms in COVID-19 Patients With Mild Disease Severity: Clinical Presentation, Stool Viral RNA Testing, and Outcomes. Am J Gastroenterol. 2020;115(6):916\u0026ndash;23.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGao J, Tian Z, Yang X. Breakthrough: Chloroquine phosphate has shown apparent efficacy in treatment of COVID-19 associated pneumonia in clinical studies. Bioscience trends. 2020;14(1):72\u0026ndash;3.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eNational Practice for Clinical Testing (4th Edition).Beijing: People's Medical Publishing House. (2015).\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChong S, Kim TS, Cho EY. Herpes simplex virus pneumonia: high-resolution CT findings. Br J Radiol. 2010;83(991):585\u0026ndash;9.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eHuang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497\u0026ndash;506.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eWang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, et al: \u003cb\u003eClinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus\u003c/b\u003e-\u003cb\u003eInfected Pneumonia in Wuhan\u003c/b\u003e, \u003cb\u003eChina\u003c/b\u003e. \u003cem\u003eJama\u003c/em\u003e 2020.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChen H, Lin C, Fan Z, Yu W, Cao M, Ke C, Jiao X. Serum cytokines and clinical features in patients with fever and thrombocytopenia syndrome. Clin Chim Acta. 2019;494:22\u0026ndash;30.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLiu Y, Freed DC, Li L, Tang A, Li F, Murray EM, Adler SP, McVoy MA, Rupp RE, Barrett D, et al: \u003cb\u003eA Replication-Defective Human Cytomegalovirus Vaccine Elicits Humoral Immune Responses Analogous to Those with Natural Infection\u003c/b\u003e. \u003cem\u003eJournal of virology\u003c/em\u003e 2019, 93(23).\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eKorish AA, Arafa MM. Propolis derivatives inhibit the systemic inflammatory response and protect hepatic and neuronal cells in acute septic shock. The Brazilian journal of infectious diseases: an official publication of the Brazilian Society of Infectious Diseases. 2011;15(4):332\u0026ndash;8.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMittal M, Siddiqui MR, Tran K, Reddy SP, Malik AB. Reactive oxygen species in inflammation and tissue injury. Antioxid Redox Signal. 2014;20(7):1126\u0026ndash;67.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChannappanavar R, Zhao J, Perlman S. T cell-mediated immune response to respiratory coronaviruses. Immunol Res. 2014;59(1\u0026ndash;3):118\u0026ndash;28.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eHuang KJ, Su IJ, Theron M, Wu YC, Lai SK, Liu CC, Lei HY. An interferon-gamma-related cytokine storm in SARS patients. Journal of medical virology. 2005;75(2):185\u0026ndash;94.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507\u0026ndash;13.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eXu XW, Wu XX, Jiang XG, Xu KJ, Ying LJ, Ma CL, Li SB, Wang HY, Zhang S, Gao HN, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series. Bmj. 2020;368:m606.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, Xing F, Liu J, Yip CC, Poon RW, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514\u0026ndash;23.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003ePan L, Mu M, Yang P, Sun Y, Wang R, Yan J, Li P, Hu B, Wang J, Hu C, et al. Clinical Characteristics of COVID-19 Patients With Digestive Symptoms in Hubei, China: A Descriptive, Cross-Sectional, Multicenter Study. Am J Gastroenterol. 2020;115(5):766\u0026ndash;73.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGuan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020;382(18):1708\u0026ndash;20.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eXiao F, Tang M, Zheng X, Liu Y, Li X, Shan H. Evidence for Gastrointestinal Infection of SARS-CoV-2. Gastroenterology. 2020;158(6):1831\u0026ndash;3. e1833.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eHolshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, Bruce H, Spitters C, Ericson K, Wilkerson S, Tural A, et al. First Case of 2019 Novel Coronavirus in the United States. N Engl J Med. 2020;382(10):929\u0026ndash;36.