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Aims and Objectives: To compare and evaluate interobserver (nurses and physicians) agreement for dengue clinical signs and symptoms, including the World Health Organization diagnostic algorithm., Background: Agreement of clinical history defines the capacity of the examiner to measure a given clinical parameter in a reproducible and consistent manner, which is prerequisite for diagnosis validity. Nurses play a major role in the triage and care of dengue patients in many countries., Study Design: This is a sub-study on interobserver agreement performed as part of a cross-sectional diagnostic accuracy study for acute febrile illness (AFI) using the checklist STARD., Methods: A previously validated semi-structured sign and symptom standardised questionnaire for AFI was independently administered to 374 patients by physician and nurse pairs. The interobserver agreement was estimated using kappa statistics., Results: For a set of 27 signs and symptoms, we found six interobserver discrepancies (examiner detected red eyes, lethargy, exanthema, dyspnoea, bleeding and myalgia) as identified by regular and moderate kappa indexes. Four signs (patient observed red eyes, cough, diarrhoea and vomiting) and one symptom (earache) had near-perfect agreement. Most signs and symptoms showed substantial agreement. The WHO (Dengue guidelines for diagnosis, treatment, prevention and control: new edition, World Health Organization, 2009) clinical criteria for dengue comprise a group of symptoms known as "pains and aches." Interobserver agreement for abdominal pain, retro-orbital pain and arthralgia exceed that found for headache and myalgia., Conclusions: During a dengue outbreak, the interobserver agreement for most of the signs and symptoms used to assess AFI was substantial., Relevance to Clinical Practice: This result suggests good potential applicability of the tool by health professionals following training. A well-trained health professional is qualified to apply the standardised questionnaire to evaluate suspected dengue cases during outbreaks., (© 2020 John Wiley & Sons Ltd.)

Background: Although performance of rapid immunochromatographic tests (RITs) for dengue virus (DENV) serotypes 1, 2 and 3 is relatively settled, evidence on accuracy of RITs for DENV-4 are based on studies with small sample sizes and with discrepant results., Objectives: To assess accuracy and inter-observer agreement of RITs targeting dengue nonstructural protein-1 (NS1) antigen - Dengue NS1-Bioeasy™, Dengue NS1 Ag Strip-Bio-Rad™, IVB Dengue Ag NS1-Orangelife™ and Dengue NS1-K130-Bioclin™ in DENV-4 samples., Methods: Study sample (n = 324) included adults presenting at an emergency unit in Rio de Janeiro, Brazil, with fever of ≤72 h and two or more dengue symptoms. A serum sample from each patient was tested by each RIT. A positive reverse-transcription polymerase chain reaction was considered as the reference standard for dengue diagnosis. The diagnostic parameters analyzed for each RIT were sensitivity, specificity, positive and negative predictive values, and likelihood ratios. Each RIT was read by homogeneous (two junior nurses) or heterogeneous (one junior nurse and one senior biologist) pairs. Agreement was estimated by simple kappa with 95% confidence interval, positive (Ppos) and negative (Pneg) proportion concordance and prevalence and bias adjusted kappa, rated from poor (k < 0.0) to almost perfect (0.8 < k < 1.0), and perfect (k = 1)., Results: NS1 RITs for DENV-4 diagnosis showed high specificity (95.9%-99.4%), but low sensitivity (14.7%-45.4%). Bioeasy™ had the best performance, with a positive likelihood ratio of 26.0 (95% CI: 8.4;81.0). Inter-observer agreement was almost perfect for all evaluated RITs. Mismatches in confirmed dengue were more common for the Bioclin™ (Ppos 88.3-90.0 %) and Orangelife™ (Ppos 91.7-94.1 %) tests., Conclusions: For DENV-4, the tested RITs had high specificity, but lower sensitivity compared to published results for other serotypes. They should not be used for screening purposes. Different brands may have very different performances. This should be considered upon deciding of using RITs in DENV-4 outbreaks., (Copyright © 2020 Sociedade Brasileira de Infectologia. Published by Elsevier España, S.L.U. All rights reserved.)

Introduction: Multi-drug-resistant bacteria surveillance (MDR) systems are used to identify the epidemiology of MDR bacteria in neonates and children. This study aimed to describe the patterns by which MDR bacteria colonize and infect neonatal (NICU) and pediatric intensive care unit (PICU) patients in the state of Rio de Janeiro State, Brazil., Methods: A cross-sectional survey was performed using electronic data on NICU and PICU patients reported to the Rio de Janeiro State MDR bacteria surveillance system. All healthcare institutions that reported at least one case during the study period were included., Results: Between 2014 and 2017, 10,210 MDR bacteria cases, including 9261 colonizations and 949 infections, were reported. Among the colonizations, 5379 occurred in NICUs and 3882 in PICUs, while 405 infections occurred in NICUs and 544 in PICUs. ESBL producing Klebsiella sp and E. coli were the most reported colonization-causing agents in NICUs (1983/5379, 36.9%) and PICUs (1494/3882; 38.5%). The main causing bacteria reported in catheter-associated bloodstream infection (CLABSI), ventilator associated pneumonia, and catheter-associated urinary tract infection in NICUs were Klebsiella sp and E.coli (56/156, 35.9%), carbapenem-resistant Gram-negative bacteria (CRGNB) (22/65, 33.9%), and CRGNB (11/36, 30.6%) respectively, while in PICUs, they were MRSA (53/169, 31.4%), CRGNB (50/87, 57.4%), Klebsiella sp and E.coli (18/52, 34.6%), respectively., Conclusions: MDR Gram-negative bacteria (ESBL producers and carbapenem-resistant bacteria) were the most reported agents among MDR bacteria reported to Rio de Janeiro surveillance system. Except for CLABSI in children, they caused all device-associated infections in NICUs and PICUs.

We tested 210 dengue virus‒negative samples collected from febrile patients during a dengue virus type 4 outbreak in Rio de Janeiro in April 2013 and found 3 samples positive for Zika virus. Our findings support previously published entomological data suggesting Zika virus was introduced into Brazil during October 2012-May 2013.

We characterized NDM-1-producing Klebsiella isolates from Rio de Janeiro, Brazil. PCR was applied for resistance and virulence determinants. The genetic context of bla NDM was determined by S1 nuclease pulsed-field gel electrophoresis (PFGE) and hybridization. Genotyping was performed by PFGE and multilocus sequence typing (MLST). Most isolates carried multiple resistance genes and remained susceptible to amikacin, fosfomycin-trometamol, polymyxin B, and tigecycline. The spread of NDM-1-producing Klebsiella pneumoniae was not associated with clonal expansion and appears to be associated with Tn 3000 ., (Copyright © 2017 American Society for Microbiology.)

Background: Dengue is an acute febrile illness considered the major arboviral disease in terms of morbidity, mortality, economic impact and dissemination worldwide. Brazil accounts for the highest notification rate, with circulation of all four dengue serotypes. The NS1 antigen is a dengue highly conserved specific soluble glycoprotein essential for viral replication and viability that can be detected 0 to 18 days from the onset of fever (peak first 3 days). It induces a strong humoral response and is known as a complement-fixing antigen. Lower NS1 test sensitivity occurs in secondary dengue infections probably due to immune complex formation impairing antigen detection by ELISA., Methods: We compared the sensitivity of NS1 ELISA in heat dissociated and non-dissociated samples from 156 RT-PCR confirmed acute dengue-4 cases from 362 prospectively enrolled patients., Results: Secondary infections accounted for 83.3% of cases. NS1 ELISA was positive in 42.5% and indeterminate in 10.2% of dengue-4 cases. After heat dissociation, 7 negative and 16 indeterminate samples turned positive, increasing the overall test sensitivity to 57.7%., Conclusions: Although it is time consuming and requires the use of specific laboratory equipment, NS1 ELISA combined with heat dissociation could be a slightly better alternative for triage in suspected dengue cases.

Background: Early diagnosis of dengue infection is important for decision-making and timely implementation of therapeutic measures. Although rapid NS1 assays have been used for dengue diagnosis since 2008, their performance in DENV-4 cases has not yet been fully assessed., Methods: We evaluated the accuracy of NS1 Bioeasy™ immunochromatographic strip test and of three clinical criteria for dengue diagnosis. Patients presenting at an emergency care center within 72 h of an acute febrile illness during the 2013 DENV-4 epidemic in Rio de Janeiro were consecutively enrolled for clinical and laboratory evaluation. We classified patients as suspected dengue or not according to three clinical criteria: WHO 2009, WHO 1997, and INI-FIOCRUZ. Dengue diagnosis was defined by RNA detection using RT-PCR and the negative cases were negative for all dengue serotypes and also Platelia™ NS1 ELISA. We obtained accuracy indices for NS1 Bioeasy™ alone and in combination with the clinical criteria., Results: RT-PCR for DENV-4 was positive in 148 out of 325 patients. Positive likelihood ratio, sensitivity, and specificity of NS1 Bioeasy™ with WHO 2009, WHO 1997, and INI-FIOCRUZ criteria were 22.6 (95% CI 7.2-70.6), 40.6% (95% CI 32.3-49.3), and 98.2% (95% CI 94.9-99.6); 18.3 (95% CI 6.8-49.2), 44.2 (95% CI 35.8-52.9), 97.6 (95% CI 94.0-99.3); 26.2 (95% CI 6.5-106.5), 29.7 (95% CI 22.4-37.8), 98.9 (95% CI 96.0-99.9), respectively. WHO 1997 clinical criteria presented high sensitivity to rule out disease, but extremely low specificity. INI-FIOCRUZ had moderate sensitivity and specificity, and could target a group to a more specific test., Conclusions: Although the large rates of false negative results using NS1 Bioeasy™ rapid test advise against its use for triaging (rule out) purposes in DENV-4 epidemics, it could be used as a confirmatory tool in a bedside algorithm.