National Health Care Network for children with oral clefts: organization, functioning, and preliminary outcomes

Introduction. Oral clefts are major congenital anomalies that may affect the lip and/or palate, and that may also involve the nose and nostrils. In Argentina, their prevalence is approximately 15 per 10 000 births. In 2015, the Ministry of Health of Argentina created a national health care network for children with oral clefts in Argentina through the joint work with the National Registry of Congenital Anomalies (Red Nacional de Anomaliás Congénitas, RENAC) (coordinating center for the national network) and the SUMAR Program. The objective of this study was to describe the health care network and its preliminary outcomes. Population and methods. A total of 61 centers that provided a comprehensive treatment for oral clefts or in collaboration with other centers were identified and accredited. Maternity centers were connected with treating centers grouped in health care network nodes. Results. In the period between March 2015 and February 2016, 550 newborn infants who were exclusively covered by the public health care system were identified. Among these, 18% had a cleft lip; 62%, cleft lip and palate; and 20%, cleft palate only; 75% were isolated cases and 25%, in association with other congenital anomalies. Conclusion. Approximately 70% of children were assessed by a certified treating institution and are receiving treatment. The network seeks to improve data systematization, include the largest number of centers possible, strengthen interdisciplinary team work, and promote highquality standards for treatments.Fil: Cassinelli, Agustina. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán". Centro Nacional de Genética Médica; ArgentinaFil: Pauselli, Nadia. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán". Centro Nacional de Genética Médica; ArgentinaFil: Piola, Agustina. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán". Centro Nacional de Genética Médica; ArgentinaFil: Martinelli, Claudia. Ministerio de Salud de la Nación; ArgentinaFil: Alves De Azevedo, José L.. Ministerio de Salud de la Nación; ArgentinaFil: Bidondo, Mariá P.. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán". Centro Nacional de Genética Médica; ArgentinaFil: Groisman, Boris. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán". Centro Nacional de Genética Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Barbero, Pablo Miguel. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán". Centro Nacional de Genética Médica; ArgentinaFil: Liascovich, Rosa. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán". Centro Nacional de Genética Médica; ArgentinaFil: Sala, Ana. Ministerio de Salud de la Nación; Argentin

Immunogenicity and Reactogenicity of 2009 Influenza A (H1N1) Inactivated Monovalent Non-Adjuvanted Vaccine in Elderly and Immunocompromised Patients

Background\ud \ud Immunosuppressed individuals present serious morbidity and mortality from influenza, therefore it is important to understand the safety and immunogenicity of influenza vaccination among them.\ud Methods\ud \ud This multicenter cohort study evaluated the immunogenicity and reactogenicity of an inactivated, monovalent, non-adjuvanted pandemic (H1N1) 2009 vaccine among the elderly, HIV-infected, rheumatoid arthritis (RA), cancer, kidney transplant, and juvenile idiopathic arthritis (JIA) patients. Participants were included during routine clinical visits, and vaccinated according to conventional influenza vaccination schedules. Antibody response was measured by the hemagglutination-inhibition assay, before and 21 days after vaccination.\ud Results\ud \ud 319 patients with cancer, 260 with RA, 256 HIV-infected, 149 elderly individuals, 85 kidney transplant recipients, and 83 with JIA were included.\ud \ud The proportions of seroprotection, seroconversion, and the geometric mean titer ratios postvaccination were, respectively: 37.6%, 31.8%, and 3.2 among kidney transplant recipients, 61.5%, 53.1%, and 7.5 among RA patients, 63.1%, 55.7%, and 5.7 among the elderly, 59.0%, 54.7%, and 5.9 among HIV-infected patients, 52.4%, 49.2%, and 5.3 among cancer patients, 85.5%, 78.3%, and 16.5 among JIA patients. The vaccine was well tolerated, with no reported severe adverse events.\ud Conclusions\ud \ud The vaccine was safe among all groups, with an acceptable immunogenicity among the elderly and JIA patients, however new vaccination strategies should be explored to improve the immune response of immunocompromised adult patients. (ClinicalTrials.gov, NCT01218685)Fundação Butantan funded the study, and employed several of the authors. The funder had a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Prognostic value of exercise echocardiography in diabetic patients

Background Coronary artery disease (CAD) is the leading cause of death in diabetic patients. Although exercise echocardiography (EE) is established as a useful method for diagnosis and stratification of risk for CAD in the general population, there are few studies on its value as a prognostic tool in diabetic patients. The purpose of this investigation was to evaluate the value of EE in predicting cardiac events in diabetics. Methods 193 diabetic patients, 97 males, 59.8 ± 9.3 yrs (mean ± SD) were submitted to EE between 2001 and 2006 and followed from 7 to 65 months with median of 29 months by phone calls and personal interviews with patients and their primary physician, and reviewing medical records and death certificates. The end points were cardiac events, defined as non-fatal myocardial infarction, late myocardial revascularization and cardiac death. Sudden death without another explanation was considered cardiac death. Survival free of end points was estimated by the Kaplan-Meier method. Results Twenty-six cardiac events were registered in 24 individuals during the follow-up. The rates of cardiac events were 20.6 and 7% in patients with positive and negative EE, respectively (p < 0.001). Predictors of cardiac events included sedentary lifestyle, with RR of 2.57 95%CI [1.09 to 6.02] (P = 0.03) and positive EE, with RR 3.63, 95%CI [1.44 to 9.16] (P = 0.01). Patients with positive EE presented higher rates of cardiac events at 12 months (6.8% vs. 2.2%), p = 0.004. Conclusion EE is a useful method to predict cardiac events in diabetic patients with suspected or known CAD

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio