ABSTRACT
IMPORTANCEHow 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. OBJECTIVETo 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 PARTICIPANTSA 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. EXPOSURESPolymerase chain reaction (PCR) and IgM-IgG antibody confirmed SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURESUnivariable 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. RESULTS16.7% (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 RELEVANCEThis 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. Key PointsO_ST_ABSQuestionC_ST_ABSWhat 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? FindingsIn 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. MeaningRate and timing of the recurrence of PCR positivity following strict quarantine were characterized. Our prediction algorithm may have implications for COVID-19 clinical treatment, patient management, and health policy.
ABSTRACT
Objective To investigate the distribution and susceptibility patterns of common uropathogens causing community-acquired urinary tract infection (UTI) in Beijing.MethodsA total of 300non-duplicate isolates were randomly collected from 3 hospitals in Beijing between Jan,1 2010 and Mar,312011.Minimal inhibitory concentrations (MICs) were determined by the broth microdilution methods,which were performed and interpreted according to the guidelines established by the Clinical and Laboratory Standards Institute (CLSI).A panel of 8 antimicrobial agents were tested:amikacin,cefaclor,cefepime,cefoperazone/sulbactam,ciprofloxacin,levofloxacin,gentamicin and nitrofurantoin. Fosfomycin trometamol MICs were determined by the agar-dilution method in cation-adjusted MH agar supplemented with glucose 6-phosphate at a concentration of 25 mg/L as detailed in the guidelines issued by 2010 CLSI. All the Escherichia coli,Klebsiella pneumoniae and Proteus mirabilis strains were screened and confirmed by double-disk synergy test for extended-spectrum β-lactamase (ESBLs).Results Among the organisms cultured,E.coli wasthepredominantpathogen(65.0％ ), followedby Enterococcus(11.7％ ),Staphylococcus( 6.3％ ), Klebsiella pneumoniae( 5. 3％ ), Proteus mirabilis( 4. 7％ ), and Pseudomonas aeruginosa (3.0％).Lower susceptibility rates to ciprofloxacin and levofloxacin (31.4％ -47.4％ ) were observed among all the stains.Amikacin,cefoperazone/sulbactam,nitrofurantoin and fosfomycin trometamol were the most active drugs (92.1％,92.1％,88.4％ and 87.9％ susceptible strains,respectively) among the Gram-negative strains.Isolates of Staphylococcus were highly sensitive to amikacin ( 100.0％ ),cefoperazone/sulbactam (94.7％),nitrofurantoin ( 100.0％ ).Higher susceptibility rates to nitrofurantoin (91.4％) and fosfomycin trometamol (90.0％) were observed in Enterococcus.ESBLs-producing strains accounted for 52.3％ (102/195) in E.coli,43.8％ (7/16) in K.pneumoniae and 14.3％(2/14) in P.mirabilis,respectively.ConclusionsResistance is most common to ciprofloxacin and levofloxacin of all the stains.Currently,the most appropriate agents for the empirical management of uncomplicated UTI seems to be amikacin,cefoperazone/sulbactam,nitrofurantoin and fosfomycin trometamol.