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eKovacevic T, Miljkovic B, Mikov M, Stojisavljevic Satara S, Dragic S, Momcicevic D, Kovacevic P. The Effect of Hypoalbuminemia on the Therapeutic Concentration and Dosage of Vancomycin in Critically Ill Septic Patients in Low-Resource Countries. Dose-response: a publication of International Hormesis Society. 2019;17(2):1559325819850419.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLamers MM, Beumer J, van der Vaart J, Knoops K, Puschhof J, Breugem TI, Ravelli RBG, Paul van Schayck J, Mykytyn AZ, Duimel HQ, et al. SARS-CoV-2 productively infects human gut enterocytes. Science. 2020;369(6499):50\u0026ndash;4.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMulticenter collaboration group of Department of Science and Technology of Guangdong Province and Health Commission of Guangdong Province for Chloroquine in the treatment of novel coronavirus pneumonia. \u003cb\u003eExpert consensus on chloroquine phosphate for the treatment of novel coronavirus pneumonia\u003c/b\u003e. Zhonghua Jie He He Hu Xi Za Zhi. 2020 March 12;43(3):185\u0026ndash;188. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3760/cma.j.issn.1001-0939.2020.03.009\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGautret P, Lagier JC, Parola P, Hoang VT, Meddeb L, Mailhe M, Doudier B, Courjon J, Giordanengo V, Vieira VE, et al: \u003cb\u003eHydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial\u003c/b\u003e. \u003cem\u003eInternational journal of antimicrobial agents\u003c/em\u003e 2020:105949.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eWu Z, McGoogan JM: \u003cb\u003eCharacteristics of and Important Lessons From the Coronavirus Disease 2019\u003c/b\u003e (\u003cb\u003eCOVID\u003c/b\u003e-\u003cb\u003e19\u003c/b\u003e) \u003cb\u003eOutbreak in China\u003c/b\u003e: \u003cb\u003eSummary of a Report of 72314 Cases From the Chinese Center for Disease Control and Prevention\u003c/b\u003e. \u003cem\u003eJama\u003c/em\u003e 2020.\u003c/span\u003e \u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, SARS-CoV-2, Clinical characteristics, Negative conversion time","lastPublishedDoi":"10.21203/rs.3.rs-68406/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-68406/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003e\u0026nbsp;The impact of COVID-19 has been devastating on a global scale. Our study aimed to identify factors in predicting prolonged negative conversion time (NCT) of SARS-CoV-2 RNA in mild/moderate COVID-19 patients. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThe clinical features and treatment outcomes were retrospectively analyzed from 32 hospitalized mild/moderate COVID-19 patients. Then univariate and multivariate analysis were used to predict in the factors of prolonged NCT of SARS-CoV-2 RNA.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe general clinical symptoms were cough (78.1%), fever (75%), diarrhea (68.8%), expectoration (56.3%), and nausea (37.5%). More than 40% of the patients had decreased erythrocyte, hemoglobin and leucocyte and 93.8% patients were detected in abnormalities of chest CT. The median NCT of SARS-CoV-2 RNA was 19.5 days (IQR: 14.25–25). Univariate analysis found fever, nausea, diarrhea and abnormalities in chest CTs were positively associated with prolonged NCT of viral RNA (P\u0026lt;0.05). The multivariate Cox proportional hazard model revealed that fever [Exp (B), 0.284; 95% CI, 0.114‑0.707; P＜0.05] and nausea [Exp (B), 0.257; 95%CI, 0.096‑0.689; P＜0.05] were two significant independent factors. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eFever, nausea, diarrhea and abnormalities in chest CT are potential factors for predicting prolonged NCT of viral RNA. Moreover, Fever and nausea were two significant independent factors in prolonged NCT of viral RNA in mild/moderate COVID-19 patients.\u003c/p\u003e","manuscriptTitle":"Clinical Characteristics of Mild/moderate COVID-19 Patients with a Prolonged Negative Conversion Time of SARS-CoV-2 Nucleic Acid Detection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-09-21 15:39:37","doi":"10.21203/rs.3.rs-68406/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2020-11-09T00:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-11-08T00:00:00+00:00","index":2,"fulltext":"Recommendation: Major revisions required\nForm responses:\n---\n\nComments to Author:\n---\nThe article entitled 'Clinical characteristics of mild/moderate COVID-19 patients with a prolonged negative conversion time of SARS-CoV-2 nucleic acid detection' is quite interesting. The statistical analysis is well conducted. The data about the digestive symptoms and the NCT conversion time are interesting.