Risk of chronic arthralgia and impact of pain on daily activities in a cohort of patients with chikungunya virus infection from Brazil

Objectives: To investigate risk factors for persistent arthralgia in patients with chikungunya, and describe its impact on daily activities. Methods: From September 2014 to July 2016, a surveillance study enrolled patients with acute febrile illness in Salvador, Brazil, and detected those with chikungunya virus infection using IgM enzyme-linked immunosorbent assay or reverse transcriptase polymerase chain reaction. Telephone follow-ups were performed to ascertain the progression of disease. Results: Of 153 followed cases, 65 (42.5%) reported chronic arthralgia that lasted >3 months, and 47 (30.7%) were still symptomatic at the time of the interview (approximately 1.5 years after symptom onset). Limitations in daily activities and mental distress were reported by 93.8% and 61.5% of those with chronic arthralgia, respectively. Female sex [risk ratio (RR) 1.79, 95% confidence interval (CI) 1.95–2.69] and age (RR 1.02 for each 1-year increase, 95% CI 1.01–1.03) were independent risk factors for chronic arthralgia. Chronic arthralgia was not associated with co-infection with dengue virus (RR 0.97, 95% CI 0.48–1.94) or chikungunya viral load at diagnosis (median chikungunya virus RNA of 5.60 and 5.52 log10 copies/μL for those with and without chronic arthralgia, respectively; P = 0.75). Conclusions: These findings reinforce the high frequency of chronic chikungunya arthralgia, and highlight the substantial disability associated with the persistence of pain. Development of novel strategies to mitigate the transmission of chikungunya virus and to provide long-term medical assistance for patients with chikungunya are needed urgently.Fil: Silva, Monaíse M. O.. Fundación Oswaldo Cruz; BrasilFil: Kikuti, Mariana. Universidade Federal da Bahia; Brasil. Fundación Oswaldo Cruz; BrasilFil: Anjos, Rosângela O.. Fundación Oswaldo Cruz; BrasilFil: Portilho, Moyra M.. Fundación Oswaldo Cruz; BrasilFil: Santos, Viviane C.. Fundación Oswaldo Cruz; BrasilFil: Gonçalves, Thaiza S.F.. Fundación Oswaldo Cruz; BrasilFil: Tauro, Laura Beatriz. Fundación Oswaldo Cruz; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Moreira, Patrícia S. S.. Fundación Oswaldo Cruz; BrasilFil: Jacob Nascimento, Leile C.. Fundación Oswaldo Cruz; BrasilFil: Santana, Perla M.. Fundación Oswaldo Cruz; BrasilFil: Campos, Gúbio S.. Universidade Federal da Bahia; BrasilFil: Siqueira, André M.. Fundación Oswaldo Cruz; BrasilFil: Kitron, Uriel D.. University of Emory; Estados Unidos. Fundación Oswaldo Cruz; BrasilFil: Reis, Mitermayer G.. University of Yale; Estados Unidos. Fundación Oswaldo Cruz; Brasil. Universidade Federal da Bahia; BrasilFil: Ribeiro, Guilherme S.. Fundación Oswaldo Cruz; Brasil. Universidade Federal da Bahia; Brasi

Accuracy of Dengue Reporting by National Surveillance System, Brazil

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2016-07-29T18:22:11Z No. of bitstreams: 1 Silva MMO Accuracy of dengue....pdf: 393651 bytes, checksum: 6b53defcc715e5938aa761a3e93608bd (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2016-07-29T18:43:43Z (GMT) No. of bitstreams: 1 Silva MMO Accuracy of dengue....pdf: 393651 bytes, checksum: 6b53defcc715e5938aa761a3e93608bd (MD5)Made available in DSpace on 2016-07-29T18:43:43Z (GMT). No. of bitstreams: 1 Silva MMO Accuracy of dengue....pdf: 393651 bytes, checksum: 6b53defcc715e5938aa761a3e93608bd (MD5) Previous issue date: 2016-02National Council for Scientific and Technological DevelopmentFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Universidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Universidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Universidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Universidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilUniversidade Federal do Rio Grande do Norte. Natal, RGN, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Yale University School of Public Health. New Haven, Connecticut, USAFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Yale University School of Public Health. New Haven, Connecticut, USA / Universidade Federal da Bahia. Faculdade de Medicina. Salvador, BA, BrasilFundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil / Universidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil / Yale University School of Public Health. New Haven, Connecticut, USADengue is an underreported disease globally. In 2010, the World Health Organization recorded 2.2 million dengue cases (1), but models projected that the number of symptomatic dengue cases might have been as high as 96 million (2). Brazil reports more cases of dengue than any other country (1); however, the degree of dengue underreporting in Brazil is unknown. We conducted a study to evaluate dengue underreporting by Brazil’s Notifiable Diseases Information System (Sistema de Informação de Agravos de Notificação [SINAN])

Accuracy of the SD BIOLINE Dengue Duo for rapid point-of-care diagnosis of dengue.

