Project description:BackgroundWith the increased number of patients discharged after having COVID-19, more and more studies have reported cases whose retesting was positive (RP) during the convalescent period, which brings a new public health challenge to the world.MethodsWe searched PubMed, Web of Science, The Cochrane Library, CNKI, WanFang and VIP from December 1, 2019 to December 31, 2020. The included studies were assessed using JBI critical appraisal tools and Newcastle-Ottawa Scale. The RP rate of discharge patients was analyzed by a meta-analysis. We adhered to PRISMA reporting guideline.FindingsWe have included 117 studies with 2669 RP participants after discharge. The methodological quality of 66 case reports were low to high, 42 case series and 3 cohort study were moderate to high, 3 case-control studies were moderate and 3 cross-sectional studies were low to moderate. The clinical manifestations of most RP patients were mild or asymptomatic, and CT imaging and laboratory examinations were usually normal. The existing risk factors suggest that more attention should be paid to sever patients, elderly patients, and patients with co-morbidities. The summary RP rate was 12·2% (95% CI 10·6-13·7) with high heterogeneity (I2 = 85%).InterpretationTo date, the causes and risk factors of RP result in discharged patients are not fully understood. High-quality etiological and clinical studies are needed to investigate these issues to further help us to make strategies to control and prevent its occurrence.
Project description:ObjectiveDuring the follow-up of patients recovered from coronavirus disease 2019 (COVID-19) in the quarantine and observation period, some of the cured patients showed positive results again. The recurrent positive RT-PCR test results drew widespread concern. We observed a certain number of cured COVID-19 patients with positive RT-PCR test results and try to analyze the factors that caused the phenomenon.MethodsWe conducted an observational study in COVID-19 patients discharged from 6 rehabilitation stations in Wuhan, China. All observed subjects met the criteria for hospital discharge and were in quarantine. Data regarding age, sex, body mass index (BMI), course of disease, comorbidity, smoking status and alcohol consumption, symptoms in and out of quarantine, and intervention were collected from the subjects' medical records and descriptively analyzed. The main outcome of this study was the RT-PCR test result of the observed subjects at the end of quarantine (negative or positive). Logistic regression analysis was used to identify the influencing factors related to recurrent positive RT-PCR test results.ResultsIn this observational study, 420 observed subjects recovered from COVID-19 were included. The median age was 56 years, 63.6% of the subjects were above 50 years old, and 50.7% (213/420) were female. The most common comorbidities were hypertension [26.4% (111/420)], hyperlipidemia [10.7% (45/420)], and diabetes [10.5% (44/420)]. 54.8% (230/420) manifested one or more symptoms at the beginning of the observation period, the most common symptoms were cough [27.6% (116/420)], shortness of breath 23.8% (100/420)], and fatigue [16.2% (68/420)], with fever rare [2.6% (11/420)]. A total of 325 subjects were exposed to comprehensive intervention; 95 subjects were absence of intervention. The recurrence rate of positive RT-PCR test results with comprehensive intervention was 2.8% (9/325), and that with no intervention was 15.8% (15/95). The results of logistic regression analysis showed that after adjusted for factors such as age, sex, and comorbidity and found out that comprehensive intervention was correlated with the recurrent positive RT-PCR test results. There was appreciably less recurrence in the comprehensive intervention group.ConclusionsThe factors related to positive RT-PCR test results in observed subjects recovered from COVID-19 were age, comorbidity, and comprehensive intervention, among which comprehensive intervention might be a protective factor.Clinical trial registrationChictr.org.cn, identifier ChiCTR2000030747.
