Cognitive Radio with Machine Learning to Increase Spectral Efficiency in Indoor Applications on the 2.5 GHz Band.

Due to the propagation characteristics in the 2.5 GHz band, the signal is significantly degraded by building entry loss (BEL), making coverage in indoor environments in some cases non-existent. Signal degradation inside buildings is a challenge for planning engineers, but it can be seen as a spectrum usage opportunity for a cognitive radio communication system. This work presents a methodology based on statistical modeling of data collected by a spectrum analyzer and the application of machine learning (ML) to leverage the use of those opportunities by autonomous and decentralized cognitive radios (CRs), independent of any mobile operator or external database. The proposed design targets using as few narrowband spectrum sensors as possible in order to reduce the cost of the CRs and sensing time, as well as improving energy efficiency. Those characteristics make our design especially interesting for internet of things (IoT) applications or low-cost sensor networks that may use idle mobile spectrum with high reliability and good recall.

Assessment of a Comparative Bayesian-Enhanced Population-Based Decision Model for COVID-19 Critical Care Prediction in the Dominican Republic Social Security Affiliates.

INTRODUCTION: The novel coronavirus disease 2019 (COVID-19) has been a major health concern worldwide. This study aims to develop a Bayesian model to predict critical outcomes in patients with COVID-19. METHODS: Sensitivity and specificity were obtained from previous meta-analysis studies. The complex vulnerability index (IVC-COV2 index for its abbreviation in Spanish) was used to set the pretest probability. Likelihood ratios were integrated into a Fagan nomogram for posttest probabilities, and IVC-COV2 + National Early Warning Score (NEWS) values and CURB-65 scores were generated. Absolute and relative diagnostic gains (RDGs) were calculated based on pretest and posttest differences. RESULTS: The IVC-COV2 index was derived from a population of 1,055,746 individuals and was based on mortality in high-risk (71.97%), intermediate-risk (26.11%), and low-risk (1.91%) groups. The integration of models in which IVC-COV2 intermediate + NEWS ≥ 5 and CURB-65 > 2 led to a "number needed to (NNT) diagnose" that was slightly improved in the CURB-65 model (2 vs. 3). A comparison of diagnostic gains revealed that neither the positive likelihood ratio (P = 0.62) nor the negative likelihood ratio (P = 0.95) differed significantly between the IVC-COV2 NEWS model and the CURB-65 model. CONCLUSION: According to the proposed mathematical model, the combination of the IVC-COV2 intermediate score and NEWS or CURB-65 score yields superior results and a greater predictive value for the severity of illness. To the best of our knowledge, this is the first population-based/mathematical model developed for use in COVID-19 critical care decision-making.

Prevalence and severity-based classification of sensory processing issues. An exploratory study with neuropsychological implications.

Sensory processing issues, mainly known as sensory processing disorder or SPD, are frequent in children with neurodevelopmental disorders and are associated with learning and behavioral difficulties. However, previous studies suggest that these disturbances might also be present in typically developing children, reaching prevalence rates of 10-20%. Nevertheless, published studies have been primary been conducted in non-European countries. Therefore, we aim, as first objective, to explore the frequency of sensory processing difficulties in a random sample of school-age children from Spain to contribute to the study of its prevalence. The Sensory Profile-2 (SP2) assessment tool was administered to 369 participants to study their sensory processing patterns, the absence or presence of sensory processing issues, the affected sensory systems, as well as their socioemotional, attentional, and behavioral impact. Furthermore, as second objective, we have developed a novel strategy to classify SPD by severity ranges using SP2 yielded results; accordingly, the sample was classified as follows: no alteration, mild, moderate, and severe sensory processing alteration. The results show prevalence rates consistent with previous findings: 15.9% of participants met the severe alteration criteria and 10.5%, 11.1% and 62.5% were classified as moderate, mild and no alteration, respectively. Finally, we hypothesize about SPD and underlying neuropsychological processes that might be associated with this condition. Our results highlight the necessity of further research efforts to establish whether high-frequency and severity rates of sensory processing alterations are linked to neuropsychological variables. The provided classification system might be useful to determine such associations.

Assessment Methods for Service-Learning Projects in Engineering in Higher Education: A Systematic Review.

