| Title:
|
Recurrence of SARS-CoV-2 PCR positivity in COVID-19 patients: a single center experience and potential implications |
| Abstract:
|
IMPORTANCE How to appropriately care for patients who become PCR-negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still not known. Patients who have recovered from coronavirus disease 2019 (COVID-19) could profoundly impact the health care system if a subset were to be PCR-positive again with reactivated SARS-CoV-2. OBJECTIVE To characterize a single center COVID-19 cohort with and without recurrence of PCR positivity, and develop an algorithm to identify patients at high risk of retest positivity after discharge to inform health care policy and case management decision-making. DESIGN, SETTING, AND PARTICIPANTS A cohort of 414 patients with confirmed SARS-CoV-2 infection, at The Second Affiliated Hospital of Southern University of Science and Technology in Shenzhen, China from January 11 to April 23, 2020. EXPOSURES Polymerase chain reaction (PCR) and IgM-IgG antibody confirmed SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES Univariable and multivariable statistical analysis of the clinical, laboratory, radiologic image, medical treatment, and clinical course of admission/quarantine/readmission data to develop an algorithm to predict patients at risk of recurrence of PCR positivity. RESULTS 16.7% (95CI: 13.0%-20.3%) patients retest PCR positive 1 to 3 times after discharge, despite being in strict quarantine. The driving factors in the recurrence prediction model included: age, BMI; lowest levels of the blood laboratory tests during hospitalization for cholinesterase, fibrinogen, albumin, prealbumin, calcium, eGFR, creatinine; highest levels of the blood laboratory tests during hospitalization for total bilirubin, lactate dehydrogenase, alkaline phosphatase; the first test results during hospitalization for partial pressure of oxygen, white blood cell and lymphocyte counts, blood procalcitonin; and the first test episodic Ct value and the lowest Ct value of the nasopharyngeal swab RT PCR results. Area under the ROC curve is 0.786. CONCLUSIONS AND RELEVANCE This case series provides clinical characteristics of COVID-19 patients with recurrent PCR positivity, despite strict quarantine, at a 16.7% rate. Use of a recurrence prediction algorithm may identify patients at high risk of PCR retest positivity of SARS-CoV-2 and help modify COVID-19 case management and health policy approaches. |
| Published:
|
5/10/2020 |
| DOI:
|
10.1101/2020.05.06.20089573 |
| DOI_URL:
|
http://doi.org/10.1101/2020.05.06.20089573 |
| Author Name:
|
Huang, J |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/huang_j |
| Author Name:
|
Zheng, L |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/zheng_l |
| Author Name:
|
Li, Z |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_z |
| Author Name:
|
Hao, S |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/hao_s |
| Author Name:
|
Ye, F |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/ye_f |
| Author Name:
|
Chen, J |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/chen_j |
| Author Name:
|
Yao, X |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/yao_x |
| Author Name:
|
Liao, J |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/liao_j |
| Author Name:
|
Wang, S |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/wang_s |
| Author Name:
|
Zeng, M |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/zeng_m |
| Author Name:
|
Qiu, L |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/qiu_l |
| Author Name:
|
Cen, F |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/cen_f |
| Author Name:
|
Huang, Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/huang_y |
| Author Name:
|
Zhu, T |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/zhu_t |
| Author Name:
|
Xu, Z |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/xu_z |
| Author Name:
|
Ye, M |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/ye_m |
| Author Name:
|
Yang, Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/yang_y |
| Author Name:
|
Wang, G |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/wang_g |
| Author Name:
|
Li, J |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_j |
| Author Name:
|
Wang, L |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/wang_l |
| Author Name:
|
Qu, J |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/qu_j |
| Author Name:
|
Yuan, J |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/yuan_j |
| Author Name:
|
Zheng, W |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/zheng_w |
| Author Name:
|
Zhang, Z |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/zhang_z |
| Author Name:
|
Li, C |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_c |
| Author Name:
|
Whitin, J C |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/whitin_j_c |
| Author Name:
|
Tian, L |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/tian_l |
| Author Name:
|
Chubb, H |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/chubb_h |
| Author Name:
|
Hwa, K |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/hwa_k |
| Author Name:
|
Gans, H A |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/gans_h_a |
| Author Name:
|
Ceresnak, S R |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/ceresnak_s_r |
| Author Name:
|
Zhang, W |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/zhang_w |
| Author Name:
|
Lu, Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/lu_y |
| Author Name:
|
Maldonado, Y A |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/maldonado_y_a |
| Author Name:
|
Cohen, H J |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/cohen_h_j |
| Author Name:
|
McElhinney, D B |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/mcelhinney_d_b |
| Author Name:
|
Sylvester, K G |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/sylvester_k_g |
| Author Name:
|
He, Q |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/he_q |
| Author Name:
|
Wang, Z |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/wang_z |
| Author Name:
|
Liu, Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/liu_y |
| Author Name:
|
Liu, L |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/liu_l |
| Author Name:
|
Ling, X B |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/ling_x_b |
| sha:
|
3074b51f9b6134655dffc154c8b99442047337d7 |
| license:
|
medrxiv |
| source_x:
|
MedRxiv; WHO |
| source_x_url:
|
https://www.who.int/ |
| url:
|
http://medrxiv.org/cgi/content/short/2020.05.06.20089573v1?rss=1
https://doi.org/10.1101/2020.05.06.20089573 |
| has_full_text:
|
TRUE |
| Keywords Extracted from Text Content:
|
coronavirus disease 2019
COVID-19 patients
COVID-19
medRxiv
IgM-IgG
patients
coronavirus 2
blood
SARS-CoV-2
ABSTRACT
Patients
medRxiv preprint
SARS-CoV-2 virus
upper tract
COVID-19
line
people
individuals
Shanghai GeneoDx
medRxiv
XGBoost
coronavirus
blood
blood cell
(re)admissions
nasopharyngeal
pulmonary
anal swabs
albumin
medRxiv preprint
N=309
blood procalcitonin
SARS-Cov-2
patient
ORF1ab
plasma
GZ-D2RM25
calcium
Shenzhen, China
cholinesterase
oxygen
SARS-CoV-2
Xiamen
catalog no. Gxzz 20203400198
SARS-CoV-2 IgM
N=19
Bronchoalveolar lavage
COVID-19 patients
prealbumin
SARS-CoV-2 antibody
microparticle
patients
bilirubin
nasopharyngeal swab
IgG
creatinine
SARS-CoV-2 RNA 9
nasopharyngeal swabs
eGFR
lymphocyte
medRxiv preprint Figure 1
alkaline
N=73
lactate dehydrogenase
fibrinogen
Patients
nasopharyngeal swab samples |
| Extracted Text Content in Record:
|
First 5000 Characters:medRxiv preprint
Question What are the characteristics, clinical presentations, and outcomes of COVID-19 patients with PCR retest positivity after resolution of the initial infection and consecutive negative tests? Can we identify recovered patients, prior to discharge, at risk of the recurrence of SARS-CoV-2 PCR positivity?
