Inequality as a Powerful Predictor of Infant and Maternal Mortality around the World

Background Maternal and infant mortality are highly devastating, yet, in many cases, preventable events for a community. The human development of a country is a strong predictor of maternal and infant mortality, reflecting the importance of socioeconomic factors in determinants of health. Previous research has shown that the Human Development Index (HDI) predicts infant mortality rate (IMR) and the maternal mortality ratio (MMR). Inequality has also been shown to be associated with worse health in certain populations. The main purpose of the present study was to determine the correlation and predictive power of the Inequality Adjusted Human Development Index (IHDI) as a measure of inequality with the Infant Mortality Rate (IMR), Maternal Mortality Rate (MMR), Early Neonatal Mortality Rate (ENMR), Late Neonatal Mortality Rate (LNMR), and the Post Neonatal Mortality Rate (PNMR). Methods and Findings Data for the present study were downloaded from two sources: infant and maternal mortality data were downloaded from the Global Burden of Disease 2013 Cause of Death Database and the Human Development Index (HDI) and Inequality-Adjusted Human Development Index (IHDI) data were downloaded from the United Nations Development Program (UNDP). Pearson correlation coefficients were estimated, following logarithmic transformations to the data, to examine the relationship between HDI and IHDI with MMR, IMR, ENMR, LNMR, and PNMR. Steiger’s Z test for the equality of two dependent correlations was utilized in order to determine whether the HDI or IHDI was more strongly associated with the outcome variables. Lastly, we constructed OLS regression models in order to determine the predictive power of the HDI and IHDI in terms of the MMR, IMR, ENMR, LNMR, and PNMR. Maternal and infant mortality were both strongly and negatively correlated with both HDI and IHDI; however, Steiger’s Z test for the equality of two dependent correlations revealed that IHDI was more strongly correlated than HDI with MMR (Z = 4.897, p \u3c 0.001), IMR (Z = 2.524, p = 0.012), ENMR (Z = 2.936, p = 0.003), LNMR (Z = 2.272, p = 0.023), and PNMR (Z = 2.277, p = 0.023). Furthermore, side-by-side OLS regression models revealed that, when IHDI was used as the predictor variable instead of HDI, the R2 value was 0.053 higher for MMR, 0.025 higher for IMR, 0.038 higher for ENMR, 0.029 higher for LNMR, and 0.026 higher for PNMR. Conclusions Even when both the HDI and the IHDI correlate with the infant and maternal mortality rates, the IHDI is a better predictor for these two health indicators. Therefore, these results add more evidence that inequality is playing an important role in determining the health status of various populations in the world and more efforts should be put into programs to fight inequality

Benefits and harms of direct oral anticoagulation and low molecular weight heparin for thromboprophylaxis in patients undergoing non-cardiac surgery : systematic review and network meta-analysis of randomised trials

OBJECTIVE To systematically compare the effect of direct oral anticoagulants and low molecular weight heparin for thromboprophylaxis on the benefits and harms to patients undergoing non-cardiac surgery. DESIGN Systematic review and network meta-analysis of randomised controlled trials. DATA SOURCES Medline, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL), up to August 2021. REVIEW METHODS Randomised controlled trials in adults undergoing non-cardiac surgery were selected, comparing low molecular weight heparin (prophylactic (low) or higher dose) with direct oral anticoagulants or with no active treatment. Main outcomes were symptomatic venous thromboembolism, symptomatic pulmonary embolism, and major bleeding. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used for network meta-analyses. Abstracts and full texts were screened independently in duplicate. Data were abstracted on study participants, interventions, and outcomes, and risk of bias was assessed independently in duplicate. Frequentist network meta-analysis with multivariate random effects models provided odds ratios with 95% confidence intervals, and GRADE (grading of recommendations, assessment, development, and evaluation) assessments indicated the certainty of the evidence. RESULTS 68 randomised controlled trials were included (51 orthopaedic, 10 general, four gynaecological, two thoracic, and one urological surgery), involving 45 445 patients. Low dose (odds ratio 0.33, 95% confidence interval 0.16 to 0.67) and high dose (0.19, 0.07 to 0.54) low molecular weight heparin, and direct oral anticoagulants (0.17, 0.07 to 0.41) reduced symptomatic venous thromboembolism compared with no active treatment, with absolute risk differences of 1-100 per 1000 patients, depending on baseline risks (certainty of evidence, moderate to high). None of the active agents reduced symptomatic pulmonary embolism (certainty of evidence, low to moderate). Direct oral anticoagulants and low molecular weight heparin were associated with a 2-3-fold increase in the odds of major bleeding compared with no active treatment (certainty of evidence, moderate to high), with absolute risk differences as high as 50 per 1000 in patients at high risk. Compared with low dose low molecular weight heparin, high dose low molecular weight heparin did not reduce symptomatic venous thromboembolism (0.57, 0.26 to 1.27) but increased major bleeding (1.87, 1.06 to 3.31); direct oral anticoagulants reduced symptomatic venous thromboembolism (0.53, 0.32 to 0.89) and did not increase major bleeding (1.23, 0.89 to 1.69). CONCLUSIONS Direct oral anticoagulants and low molecular weight heparin reduced venous thromboembolism compared with no active treatment but probably increased major bleeding to a similar extent. Direct oral anticoagulants probably prevent symptomatic venous thromboembolism to a greater extent than prophylactic low molecular weight heparin.Peer reviewe