\nA major limitations of this study is the small number of patients.\nI suggest to add in the univariate and multivariate analysis the duration from onset fever, at home also and not only during the hospitalization as well as from digestive symptoms.\nConcerning the chloroquine there are controversial data, I suggest to put this information only in the results section and not in the discussion part.\n\nI suggest to summarize the underlying diseases in Table 1, to remove table 2 and put symptoms and signs in table 1. Remove Table 3.\n\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"reviewerAgreed","content":"","date":"2020-10-04T12:00:00+00:00","index":2,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-10-02T12:00:00+00:00","index":1,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-10-02T12:00:00+00:00","index":1,"fulltext":"Recommendation: Reject\nForm responses:\n---\n\nComments to Author:\n---\nYang et al. report factors associated with prolonged SARS-Cov-2 positive PCR in patients with mild/moderate COVID-19.\nThe manuscript is affected by several weakpoints including a small sample size, unclear methods for collecting swabs, lack of references and an incompletely full discussion.\nAdditional points:\nComments to Yang et al.\n\n * Abstract\n ◦ Predict factors associated with…\n ◦ There is no definition of \"prolonged time\"\n ◦ In the Conclusions I will include only factors that were singificant at the Multivariate analysis\n\n * Background\n ◦ I would suggest to shorten the introduction on general features of COVID-19 (unfortuntaely weel known to all the readers) and concnetrate on the severity of the diseases and associated factors as well as on the available data of time to negative PCR\n ◦ I would also include CDC data on positive PCR but no infectivity after 10 days in order to critically discuss the authors' findings\n\n * M\u0026M\n ◦ What about the initial viral load? I believe it could a significant factor to be included in the analysis\n ◦ How often nasopharingeal swabs were performed? I was not able to find this pieceof information that may be relevant for the observe results\n\n * Results\n ◦ Page 9 line 34 \"lopinavir\" typo\n ◦ There is no mention of diffrential time to negative PCR according to different treatments\n\n * Discussion\n ◦ There are several references missing on factors associated with prolonged sheding and infectivity\n ◦ The discussion on hydroxychlorouqine effect is interesting but it should included in the Results section while here all data against HCQ administration need to be cited.* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Declaration of competing interests: **No competing interest**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **No**\n* Are the methods sufficiently described to allow the study to be repeated?: **No**\n* Is the use of statistics and treatment of uncertainties appropriate?: **No**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"editorAssigned","content":"","date":"2020-09-17T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-09-17T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-09-16T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-09-15T12:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2020-08-28T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"61b4c57c-45ee-4d6c-bec9-fe9b22b49596","owner":[],"postedDate":"September 21st, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":562812,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2021-02-07T15:03:21+00:00","versionOfRecord":{"articleIdentity":"rs-68406","link":"https://doi.org/10.1186/s12879-021-05851-z","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2021-02-03 15:00:42","publishedOnDateReadable":"February 3rd, 2021"},"versionCreatedAt":"2020-09-21 15:39:37","video":"","vorDoi":"10.1186/s12879-021-05851-z","vorDoiUrl":"https://doi.org/10.1186/s12879-021-05851-z","workflowStages":[]},"version":"v1","identity":"rs-68406","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-68406","identity":"rs-68406","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}