Project description:BackgroundOur hospital is a designated institution for COVID-19 patients in Chengdu, China. This study aimed to analyze the clinical and chest CT features of 15 COVID-19 patients with positive reverse transcription-polymerase chain reaction (RT-PCR) retest results after discharge. Patients who met the current standards of discharge could still carry the SARS-CoV-2 virus.MethodsClinical manifestations, laboratory data, and chest CT images were retrospectively reviewed and analyzed.ResultsThe most common symptoms at Covid-19COVID-19 initial onset were fever (12/15, 80%) and cough (11/15, 73.3%). Most of the patients had a normal white blood cells (12/15, 80%), neutrophils (12/15, 80%), and lymphocytes count (13/15, 86.7%); some patients had increased C-reactive protein (CRP) (5/15, 33.3%), and increased lactate dehydrogenase (LDH) (4/15, 26.7%) during first admission. Five patients (33.3%) had a cough before their first discharge. The average interval from the first discharge to re-admission was 17 days (range, 9–30 days). At re-admission, two (13.3%) patients presented with cough, and one (6.6%) had chest pain with anxiety. At re-admission, all patients had normal clinical results except five (33.3%) patients had increased CRP compared with first discharging, two (13.3%) patients had increased neutrophils count, and one (6.6%) had increased CRP. The majority of patients had normal procalcitonin. Ground glass opacities (GGOs) and reticulation in the peripheral and subpleural areas were the most common CT manifestations, and six patients (40%) showed a transformation from reticulation to GGOs when re-admitted.ConclusionsThere may be no specific clinical characteristics to predict the re-detectability of the virus. A regular medical observation and a bi-monthly follow-up is recommended.
Project description:BackgroundCOVID-19 is an infectious disease of variable severity caused by a new coronavirus. Clinical presentation ranges from asymptomatic cases to severe illness. Most cases in newborns appear to be asymptomatic or mild.ObjectiveTo conduct a systematic review of the literature on published studies of COVID-19 in newborns with a positive RT-PCR test.MethodsThe PubMed and EMBASE databases were searched for infection data in newborns from 1 December 2019-21 May 2021. The mesh terms included "SARS-CoV-2", "COVID-19", "novel coronavirus", "newborns" and "neonates". The selection criteria were as follows: original studies reporting clinical, radiological, laboratory, and outcome data in newborns with a positive RT-PCR test for SARS-CoV-2. Two independent investigators reviewed the studies.ResultsSeventy-two studies that involved 236 newborns were included. The main clinical manifestations were fever (43.2%), respiratory (46.6%), and gastrointestinal (35.2%) symptoms; 60.1% had mild/moderate disease. A total of 52.5% had a chest X-ray; 43.5% were normal, and 24.1% reported consolidation/infiltration images. The most frequent laboratory abnormalities were elevated C reactive protein and elevated procalcitonin and lymphopenia. Mortality was 1.7%.ConclusionSymptoms of SARS-CoV-2 infection were mild to moderate in most of the newborns. The prognosis was good, and mortality was mainly associated with other comorbidities.
Project description:BackgroundThe emergency of new COVID-19 variants over the past three years posed a serious challenge to the public health. Cities in China implemented mass daily RT-PCR tests by pooling strategies. However, a random delay exists between an infection and its first positive RT-PCR test. It is valuable for disease control to know the delay pattern and daily infection incidences reconstructed from RT-PCR test observations.MethodsWe formulated the convolution model between daily incidences and positive RT-PCR test counts as a linear inverse problem with positivity restrictions. Consequently, the Richard-Lucy deconvolution algorithm was used to reconstruct COVID-19 incidences from daily PCR tests. A real-time deconvolution was further developed based on the same mathematical principle. The method was applied to an Omicron epidemic data set of a bar outbreak in Beijing and another in Wuxi in June 2022. We estimated the delay function by maximizing likelihood via an E-M algorithm.ResultsThe delay function of the bar-outbreak in 2022 differs from that reported in 2020. Its mode was shortened to 4 days by one day. A 95% confidence interval of the mean delay is [4.43,5.55] as evaluated by bootstrap. In addition, the deconvolved infection incidences successfully detected two associated infection events after the bar was closed. The application of the real-time deconvolution to the Wuxi data identified all explosive incidence increases. The results revealed the progression of the two COVID-19 outbreaks and provided new insights for prevention and control strategies, especially for the role of mass daily RT-PCR testing.ConclusionsThe proposed deconvolution method is generally applicable to other infectious diseases if the delay model can be assumed to be approximately valid. To ensure a fair reconstruction of daily infection incidences, the delay function should be estimated in a similar context in terms of virus variant and test protocol. Both the delay estimate from the E-M algorithm and the incidences resulted from deconvolution are valuable for epidemic prevention and control. The real-time feedback is particularly useful during the epidemic's acute phase because it can help the local disease control authorities modify the control measures more promptly and precisely.