Patients Living With Arterial Hypertension in Mexico: First Insights of The Mexican Registry of Arterial Hypertension (RIHTA Study).

BACKGROUND: Arterial hypertension is a significant cause of morbidity and mortality in Mexico. However, there is limited evidence to understand blood pressure management and cardiometabolic profiles. Here, we aim to assess the prevalence of controlled and uncontrolled blood pressure, as well as the prevalence of cardiometabolic risk factors among patients from the Mexican Registry of Arterial Hypertension (RIHTA). METHODS: We conducted a cross-sectional analysis of participants living with arterial hypertension registered on RIHTA between December 2021 and April 2023. We used both the 2017 ACC/AHA and 2018 ESC/ESH thresholds to define controlled and uncontrolled arterial hypertension. We considered eleven cardiometabolic risk factors, which include overweight, obesity, central obesity, insulin resistance, diabetes, hypercholesterolemia, hypertriglyceridemia, low HDL-C, high LDL-C, low-eGFR, and high cardiovascular disease (CVD) risk. RESULTS: In a sample of 5,590 participants (female: 61%, n = 3,393; median age: 64 [IQR: 56-72] years), the prevalence of uncontrolled hypertension varied significantly, depending on the definition (2017 ACC/AHA: 59.9%, 95% CI: 58.6-61.2 and 2018 ESC/ESH: 20.1%, 95% CI: 19.0-21.2). In the sample, 40.43% exhibited at least 5-6 risk factors, and 32.4% had 3-4 risk factors, chiefly abdominal obesity (83.4%, 95% CI: 82.4-84.4), high LDL-C (59.6%, 95% CI: 58.3-60.9), high CVD risk (57.9%, 95% CI: 56.6-59.2), high triglycerides (56.2%, 95% CI: 54.9-57.5), and low HDL-C (42.2%, 95% CI: 40.9-43.5). CONCLUSIONS: There is a high prevalence of uncontrolled hypertension interlinked with a high burden of cardiometabolic comorbidities in Mexican adults living with arterial hypertension, underscoring the urgent need for targeted interventions and better healthcare policies to reduce the burden of the disease in our country.

[Risk factors associated with cognitive impairment in aged: Cross-sectional study]. / Factores de riesgo asociados a deterioro cognitivo en adultos mayores: estudio transversal.

Background: With the increase in life expectancy, conditions related to older age have increased in incidence, one of these pathologies is Cognitive Impairment (CI), which has a prevalence of up to 28%, conditions that increase the presence of CI are known. However, there is controversy about the factors that increase the risk of CI. Objective: To determine the factors associated with cognitive impairment in older adults. Material and methods: We conducted a cross-sectional, analytical, observational, retroprolective study that included adults ≥65 years of age, with no history of cerebral vascular event, cranioencephalic trauma. Demographic factors were analyzed, CI was assessed with the Mini Mental State Examination test. For statistical analysis we used Odds Ratio (OR) and 95% confidence interval (95% CI) for each factor and multiple logistic regression as multivariate analysis. Results: 420 older adults were included, 61% were women, 32.6% with age >75 years, 84.5% with schooling <9 years, in the multiple logistic regression the following were independent factors for the presence of mild CI: dependence on basic activities of daily living (ADLs) with OR 5.88, absence of cognitive stimulation RM 4.50, age >75 years OR 2.92, polypharmacy OR 2.16, uncontrolled blood pressure OR 1.92. Conclusion: ADLs dependence, absence of cognitive stimulation, age >75 years, polypharmacy and uncontrolled blood pressure are risk factors associated with CI in older adults.

Introducción: con el aumento en la esperanza de vida las condiciones relacionadas con mayor edad incrementaron su incidencia; una de estas patologías es el deterioro cognitivo (DC) que presenta una prevalencia de hasta el 28%, hoy en día se conocen condiciones que aumentan la presencia de DC. Sin embargo, existe controversia sobre los factores que aumentan el riesgo para su presencia. Objetivo: determinar los factores asociados al deterioro cognitivo en adultos mayores. Material y métodos: se realizó un estudio transversal, analítico, observacional, retroprolectivo que incluyó a adultos ≥ 65 años, sin antecedente de evento vascular cerebral o traumatismo craneoencefálico. Se analizaron factores demográficos, el DC se evaluó con la prueba Mini-Mental. Para el análisis estadístico se usó razón de momios (RM) e intervalo de confianza al 95% (IC95%) para cada factor y como análisis multivariado, regresión logística múltiple. Resultados: se incluyeron 420 adultos mayores, de los cuales el 61% eran mujeres, el 32.6% tenían edad > 75 años, el 84.5% con escolarización < 9 años. En la regresión logística múltiple los siguientes fueron factores independientes para la presencia de DC leve: la dependencia de actividades básicas de la vida diaria (ABVD), ausencia de estimulación cognitiva, edad > 75 años, polifarmacia y descontrol de tensión arterial. Conclusión: la dependencia de ABVD, ausencia de estimulación cognitiva, edad > 75 años, polifarmacia y descontrol de la tensión arterial son factores de riesgo asociados al DC en adultos mayores.

High Virulence and Multidrug Resistance of Escherichia coli Isolated in Periodontal Disease.

Periodontal disease is caused by different gram-negative anaerobic bacteria; however, Escherichia coli has also been isolated from periodontitis and its role in periodontitis is less known. This study aimed to determine the variability in virulence genotype, antibiotic resistance phenotype, biofilm formation, phylogroups, and serotypes in different emerging periodontal strains of Escherichia coli, isolated from patients with periodontal disease and healthy controls. E. coli, virulence genes, and phylogroups, were identified by PCR, antibiotic susceptibility by the Kirby-Bauer method, biofilm formation was quantified using polystyrene microtiter plates, and serotypes were determined by serotyping. Although E. coli was not detected in the controls (n = 70), it was isolated in 14.7% (100/678) of the patients. Most of the strains (n = 81/100) were multidrug-resistance. The most frequent adhesion genes among the strains were fimH and iha, toxin genes were usp and hlyA, iron-acquisition genes were fyuA and irp2, and protectin genes were ompT, and KpsMT. Phylogroup B2 and serotype O25:H4 were the most predominant among the strains. These findings suggest that E. coli may be involved in periodontal disease due to its high virulence, multidrug-resistance, and a wide distribution of phylogroups and serotypes.

Risk factors associated with SARS-CoV-2 pneumonia in the pediatric population.

INTRODUCCIÓN: Hasta ahora existen pocos estudios sobre las características clínicas de la población pediátrica con neumonía por COVID-19. El objetivo de este estudio fue analizar los datos que se asocian con el desarrollo de neumonía en niños y adolescentes con infección por SARS-CoV-2 en México. MÉTODOS: Se llevó a cabo un análisis secundario de la base de datos de la Dirección General de Epidemiología del Gobierno Mexicano. Se incluyeron menores de 19 años con infección por SARS-CoV-2 confirmada mediante la prueba de retrotranscripción acoplada a la reacción en cadena de la polimerasa (RT-PCR). La variable dependiente fue el diagnóstico de neumonía. Se calcularon las razones de momios (RM) y los intervalos de confianza del 95% (IC95%). Se realizaron modelos de regresión logística múltiple para ajustar los factores asociados a neumonía. RESULTADOS: Se incluyeron 1443 niños con diagnóstico de COVID-19. La mediana de edad de los participantes fue de 12 años (rango intercuartilar 25-75: 5-16). La neumonía se presentó en 141 niños (9.8%). Los principales factores de riesgo fueron edad < 3 años (RM: 3.5; IC95%: 2.45-5.03), diabetes u obesidad (RM: 12.6; IC95%: 4.62-34.91) e inmunocompromiso (RM: 7.03; IC95%: 3.97-13.61). CONCLUSIONES: Los niños con COVID-19 menores de 3 años y con comorbilidad, especialmente diabetes u obesidad, y los inmunocomprometidos presentan mayor riesgo de desarrollar neumonía. BACKGROUND: Currently, there are a few studies on the clinical characteristics of the pediatric population with COVID-19 and pneumonia. This study aimed to analyze data associated with the development of pneumonia in children and adolescents with SARS-CoV-2 infection throughout Mexico. METHODS: We conducted a secondary analysis of the database of the Dirección General de Epidemiología of the Mexican Government. We included children under the age of 19 who were confirmed with SARS-CoV-2 infection by reverse transcription-polymerase chain reaction (RT-PCR) test. The dependent variable was the diagnosis of pneumonia. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated. Multiple logistic regression models were performed to adjust factors associated with pneumonia. RESULTS: A total of 1443 children with a COVID-19 diagnosis were included. The median age of the participants was 12 years (interquartile range 25, 75: 5, 16). Pneumonia occurred in 141 children (9.8%). The main risk factors were age < 3 years (OR, 3.5; 95%CI, 2.45-5.03); diabetes or obesity (OR, 12.6; 95%CI, 4.62-34.91); and immunocompromise (OR, 7.03; 95%CI, 3.97-13.61). CONCLUSIONS: Children < 3 years with COVID-19 and comorbidities, especially diabetes or obesity, and immunocompromised patients have a higher risk of developing pneumonia.