The cytogenetic architecture of the aphid genome

In recent years aphids, with their well-defined polyphenism, have become favoured as model organisms for the study of epigenetic processes. The availability of the pea aphid (Acyrthosiphon pisum) genome sequence has engendered much research aimed at elucidating the mechanisms by which the phenotypic plasticity of aphids is inherited and controlled. Yet so far this research effort has paid little attention to the cytogenetic processes that play a vital part in the organisation, expression and inheritance of the aphid genome. Aphids have holocentric chromosomes, which have very different properties from the chromosomes with localised centromeres that are found in most other organisms. Here we review the diverse forms of aphid chromosome behaviour that occur during sex determination and male and female meiosis, often in response to environmental changes and mediated by endocrine factors. Remarkable differences occur, even between related species, that could have significant effects on the inheritance of all or parts of the genome. In relation to this, we review the particular features of the distribution of heterochromatin, rDNA genes and other repetitive DNA in aphid chromosomes, and discuss the part that these may play in the epigenetic modification of chromatin structure and function

First Latin American clinical practice guidelines for the treatment of systemic lupus erythematosus: Latin American Group for the Study of Lupus (GLADEL, Grupo Latino Americano de Estudio del Lupus)-Pan-American League of Associations of Rheumatology (PANLAR)

Systemic lupus erythematosus (SLE), a complex and heterogeneous autoimmune disease, represents a significant challenge for both diagnosis and treatment. Patients with SLE in Latin America face special problems that should be considered when therapeutic guidelines are developed. The objective of the study is to develop clinical practice guidelines for Latin American patients with lupus. Two independent teams (rheumatologists with experience in lupus management and methodologists) had an initial meeting in Panama City, Panama, in April 2016. They selected a list of questions for the clinical problems most commonly seen in Latin American patients with SLE. These were addressed with the best available evidence and summarised in a standardised format following the Grading of Recommendations Assessment, Development and Evaluation approach. All preliminary findings were discussed in a second face-to-face meeting in Washington, DC, in November 2016. As a result, nine organ/system sections are presented with the main findings; an 'overarching' treatment approach was added. Special emphasis was made on regional implementation issues. Best pharmacologic options were examined for musculoskeletal, mucocutaneous, kidney, cardiac, pulmonary, neuropsychiatric, haematological manifestations and the antiphospholipid syndrome. The roles of main therapeutic options (ie, glucocorticoids, antimalarials, immunosuppressant agents, therapeutic plasma exchange, belimumab, rituximab, abatacept, low-dose aspirin and anticoagulants) were summarised in each section. In all cases, benefits and harms, certainty of the evidence, values and preferences, feasibility, acceptability and equity issues were considered to produce a recommendation with special focus on ethnic and socioeconomic aspects. Guidelines for Latin American patients with lupus have been developed and could be used in similar settings.Fil: Pons Estel, Bernardo A.. Centro Regional de Enfermedades Autoinmunes y Reumáticas; ArgentinaFil: Bonfa, Eloisa. Universidade de Sao Paulo; BrasilFil: Soriano, Enrique R.. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Cardiel, Mario H.. Centro de Investigación Clínica de Morelia; MéxicoFil: Izcovich, Ariel. Hospital Alemán; ArgentinaFil: Popoff, Federico. Hospital Aleman; ArgentinaFil: Criniti, Juan M.. Hospital Alemán; ArgentinaFil: Vásquez, Gloria. Universidad de Antioquia; ColombiaFil: Massardo, Loreto. Universidad San Sebastián; ChileFil: Duarte, Margarita. Hospital de Clínicas; ParaguayFil: Barile Fabris, Leonor A.. Hospital Angeles del Pedregal; MéxicoFil: García, Mercedes A.. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; ArgentinaFil: Amigo, Mary Carmen. Centro Médico Abc; MéxicoFil: Espada, Graciela. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Catoggio, Luis J.. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Sato, Emilia Inoue. Universidade Federal de Sao Paulo; BrasilFil: Levy, Roger A.. Universidade do Estado de Rio do Janeiro; BrasilFil: Acevedo Vásquez, Eduardo M.. Universidad Nacional Mayor de San Marcos; PerúFil: Chacón Díaz, Rosa. Policlínica Méndez Gimón; VenezuelaFil: Galarza Maldonado, Claudio M.. Corporación Médica Monte Sinaí; EcuadorFil: Iglesias Gamarra, Antonio J.. Universidad Nacional de Colombia; ColombiaFil: Molina, José Fernando. Centro Integral de Reumatología; ColombiaFil: Neira, Oscar. Universidad de Chile; ChileFil: Silva, Clóvis A.. Universidade de Sao Paulo; BrasilFil: Vargas Peña, Andrea. Hospital Pasteur Montevideo; UruguayFil: Gómez Puerta, José A.. Hospital Clinic Barcelona; EspañaFil: Scolnik, Marina. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Pons Estel, Guillermo J.. Centro Regional de Enfermedades Autoinmunes y Reumáticas; Argentina. Hospital Provincial de Rosario; ArgentinaFil: Ugolini Lopes, Michelle R.. Universidade de Sao Paulo; BrasilFil: Savio, Verónica. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Drenkard, Cristina. University of Emory; Estados UnidosFil: Alvarellos, Alejandro J.. Hospital Privado Universitario de Córdoba; ArgentinaFil: Ugarte Gil, Manuel F.. Universidad Cientifica del Sur; Perú. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Babini, Alejandra. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Cavalcanti, André. Universidade Federal de Pernambuco; BrasilFil: Cardoso Linhares, Fernanda Athayde. Hospital Pasteur Montevideo; UruguayFil: Haye Salinas, Maria Jezabel. Hospital Privado Universitario de Córdoba; ArgentinaFil: Fuentes Silva, Yurilis J.. Universidad de Oriente - Núcleo Bolívar; VenezuelaFil: Montandon De Oliveira E Silva, Ana Carolina. Universidade Federal de Goiás; BrasilFil: Eraso Garnica, Ruth M.. Universidad de Antioquia; ColombiaFil: Herrera Uribe, Sebastián. Hospital General de Medellin Luz Castro de Gutiérrez; ColombiaFil: Gómez Martín, DIana. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Robaina Sevrini, Ricardo. Universidad de la República; UruguayFil: Quintana, Rosana M.. Hospital Provincial de Rosario; Argentina. Centro Regional de Enfermedades Autoinmunes y Reumáticas; ArgentinaFil: Gordon, Sergio. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Fragoso Loyo, Hilda. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Rosario, Violeta. Hospital Docente Padre Billini; República DominicanaFil: Saurit, Verónica. Hospital Privado Universitario de Córdoba; ArgentinaFil: Appenzeller, Simone. Universidade Estadual de Campinas; BrasilFil: Dos Reis Neto, Edgard Torres. Universidade Federal de Sao Paulo; BrasilFil: Cieza, Jorge. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: González Naranjo, Luis A.. Universidad de Antioquia; ColombiaFil: González Bello, Yelitza C.. Ceibac; MéxicoFil: Collado, María Victoria. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Sarano, Judith. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Retamozo, Maria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; ArgentinaFil: Sattler, María E.. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Gamboa Cárdenas, Rocio V.. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Cairoli, Ernesto. Universidad de la República; UruguayFil: Conti, Silvana M.. Hospital Provincial de Rosario; ArgentinaFil: Amezcua Guerra, Luis M.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Silveira, Luis H.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Borba, Eduardo F.. Universidade de Sao Paulo; BrasilFil: Pera, Mariana A.. Hospital Interzonal General de Agudos General San Martín; ArgentinaFil: Alba Moreyra, Paula B.. Universidad Nacional de Córdoba. Facultad de Medicina; ArgentinaFil: Arturi, Valeria. Hospital Interzonal General de Agudos General San Martín; ArgentinaFil: Berbotto, Guillermo A.. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Gerling, Cristian. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Gobbi, Carla Andrea. Universidad Nacional de Córdoba. Facultad de Medicina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gervasoni, Viviana L.. Hospital Provincial de Rosario; ArgentinaFil: Scherbarth, Hugo R.. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Brenol, João C. Tavares. Hospital de Clinicas de Porto Alegre; BrasilFil: Cavalcanti, Fernando. Universidade Federal de Pernambuco; BrasilFil: Costallat, Lilian T. Lavras. Universidade Estadual de Campinas; BrasilFil: Da Silva, Nilzio A.. Universidade Federal de Goiás; BrasilFil: Monticielo, Odirlei A.. Hospital de Clinicas de Porto Alegre; BrasilFil: Seguro, Luciana Parente Costa. Universidade de Sao Paulo; BrasilFil: Xavier, Ricardo M.. Hospital de Clinicas de Porto Alegre; BrasilFil: Llanos, Carolina. Universidad Católica de Chile; ChileFil: Montúfar Guardado, Rubén A.. Instituto Salvadoreño de la Seguridad Social; El SalvadorFil: Garcia De La Torre, Ignacio. Hospital General de Occidente; MéxicoFil: Pineda, Carlos. Instituto Nacional de Rehabilitación; MéxicoFil: Portela Hernández, Margarita. Umae Hospital de Especialidades Centro Medico Nacional Siglo Xxi; MéxicoFil: Danza, Alvaro. Hospital Pasteur Montevideo; UruguayFil: Guibert Toledano, Marlene. Medical-surgical Research Center; CubaFil: Reyes, Gil Llerena. Medical-surgical Research Center; CubaFil: Acosta Colman, Maria Isabel. Hospital de Clínicas; ParaguayFil: Aquino, Alicia M.. Hospital de Clínicas; ParaguayFil: Mora Trujillo, Claudia S.. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: Muñoz Louis, Roberto. Hospital Docente Padre Billini; República DominicanaFil: García Valladares, Ignacio. Centro de Estudios de Investigación Básica y Clínica; MéxicoFil: Orozco, María Celeste. Instituto de Rehabilitación Psicofísica; ArgentinaFil: Burgos, Paula I.. Pontificia Universidad Católica de Chile; ChileFil: Betancur, Graciela V.. Instituto de Rehabilitación Psicofísica; ArgentinaFil: Alarcón, Graciela S.. Universidad Peruana Cayetano Heredia; Perú. University of Alabama at Birmingahm; Estados Unido