Service-learning (SL) helps engineering students to be involved in community activities and to be motivated by their studies. Although several reviews and research studies have been published about SL, it is not widespread in sciences and engineering at the university level. The purpose of this research is to analyze the different community services or projects where SL is implemented by engineering students and faculty and to identify the procedures that were usually implemented to assess SL-based courses and activities. Assessment could be considered as the evaluation of a specific module and the engineering competencies, the evaluation of the effectiveness of the SL program, the assessment of the participation of the student in those programs, and the assessment of whether students have achieved certain outcomes or gained specific skills. We conducted a systematic review with a search in three scientific databases: Scopus, Science Direct, and ERIC educational database to analyze the assessment methods and what that assessment covers. From 14,107 publications related to SL, 120 documents were analyzed to inform the conclusions of this study. We found that SL is widely used in several universities as experiential education, and it is considered an academic activity. The most widely used assessment technique is a survey to evaluate the engagement and attitudes of students and, to a lesser extent, teamwork presentations.

Abdominal obesity and myocardial infarction risk - We demonstrate the anthropometric and mathematical reasons that justify the association bias of the waist-to-hip ratio / Obesidad abdominal y riesgo de infarto de miocardio: demostramos las razones antropométricas y matemáticas que justifican el sesgo de asociación del índice cintura-cadera

Background: the waist-to-hip ratio (WHR) is widely used to evaluate the association of abdominal obesity with myocardial infarction (MI). Objective: our aim was to determine whether WHR-associated risk provides a bias. Methods: a case-control study in 252 men. Stratification was used as an approach for removing bias effects. We created a baseline covariate (WHR0.95-0.99) from a new matched sample in the stratum between 0.95 and 0.99. This stratum coincides with the overlap area of the distribution, where all subjects have a similar propensity score. We considered other covariate (WHRS), conditioned on WHR < 1 and waist circumference (WC) being assigned a spurious risk. We hypothesized that subtracting hip circumference from WC (WHD) can be essential to observe the confounding effect provided by WHR. Results: BMI: AUC: 0.694, 95 % CI (0.628-0.760); OR: 3.8. WC: AUC: 0.743, 95 % CI (0.681-0.805); OR: 5.7. WHR: AUC: 0.798, 95 % CI (0.740-0.855); OR: 8.6. Waist-height ratio (WHtR): AUC: 0.782, 95 % CI (0.724-0.840); OR: 8.5. WHD: AUC: 0.204, 95 % CI (0.146-0.261); OR: 0.36. Prevalence in cases: WHR ≥ 0.95 (84.1 % vs. 38 %; OR: 8.6); WHR < 1 (36.3 % vs. 85.7 %; OR: 2.3); WHR ≥ 1 (63.4 % vs. 14.2 %; OR: 4.4); WC ≥ 94.4 (71.4 % vs. 30.1 %; OR: 5.7); WHD ≥ 2.2 (27.7 % vs. 75.3 %; OR: 7.9); WHRs (50 % vs. 25 %; OR: 2). Conclusions: WHR provides an association bias in MI cases. This can be extrapolated to other study populations. The bias is explained by a mathematical misconception where the protective effect of HC is overestimated concerning WC and height. The risk associated with WHR as higher than that associated with WC and WHtR entails anthropometric inconsistency and bias, to the extent of becoming epidemiologically false. (AU)

Antecedentes: el índice cintura-cadera (ICC) se utiliza ampliamente para evaluar la asociación de la obesidad abdominal con el infarto de miocardio (IM). Objetivo: nuestro propósito era determinar si el riesgo asociado a la ICC produce sesgo. Métodos: estudio de casos y controles en 252 varones. Usamos la estratificación como criterio para eliminar los efectos del sesgo. Creamos una covariable basal (ICC0,95-0,99) para una nueva muestra emparejada en el estrato de valores entre 0,95 y 0,99. Este estrato coincide con el área común de solapamiento de la distribución de puntos, donde todos los sujetos tienen un índice de propensión similar. Consideramos otra covariable (ICCS) condicionada en ICC < 1 y una circunferencia de cintura (CC) donde la asignación de riesgo fuera espúrea. Hipotetizamos que restando CC del valor de la cadera se calculaba otra variable aritmética (DCC) que podría ser esencial para evidenciar el efecto de confusion que genera el ICC. Resultados: IMC: ABC: 0,694, IC 95 % (0,628-0,760); OR: 3,8. CC: ABC: 0,743, IC 95 % (0,681-0,805); OR: 5,7. ICC: ABC: 0,798, IC 95 % (0,740-0,855); OR: 8,6. Índice cintura-talla (ICT): ABC: 0,782, IC 95 % (0,724-0,840); OR: 8,5. DCC: ABC: 0,204, IC 95 % (0,146-0,261); OR: 0,36. Prevalencia en los casos: ICC ≥ 0,95 (84,1 % vs. 38 %; OR: 8,6); ICC < 1 (36,3 % vs. 85,7 %; OR: 2,3); ICC ≥ 1 (63,4 % vs. 14,2 %; OR: 4,4); CC ≥ 94,4 (71,4 % vs. 30,1 %; OR: 5,7); DCC ≥ 2,2 (27,7 % vs. 75,3 %; OR: 7,9); ICCs (50 % vs. 25 %; OR: 2). Conclusiones: el ICC produce un sesgo de asociación en los casos de IM. Ello puede extrapolarse a otras poblaciones de estudio. El sesgo se explica por un error de concepto matemático que sobreestima el efecto protector de la cadera con respecto a la CC y la altura. El riesgo asociado al ICC por encima del de la CC o el ICT presenta inconsistencia antropométrica y sesgo, llegando a ser epidemiológicamente falso. (AU)

Abdominal obesity and myocardial infarction risk - We demonstrate the anthropometric and mathematical reasons that justify the association bias of the waist-to-hip ratio.

INTRODUCTION: Antecedentes: el índice cintura-cadera (ICC) se utiliza ampliamente para evaluar la asociación de la obesidad abdominal con el infarto de miocardio (IM). Objetivo: nuestro propósito era determinar si el riesgo asociado a la ICC produce sesgo. Métodos: estudio de casos y controles en 252 varones. Usamos la estratificación como criterio para eliminar los efectos del sesgo. Creamos una covariable basal (ICC0,95-0,99) para una nueva muestra emparejada en el estrato de valores entre 0,95 y 0,99. Este estrato coincide con el área común de solapamiento de la distribución de puntos, donde todos los sujetos tienen un índice de propensión similar. Consideramos otra covariable (ICCS) condicionada en ICC < 1 y una circunferencia de cintura (CC) donde la asignación de riesgo fuera espúrea. Hipotetizamos que restando CC del valor de la cadera se calculaba otra variable aritmética (DCC) que podría ser esencial para evidenciar el efecto de confusion que genera el ICC. Resultados: IMC: ABC: 0,694, IC 95 % (0,628-0,760); OR: 3,8. CC: ABC: 0,743, IC 95 % (0,681-0,805); OR: 5,7. ICC: ABC: 0,798, IC 95 % (0,740-0,855); OR: 8,6. Índice cintura-talla (ICT): ABC: 0,782, IC 95 % (0,724-0,840); OR: 8,5. DCC: ABC: 0,204, IC 95 % (0,146-0,261); OR: 0,36. Prevalencia en los casos: ICC ≥ 0,95 (84,1 % vs. 38 %; OR: 8,6); ICC < 1 (36,3 % vs. 85,7 %; OR: 2,3); ICC ≥ 1 (63,4 % vs. 14,2 %; OR: 4,4); CC ≥ 94,4 (71,4 % vs. 30,1 %; OR: 5,7); DCC ≥ 2,2 (27,7 % vs. 75,3 %; OR: 7,9); ICCs (50 % vs. 25 %; OR: 2). Conclusiones: el ICC produce un sesgo de asociación en los casos de IM. Ello puede extrapolarse a otras poblaciones de estudio. El sesgo se explica por un error de concepto matemático que sobreestima el efecto protector de la cadera con respecto a la CC y la altura. El riesgo asociado al ICC por encima del de la CC o el ICT presenta inconsistencia antropométrica y sesgo, llegando a ser epidemiológicamente falso.