BACKGROUND:Rapid diagnosis tests (RDTs) are easy to carry out, provide fast results, and could potentially guide medical treatment decisions. We investigated the performance of a commercially available RDT, which simultaneously detects the non-structural 1 (NS1) dengue virus (DENV) antigen, and IgM and IgG DENV antibodies, using representative serum samples from individuals in a dengue endemic area in Salvador, Brazil. METHODOLOGY/PRINCIPAL FINDINGS:We evaluated the accuracy of the SD BIOLINE Dengue Duo RDT (Abbott, Santa Clara, USA; former Alere Inc, Waltham, USA) in a random collection of sera. Samples included acute-phase sera from 246 laboratory-confirmed dengue cases and 108 non-dengue febrile patients enrolled in a surveillance study for dengue detection, 73 healthy controls living in the same surveillance community, and 73 blood donors. RDT accuracy was blindly assessed based on the combined results for the NS1 and the IgM test components. The RDT sensitivity was 46.8% (38.6% for the NS1 component and 13.8% for the IgM component). Sensitivity was greater for samples obtained from patients with secondary DENV infections (49.8%) compared to primary infections (31.1%) (P: 0.02) and was also influenced by the result in the confirmatory dengue diagnostic test, ranging from 39.7% for samples of cases confirmed by IgM-ELISA seroconversion between paired samples to 90.4% for samples of cases confirmed by a positive NS1-ELISA. The RDT specificity was 94.4% for non-dengue febrile patients, 87.7% for the community healthy controls, and 95.9% for the blood donors. CONCLUSIONS/SIGNIFICANCE:The SD BIOLINE Dengue Duo RDT showed good specificities, but low sensitivity, suggesting that it may be more useful to rule in than to rule out a dengue diagnosis in dengue endemic regions

Respect.

<p>The keywords were identified using the Atlas.ti 6.0 software. The words were sorted according to the frequency of their appearance in the interviews. The cut-off point, which divides the set of words into high-frequency and low-frequency groups, was identified. The graphs explaining the frequency of appearance were created with MS Excel 2007.</p

Today´s medical self and the other: Challenges and evolving solutions for enhanced humanization and quality of care

<div><p>Background</p><p>Recent scientific developments, along with growing awareness of cultural and social diversity, have led to a continuously growing range of available treatment options; however, such developments occasionally lead to an undesirable imbalance between science, technology and humanism in clinical practice. This study explores the understanding and practice of values and value clusters in real-life clinical settings, as well as their role in the humanization of medicine and its institutions. The research focuses on the values of clinical practice as a means of finding ways to enhance the pairing of Evidence-Based Medicine (EBM) with Values-based Medicine (VBM) in daily practice.</p><p>Methods and findings</p><p>The views and representations of clinical practice in 15 pre-CME and 15 post-CME interviews were obtained from a random sampling of active healthcare professionals. These views were then identified and qualitatively analyzed using a three-step hermeneutical approach.</p><p>A <i>clinical values space</i> was identified in which ethical and epistemic values emerge, grow and develop within the biomedical, ethical, and socio-economic dimensions of everyday health care. Three main values—as well as the dynamic clusters and networks that they tend to form—were recognized: healthcare personnel-patient relationships, empathy, and respect. An examination of the interviews suggested that an adequate conceptualization of values leads to the formation of a wider axiological system. The role of <i>clinician-as-consociate</i> emerged as an ideal for achieving medical excellence.</p><p>Conclusions</p><p>By showing the intricate clusters and networks into which values are interwoven, our analysis suggests methods for fine-tuning educational interventions so they can lead to demonstrable changes in attitudes and practices.</p></div

Unrecognized Emergence of Chikungunya Virus during a Zika Virus Outbreak in Salvador, Brazil

<div><p>Background</p><p>Chikungunya virus (CHIKV) entered Brazil in 2014, causing a large outbreak in Feira de Santana, state of Bahia. Although cases have been recorded in Salvador, the capital of Bahia, located ~100 km of Feira de Santana, CHIKV transmission has not been perceived to occur epidemically, largely contrasting with the Zika virus (ZIKV) outbreak and ensuing complications reaching the city in 2015.</p><p>Methodology/Principal Findings</p><p>This study aimed to determine the intensity of CHIKV transmission in Salvador between November 2014 and April 2016. Results of all the CHIKV laboratory tests performed in the public sector were obtained and the frequency of positivity was analyzed by epidemiological week. Of the 2,736 tests analyzed, 456 (16.7%) were positive. An increasing in the positivity rate was observed, starting in January/2015, and peaking at 68% in August, shortly after the exanthematous illness outbreak attributed to ZIKV.</p><p>Conclusions/Significance</p><p>Public health authorities and health professionals did not immediately detect the increase in CHIKV cases, likely because all the attention was directed to the ZIKV outbreak and ensuing complications. It is important that regions in the world that harbor arbovirus vectors and did not experience intense ZIKV and CHIKV transmission be prepared for the potential co-emergence of these two viruses.</p></div

Empathy value networks before CME training.

<p><b>A.</b> The keywords were identified using the Atlas.ti 6.0 software. The words were sorted according to the frequency of their appearance in the interviews. <b>B. Empathy value networks after CME training.</b> The keywords were identified using the Atlas.ti 6.0 software. The words were sorted according to the frequency of their appearance in the interviews</p

Consociate clinician-patient relationship as cement for the EBM and VBM binomial.

<p>Quotations from interviews illustrating its key aspects.</p

Healthcare personnel-patient relationship value networks before CME training.

<p><b>A.</b> Keywords were identified using the Atlas.ti 6.0 software. The words were sorted according to the frequency of their appearance in the interviews. <b>B. Healthcare personnel-patient relationship value networks after CME training</b>. Keywords were identified using the Atlas.ti 6.0 software. The words were sorted according to the frequency of their appearance in the interviews.</p

Value semantic networks.

<p>Keywords were identified using the Atlas.ti 6.0 software. The words were sorted according to the frequency of their appearance in the interviews. The cut-off point, which divides the set of words into high-frequency and low-frequency groups, was identified. Radial graphs explaining the frequency of appearance were created with MS Excel 2007. The upper left-hand side (I) shows the most relevant values that are consistently mentioned and discussed by the participants prior to the CME intervention on clinical ethics. The lower right-hand side (II) shows the most relevant values that are consistently mentioned and discussed by the participants following the CME intervention on clinical ethics.</p