Scatterplot of MMR (on a natural logarithmic scale) and human development as measured by the HDI and IHDI.

<p>Scatterplot of MMR (on a natural logarithmic scale) and human development as measured by the HDI and IHDI.</p

Scatterplot of IMR (on a natural logarithmic scale) and human development as measured by the HDI and IHDI.

<p>Scatterplot of IMR (on a natural logarithmic scale) and human development as measured by the HDI and IHDI.</p

Geographic representation of the IMR.

<p>Open source polygon feature data for the maps were downloaded [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140796#pone.0140796.ref020" target="_blank">20</a>] and, subsequently, projected using ESRI ArcGIS [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140796#pone.0140796.ref021" target="_blank">21</a>].</p

Simple OLS Regression Models for MMR, IMR, ENMR, LNMR, and PNMR on HDI and IHDI.

<p><i>Note</i>. Bootstrap results are based on 1,000 bootstrap samples. All regression models are based on logarithmic transformations of the MMR, IMR, ENMR, LNMR, and PNMR variables.</p><p>Simple OLS Regression Models for MMR, IMR, ENMR, LNMR, and PNMR on HDI and IHDI.</p

Geographic representation of the MMR.

<p>Open source polygon feature data for the maps were downloaded [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140796#pone.0140796.ref020" target="_blank">20</a>] and, subsequently, projected using ESRI ArcGIS [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140796#pone.0140796.ref021" target="_blank">21</a>].</p