INTRODUCCIÓN: Background: the waist-to-hip ratio (WHR) is widely used to evaluate the association of abdominal obesity with myocardial infarction (MI). Objective: our aim was to determine whether WHR-associated risk provides a bias. Methods: a case-control study in 252 men. Stratification was used as an approach for removing bias effects. We created a baseline covariate (WHR0.95-0.99) from a new matched sample in the stratum between 0.95 and 0.99. This stratum coincides with the overlap area of the distribution, where all subjects have a similar propensity score. We considered other covariate (WHRS), conditioned on WHR < 1 and waist circumference (WC) being assigned a spurious risk. We hypothesized that subtracting hip circumference from WC (WHD) can be essential to observe the confounding effect provided by WHR. Results: BMI: AUC: 0.694, 95 % CI (0.628-0.760); OR: 3.8. WC: AUC: 0.743, 95 % CI (0.681-0.805); OR: 5.7. WHR: AUC: 0.798, 95 % CI (0.740-0.855); OR: 8.6. Waist-height ratio (WHtR): AUC: 0.782, 95 % CI (0.724-0.840); OR: 8.5. WHD: AUC: 0.204, 95 % CI (0.146-0.261); OR: 0.36. Prevalence in cases: WHR ≥ 0.95 (84.1 % vs. 38 %; OR: 8.6); WHR < 1 (36.3 % vs. 85.7 %; OR: 2.3); WHR ≥ 1 (63.4 % vs. 14.2 %; OR: 4.4); WC ≥ 94.4 (71.4 % vs. 30.1 %; OR: 5.7); WHD ≥ 2.2 (27.7 % vs. 75.3 %; OR: 7.9); WHRs (50 % vs. 25 %; OR: 2). Conclusions: WHR provides an association bias in MI cases. This can be extrapolated to other study populations. The bias is explained by a mathematical misconception where the protective effect of HC is overestimated concerning WC and height. The risk associated with WHR as higher than that associated with WC and WHtR entails anthropometric inconsistency and bias, to the extent of becoming epidemiologically false.

Obesity vs. Whole-body-fat and myocardial infarction risk prediction. Body fat percentageis better indicator / Obesidad vs. grasa corporal total y predicción de riesgo de infarto. El porcentaje de grasa corporal es mejor indicador

OBJECTIVE: Our aim was to realize an anthropometric analysis to identify both the association and plausibility of measurements and indicators of general obesity and whole-body fat on the risk prediction for myocardial infarction (MI) in men. MATERIAL AND METHOD: A case-control study in 244 European men aged 30-74 years was conducted. We measured weight, height, waist and hip perimeters and skinfolds: triceps, subscapular and supraspinale, according to standardized protocols. We calculated the areas under the ROC curves, the odds ratios and correlations for indicators. RESULTS: Body mass index (BMI) [AUC: 0.687, 95% CI (0.619-0.715); OR: 3.5]. Waist circumference (WC) [AUC: 0.742, 95% CI (0.679-0.805); OR: 5.9]. Waist-to-height ratio (WHtR) [AUC: 0.780, 95% CI (0.721-0.839); OR: 8.4]. Endomorphy [AUC: 0.721, 95% CI (0.656-0.785); OR: 2.4]. Body fat percentage (%BF) [AUC: 0.774, 95% CI (0.714-0.834); OR: 10.2]. Lean body mass (LBM) [AUC: 0.490, 95% CI (0.413-0.568); OR: 1]. BMI correlated with %BF (0.84), endomorphy (0.80), WC (0.69), WHtR (0.72) and LBM (0.65). WHtR correlated with WC (0.97), %BF (0.92), endomorphy (0.62) and LBM (0.32). %BF correlated with WC (0.86) and endomorphy (0.78). The correlations between WHtR and body fat-associated indicators were strong (all r ≥ 0.62, p < 0.001). CONCLUSIONS: In MI men, body fat-associated indicators show different discriminative ability. BMI-defined obesity presents moderate discrimination and anthropometric association bias that do not lent support their suitability as risk predictor. Abdo-minal adiposity and whole-body fat percentage show the highest discriminative abilities and robust anthropometric reasons related with the true biological risk. We defend the use of WHtR as concept of risk volume and individual visceral adiposity for the early identification of adult men at risk of myocardial infarction