Findings In this series of 414 COVID-19 inpatients discharged to a designated quarantine center, 69 retest positive (13 with 2 readmissions, and 3 with 3 readmissions). A multivariable model was developed to predict the risk of the recurrence of SARS-CoV-2 PCR positivity.
Meaning Rate and timing of the recurrence of PCR positivity following strict quarantine were characterized. Our prediction algorithm may have implications for ABSTRACT IMPORTANCE How to appropriately care for patients who become PCR-negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still not known.
Patients who have recovered from coronavirus disease 2019 (COVID-19) could profoundly impact the health care system if a subset were to be PCR-positive again with reactivated SARS-CoV-2.
OBJECTIVE To characterize a single center COVID-19 cohort with and without recurrence of PCR positivity, and develop an algorithm to identify patients at high risk of retest positivity after discharge to inform health care policy and case management decision-making.
A cohort of 414 patients with confirmed SARS-CoV-2 infection, at The Second Affiliated EXPOSURES Polymerase chain reaction (PCR) and IgM-IgG antibody confirmed SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES Univariable and multivariable statistical analysis of the clinical, laboratory, radiologic image, medical treatment, and clinical course of admission/quarantine/readmission data to develop an algorithm to predict patients at risk of recurrence of PCR positivity.
RESULTS 16.7% (95CI: 13.0%-20.3%) patients retest PCR positive 1 to 3 times after discharge, despite being in strict quarantine. The driving factors in the recurrence prediction model included: age, BMI; lowest levels of the blood laboratory tests . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
during hospitalization for cholinesterase, fibrinogen, albumin, prealbumin, calcium, eGFR, creatinine; highest levels of the blood laboratory tests during hospitalization for total bilirubin, lactate dehydrogenase, alkaline phosphatase; the first test results during hospitalization for partial pressure of oxygen, white blood cell and lymphocyte counts, blood procalcitonin; and the first test episodic Ct value and the lowest Ct value of the nasopharyngeal swab RT PCR results. Area under the ROC curve is 0.786.
Given the sudden emergence and rapid community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) being observed worldwide, a strategy of social distancing and shelter in place has been widely adopted in an effort to curb the spread of COVID-19 across space and time 1, 2 . The quarantining of patients testing positive for SARS-CoV-2 virus is considered mandatory in order to prevent continued viral spread (contagion). In last 6 months, many of COVID-19 patients have since clinically recovered and been discharged from the hospital, but it remains unclear the degree to which patients with COVID-19 (clinical symptoms and PCR test positivity) remain contagious and or at risk for disease relapse. The rising concern is that COVID-19 discharged patients may be at risk of viral reactivation to infect others as asymptomatic carriers, or be re-infected themselves. In an attempt to better understand these concerns, varying quarantine strategies have been implemented during the transition of COVID-19 recovering patients from healthcare to non-healthcare settings in this current pandemic.
Recently, the early experiences of 116 cases confirmed by nasopharyngeal swab testing, potentially resulting from either "reactivated" or "re-infected" SARS-CoV-2, was reported in South Korea 3, 4 . In response, the World Health Organization (WHO) commented that there is currently "no evidence" demonstrating that people who have recovered from the coronavirus are not at risk of re-infection 5 .
However, limited information is available regarding viral shedding kinetics and live virus isolation. Variability in PCR methodology will result in different thresholds . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
The copyright holder for this preprint this version posted May 10, 2020. . https://doi.org/10.1101/2020.05.06.20089573 doi: medRxiv preprint of the assay for RNA detection, but in one study the SARS-CoV-2 RNA threshold upon PCR testing needs to be greater than 10 6 copies per sample 6 In order to assist with pandemic management, a better u |
| PDF JSON Files:
|
document_parses/pdf_json/3074b51f9b6134655dffc154c8b99442047337d7.json |
| G_ID:
|
recurrence_of_sars_cov_2_pcr_positivity_in_covid_19_patients_a_single_center_experience |
| S2 ID:
|
218561632 |