Risk factors associated with SARS-CoV-2 pneumonia in the pediatric population / Factores de riesgo asociados con neumonía por SARS-CoV-2 en población pediátrica

Abstract Background: Currently, there are a few studies on the clinical characteristics of the pediatric population with COVID-19 and pneumonia. This study aimed to analyze data associated with the development of pneumonia in children and adolescents with SARS-CoV-2 infection throughout Mexico. Methods: We conducted a secondary analysis of the database of the Dirección General de Epidemiología of the Mexican Government. We included children under the age of 19 who were confirmed with SARS-CoV-2 infection by reverse transcription-polymerase chain reaction (RT-PCR) test. The dependent variable was the diagnosis of pneumonia. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated. Multiple logistic regression models were performed to adjust factors associated with pneumonia. Results: A total of 1443 children with a COVID-19 diagnosis were included. The median age of the participants was 12 years (interquartile range 25, 75: 5, 16). Pneumonia occurred in 141 children (9.8%). The main risk factors were age < 3 years (OR, 3.5; 95%CI, 2.45-5.03); diabetes or obesity (OR, 12.6; 95%CI, 4.62-34.91); and immunocompromise (OR, 7.03; 95%CI, 3.97-13.61). Conclusions: Children < 3 years with COVID-19 and comorbidities, especially diabetes or obesity, and immunocompromised patients have a higher risk of developing pneumonia.

Resumen Introducción: Hasta ahora existen pocos estudios sobre las características clínicas de la población pediátrica con neumonía por COVID-19. El objetivo de este estudio fue analizar los datos que se asocian con el desarrollo de neumonía en niños y adolescentes con infección por SARS-CoV-2 en México. Métodos: Se llevó a cabo un análisis secundario de la base de datos de la Dirección General de Epidemiología del Gobierno Mexicano. Se incluyeron menores de 19 años con infección por SARS-CoV-2 confirmada mediante la prueba de retrotranscripción acoplada a la reacción en cadena de la polimerasa (RT-PCR). La variable dependiente fue el diagnóstico de neumonía. Se calcularon las razones de momios (RM) y los intervalos de confianza del 95% (IC95%). Se realizaron modelos de regresión logística múltiple para ajustar los factores asociados a neumonía. Resultados: Se incluyeron 1443 niños con diagnóstico de COVID-19. La mediana de edad de los participantes fue de 12 años (rango intercuartilar 25-75: 5-16). La neumonía se presentó en 141 niños (9.8%). Los principales factores de riesgo fueron edad < 3 años (RM: 3.5; IC95%: 2.45-5.03), diabetes u obesidad (RM: 12.6; IC95%: 4.62-34.91) e inmunocompromiso (RM: 7.03; IC95%: 3.97-13.61). Conclusiones: Los niños con COVID-19 menores de 3 años y con comorbilidad, especialmente diabetes u obesidad, y los inmunocomprometidos presentan mayor riesgo de desarrollar neumonía.

[The relevance and irrelevance of charts in clinical research]. / Pertinencia e impertinencia de los gráficos en la investigación clíni-ca.

Charts are a visual aid that is used in articles in order to highlight the results of an investigation. They allow illustrating the results with the purpose of making them clearer. Charts, just like statistical tests, are selected based on the objective of the study, the types of variable, and the statistical analyzes to be illustrated. Some of the most commonly used charts in clinical practice are frequency histograms, which illustrate qualitative variables or frequencies; also error charts, that are used for normally distributed quantitative variables; box plots or violin plots are used for distribution-free quantitative variables, and survival curves are for variables that include the person-time variable. The aforementioned charts can be used to illustrate the comparisons between maneuvers and outcome depending on the type of variable that is being analyzed. When two groups are compared and the dependent variable is dichotomous, forest plots are used; for multivariate models, the chart depends on the type of analysis. As for logistic regression and linear regression, tree diagrams are used; and scatter plots are used for linear regression. Survival plots are used for Cox proportional hazards. Although charts can be very useful, if they are misused, they can show differences where there are none, which leads to a misinterpretation of the studies. In this article, we will use examples to complement the topics that were previously addressed in the articles of this series.

Los gráficos constituyen una ayuda visual que usan los artículos para resaltar los resultados de una investigación. Estos permiten ilustrar los resultados con el fin de hacerlos más claros. Los gráficos, al igual que las pruebas estadísticas, se seleccionan a partir del objetivo del estudio, de los tipos de variable y de los análisis estadísticos que se desee ilustrar. Algunos de los gráficos más usados en la práctica clínica son los histogramas de frecuencia que ilustran las variables cualitativas o frecuencias, los gráficos de error se usan para variables cuantitativas con distribución normal, el gráfico de cajas o gráfico de violín para variables cuantitativas de libre distribución y las curvas de supervivencia para las variables que incluyen la variable tiempo/persona. Estos mismos gráficos pueden ser usados para ilustrar las comparaciones entre maniobras y desenlace dependiendo del tipo de variable que se analice. Cuando se comparan dos grupos y la variable dependiente es dicotómica se usan gráficos de bosque. Para los modelos multivariados los gráficos dependen del tipo de análisis, en el caso de la regresión logística se utilizan gráficos de árbol y para la regresión lineal, de dispersión; y para los riesgos proporcionales de Cox, gráficos de supervivencia. Si bien los gráficos son de gran utilidad, mal utilizados pueden mostrar diferencias donde no las hay, provocando una errónea interpretación de los estudios. En este artículo complementaremos con ejemplos los temas abordados con anterioridad en los artículos de esta misma serie.