INTRODUCCIÓN: Nuestro objetivo era realizar un análisis por antropometría para identificar la asociación y plausibilidad de mediciones e indicadores de obesidad general y grasa corporal total en la predicción de riesgo de infarto en varones. MATERIAL Y MÉTODO: estudio caso-control en 244 varones de 30 a 74 años de edad. Medimos peso y talla, perímetros de cintura y cadera, y pliegues de triceps, subescapular y supraespinal, según protocolos estandarizados. Obtuvimos las áreas bajo la curva ROC y las odds ratios para la asociación de indicadores. RESULTADOS: índice de masa corporal (IMC) [ABC: 0,687, 95% CI (0,619-0,715); OR: 3,5]. Circunferencia de cintura (CC) [ABC: 0,742, 95% CI (0,679-0,805); OR: 5,9]. Índice cintura-talla (ICT) [ABC: 0,780, 95% CI (0,721-0,839); OR: 8.4]. Endomorfia [ABC: 0,721, 95% CI (0,656-0,785); OR: 2,4]. Porcentaje de grasa corporal (GC%) [ABC: 0,774, 95% CI (0,714-0,834); OR: 10,2]. Masa magra (MM) [ABC: 0,490, 95% CI (0,413-0,568); OR: 1]. IMC correlacionó con GC% (0,84), endomorfia (0,80), CC (0,69), ICT (0,72) y MM (0,65). ICT correlacionó con CC (0,97), GC% (0,92), endomorfia (0,62) y MM (0,32). GC% correlacionó con CC (0,86) y endomorfia (0,78). Las correlaciones entre ICT y los indicadores asociados a la grasa corporal fueron fuertes (todas r ≥ 0,62, p < 0,001). CONCLUSIONES: En los varones infartados, los indicadores asociados a la grasa corporal muestran diferente capacidad discriminativa. El IMC presenta moderada discriminación y sesgos de asociación antropométrica que no avalan su idoneidad como predictor de riesgo. La obesidad abdominal y el porcentaje de grasa corporal muestran las mayores capacidades discriminativas y robustas razones antropométricas relacionadas con el verdadero riesgo biológico. Nosotros defendemos el uso del índice cintura-talla como concepto de volumen de riesgo y adiposidad visceral individual para la temprana identificación de varones adultos en riesgo de infarto de miocardio

Obesity and risk of myocardial infarction in a sample of European males. Waist to-hip-ratio presents information bias of the real risk of abdominal obesity / Obesidad y riesgo de infarto de miocardio en una muestra de varones europeos. El índice cintura-cadera sesga el riesgo real de la obesidad abdominal

Background: Obesity is a coronary risk factor associated to myocardial infarction although waist to-hip-ratio has shown higher predictive power. Objective: The aim of this study was a Receiver Operating Characteristic anthropometric analysis in infarcted males to identify the strength of association for simple measurements, obesity and indicators such as, waist to-hip-ratios, waist to-height-ratios and conicity index. Methods:Case-control study of myocardial infarction in European males. One hundred and twelve cases and 112 controls aged 30-74 years were enrolled. We measured weight, height, waist circumference, umbilical waist circumference and hip circumference. We calculated various anthropometric indicators. We obtained the areas under the ROC curves, the odds ratio and correlations for measurements and anthropometric indicators. Results: Body mass index [AUC: 0.686, 95% CI (0.616-0.755); OR: 3.3], waist circumference [AUC: 0.734, 95% CI (0.668-0.800); OR: 5.7], height [AUC: 0.623, 95% CI (0.550-0.696); OR: 2.3], hip circumference [AUC: 0.555, 95% CI (0.479-0.631); OR: 1], waist to-hip-ratio [AUC: 0.796, 95% CI (0.737-0.855); OR: 9.9], umbilical waist to-hip-ratio [AUC: 0.830, 95% CI (0.729-0.847); OR: 5.5], umbilical waist to-height-ratio [AUC: 0.788, 95% CI (0.729-0.847); OR: 7.5], conicity index [AUC: 0.795; 95% CI (0.738-0.853); OR: 9]. The correlations for waist to-height-ratios and conicity index were strong (all r ≥ 0.85; p < 0.001). Conclusions: Waist and height are measurements of associated independent risk. Hip circumference does no show discriminatory power. Obesity and waist-ratios are associated to myocardial infarction with different strength. Between other indicators, general obesity is more weakly associated. Waist to-hip-ratios present the best ROC curves but it occur information bias of their predictive power of risk. Umbilical waist to-height-ratio and conicity index present high discriminatory power and the best anthropometric risk correlations that support its use for the identification of obesity as risk factor associated to myocardial infarction and in all strategies for coronary health promotion.

Introducción: la obesidad es un factor de riesgo asociado al infarto de miocardio aunque el índice cintura-cadera ha mostrado mayor poder predictivo. Objetivo: análisis antropométrico Receiver Operating Characteristic (ROC) en infartados para identificar la fuerza discriminatoria de mediciones, obesidad, ratios cintura-cadera, ratios cintura-talla e índice de conicidad. Métodos: estudio caso-control de infarto miocárdico en varones europeos. Ciento doce casos/112 controles de 30-74 años fueron reclutados. Se midieron: peso, talla, cintura, cintura umbilical y cadera. Se obtuvieron las áreas bajo la curva (ABC), las odds ratio y correlaciones de medidas e indicadores. Resultados: IMC [ABC: 0,686 (0,616-0,755); OR: 3,3], cintura [ABC: 0,734 (0,668-0,800); OR: 5,7], talla [ABC: 0,623 (0,550-0,696); OR: 2,3], cadera [ABC: 0,555 (0,479-0,631); OR: 1], cintura-cadera [ABC: 0,796 (0,737-0,855); OR: 9,9]; cintura umbilical-cadera [ABC:0,830 (0,775-0,885); OR: 5,5], cintura umbilical-talla [ABC: 0,788 (0,729-0,847); OR: 7,5]; conicidad [ABC: 0,795 (0,738-0,853); OR:9]. Cintura-talla y conicidad presentaron altas correlaciones de riesgo (todas r ≥ 0,85; p < 0,001). Conclusiones: cintura y talla son medidas con riesgo independiente asociado. La circunferencia de cadera no es discriminatoria. Obesidad e índices de cintura están asociados al infarto con diferente fuerza. La obesidad presenta una asociación débil. Los índices cintura-cadera presentan las mejores curvas ROC, pero sesgadas en su poder predictivo de riesgo. Cintura umbilical-talla y conicidad presentan alto poder discriminatorio y mejores correlaciones antropométricas de riesgo, por lo que se recomienda su uso en la identificación de la obesidad como factor asociado al infarto de miocardio y en todas las estrategias de promoción de la salud coronaria.

Obesidad y riesgo de infarto de miocardio en una muestra de varones europeos. El índice cintura-cadera sesga el riesgo real de la obesidad abdominal / Obesity and risk of myocardial infarction in a sample of European males. Waist to-hip-ratio presents information bias of the real risk of abdominal obesity

Introducción: la obesidad es un factor de riesgo asociado al infarto de miocardio aunque el índice cintura-cadera ha mostrado mayor poder predictivo. Objetivo: análisis antropométrico Receiver Operating Characteristic (ROC) en infartados para identificar la fuerza discriminatoria de mediciones, obesidad, ratios cintura-cadera, ratios cintura-talla e índice de conicidad. Métodos: estudio caso-control de infarto miocárdico en varones europeos. Ciento doce casos/112 controles de 30-74 años fueron reclutados. Se midieron: peso, talla, cintura, cintura umbilical y cadera. Se obtuvieron las áreas bajo la curva (ABC), las odds ratio y correlaciones de medidas e indicadores. Resultados: IMC [ABC: 0,686 (0,616-0,755); OR: 3,3], cintura [ABC: 0,734 (0,668-0,800); OR: 5,7], talla [ABC: 0,623 (0,550-0,696); OR: 2,3], cadera [ABC: 0,555 (0,479-0,631); OR: 1], cintura-cadera [ABC: 0,796 (0,737-0,855); OR: 9,9]; cintura umbilical-cadera [ABC:0,830 (0,775-0,885); OR: 5,5], cintura umbilical-talla [ABC: 0,788 (0,729-0,847); OR: 7,5]; conicidad [ABC: 0,795 (0,738-0,853); OR:9]. Cintura-talla y conicidad presentaron altas correlaciones de riesgo (todas r ≥ 0,85; p < 0,001). Conclusiones: cintura y talla son medidas con riesgo independiente asociado. La circunferencia de cadera no es discriminatoria. Obesidad e índices de cintura están asociados al infarto con diferente fuerza. La obesidad presenta una asociación débil. Los índices cintura-cadera presentan las mejores curvas ROC, pero sesgadas en su poder predictivo de riesgo. Cintura umbilical-talla y conicidad presentan alto poder discriminatorio y mejores correlaciones antropométricas de riesgo, por lo que se recomienda su uso en la identificación de la obesidad como factor asociado al infarto de miocardio y en todas las estrategias de promoción de la salud coronaria (AU)

Background: Obesity is a coronary risk factor associated to myocardial infarction although waist to-hip-ratio has shown higher predictive power. Objective: The aim of this study was a Receiver Operating Characteristic anthropometric analysis in infarcted males to identify the strength of association for simple measurements, obesity and indicators such as, waist to-hip-ratios, waist to-height-ratios and conicity index. Methods: Case-control study of myocardial infarction in European males. One hundred and twelve cases and 112 controls aged 30-74 years were enrolled. We measured weight, height, waist circumference, umbilical waist circumference and hip circumference. We calculated various anthropometric indicators. We obtained the areas under the ROC curves, the odds ratio and correlations for measurements and anthropometric indicators. Results: Body mass index [AUC: 0.686, 95% CI (0.616-0.755); OR: 3.3], waist circumference [AUC: 0.734, 95% CI (0.668-0.800); OR: 5.7], height [AUC: 0.623, 95% CI (0.550-0.696); OR: 2.3], hip circumference [AUC: 0.555, 95% CI (0.479-0.631); OR: 1], waist to-hip-ratio [AUC: 0.796, 95% CI (0.737-0.855); OR: 9.9], umbilical waist to-hip-ratio [AUC: 0.830, 95% CI (0.729-0.847); OR: 5.5], umbilical waist to-height-ratio [AUC: 0.788, 95% CI (0.729-0.847); OR: 7.5], conicity index [AUC: 0.795; 95% CI (0.738-0.853); OR: 9]. The correlations for waist to-height-ratios and conicity index were strong (all r ≥ 0.85; p < 0.001). Conclusions: Waist and height are measurements of associated independent risk. Hip circumference does no show discriminatory power. Obesity and waist-ratios are associated to myocardial infarction with different strength. Between other indicators, general obesity is more weakly associated. Waist to-hip-ratios present the best ROC curves but it occur information bias of their predictive power of risk. Umbilical waist to-height-ratio and conicity index present high discriminatory power and the best anthropometric risk correlations that support its use for the identification of obesity as risk factor associated to myocardial infarction and in all strategies for coronary health promotion (AU)

Entomological factors affecting the low endemicity of Chagas disease in Nazca, Southwestern Peru.

Chagas disease is prevalent in Peru. The province of Nazca, in the southwestern region of the country, shows a high intradomiciliary infestation rate of Triatoma infestans bugs. Although the vector is present, the number of Chagas disease cases appears to be much lower than those reported in the neighboring region of Arequipa. We examined 624 T. infestans from Nazca to determine the current Trypanosoma cruzi infection rates, and found that no bugs were infected with this parasite. These results contrast with those found in Arequipa, where 19-30% triatomines have been reported infected. To compare their vectorial capacity, we infected 30 T. infestans specimens, selected both from Nazca and Arequipa, by feeding bugs on T. cruzi-infected mice. The parasites developed all stages expected in the vector; furthermore, the infective stage, metacyclic trypomastigote, was found in both insect populations from the second week after infection. In addition, those insects that accepted to be fed with mice blood defecated immediately after finishing blood meal, indicating that they might be efficient vectors. We maintain that differences observed in infection rates between vectors from Nazca and Arequipa may be explained by differences in host availability. In Arequipa hosts are mainly small animals, whereas in Nazca the main blood source comes from birds, which are refractory to the infection.