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11 results on '"Cardona-Pérez, Arturo"'

3. Clinical characteristics and risk factors for SARS-CoV-2 infection in pregnant women attending a third level reference center in Mexico City.

Author

Hernández-Cruz, Rosa Gabriela, Sánchez-Cobo, Daniela, Acevedo-Gallegos, Sandra, Helguera-Repetto, Addy Cecilia, Rodriguez-Bosch, Mario Roberto, Ramirez-Santes, Victor Hugo, Villegas-Mota, Isabel, Cardona-Pérez, Arturo, Cortes-Bonilla, Manuel, Irles, Claudine, Mateu-Rogell, Paloma, Villanueva-Calleja, Job, Carrisoza, Oscar Villavicencio, Estrada-Gutiérrez, Gaudalupe, Espino-Y-Sosa, Salvador, Torres-Torres, Johnatan, and Martinez-Portilla, Raigam Jafet

Subjects
PREGNANT women, SARS-CoV-2, MEDICAL screening, INFECTION, LOGISTIC regression analysis
Abstract

Background COVID-19 symptoms vary widely among pregnant women. We aimed to assess the most frequent symptoms amongst pregnant women with SARS-CoV-2 infection in a tertiary hospital in Mexico City. Methods A cross-sectional study of pregnant women attending the National Institute of Perinatology in Mexico City was performed. All women who attended the hospital, despite their symptoms, were tested for SARS-CoV-2. A multivariate-age-adjusted logistic regression was used to assess the association between the main outcome and each characteristic of the clinical history. Results A total of 1880 women were included in the data analysis. Among all women, 30.74% (n = 578) had a positive PCR for SARS-CoV-2 from which 2.7 (n = 50) were symptomatic. Symptoms associated with a positive PCR result were headache (p=.01), dyspnea (p=.043), and myalgia (p=.043). Conclusions At universal screening for SARS-CoV-2, one-third of the population had a positive result, while those symptoms associated with a positive PCR were headache, dyspnea, and myalgia. [ABSTRACT FROM AUTHOR]

Published
2022
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4. Prevalence of Depression, Anxiety, and Perceived Stress in Postpartum Mexican Women during the COVID-19 Lockdown

Author

Suárez-Rico, Blanca Vianey, primary, Estrada-Gutierrez, Guadalupe, additional, Sánchez-Martínez, Maribel, additional, Perichart-Perera, Otilia, additional, Rodríguez-Hernández, Carolina, additional, González-Leyva, Carla, additional, Osorio-Valencia, Erika, additional, Cardona-Pérez, Arturo, additional, Helguera-Repetto, Addy Cecilia, additional, Espino y Sosa, Salvador, additional, Solis-Paredes, Mario, additional, and Reyes-Muñoz, Enrique, additional

Published
2021
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5. Clinical characteristics and risk factors for SARS-CoV-2 infection in pregnant women attending a third level reference center in Mexico City

Author

Hernández-Cruz, Rosa Gabriela, primary, Sánchez-Cobo, Daniela, additional, Acevedo-Gallegos, Sandra, additional, Helguera-Repetto, Addy Cecilia, additional, Rodriguez-Bosch, Mario Roberto, additional, Ramirez-Santes, Victor Hugo, additional, Villegas-Mota, Isabel, additional, Cardona-Pérez, Arturo, additional, Cortes-Bonilla, Manuel, additional, Irles, Claudine, additional, Mateu-Rogell, Paloma, additional, Villanueva-Calleja, Job, additional, Villavicencio Carrisoza, Oscar, additional, Estrada-Gutiérrez, Gaudalupe, additional, Espino-Y-Sosa, Salvador, additional, Torres-Torres, Johnatan, additional, and Martinez-Portilla, Raigam Jafet, additional

Published
2021
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6. Molecular Insights into the Thrombotic and Microvascular Injury in Placental Endothelium of Women with Mild or Severe COVID-19

Author

Flores-Pliego, Arturo, primary, Miranda, Jael, additional, Vega-Torreblanca, Sara, additional, Valdespino-Vázquez, Yolotzin, additional, Helguera-Repetto, Cecilia, additional, Espejel-Nuñez, Aurora, additional, Borboa-Olivares, Héctor, additional, Espino y Sosa, Salvador, additional, Mateu-Rogell, Paloma, additional, León-Juárez, Moisés, additional, Ramírez-Santes, Victor, additional, Cardona-Pérez, Arturo, additional, Villegas-Mota, Isabel, additional, Torres-Torres, Johnatan, additional, Juárez-Reyes, Ángeles, additional, Rizo-Pica, Thelma, additional, González, Rosa O., additional, González-Mariscal, Lorenza, additional, and Estrada-Gutierrez, Guadalupe, additional

Published
2021
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8. Key Clinical Factors Predicting Adipokine and Oxidative Stress Marker Concentrations among Normal, Overweight and Obese Pregnant Women Using Artificial Neural Networks

Author

Solis-Paredes, Mario, primary, Estrada-Gutierrez, Guadalupe, additional, Perichart-Perera, Otilia, additional, Montoya-Estrada, Araceli, additional, Guzmán-Huerta, Mario, additional, Borboa-Olivares, Héctor, additional, Bravo-Flores, Eyerahi, additional, Cardona-Pérez, Arturo, additional, Zaga-Clavellina, Veronica, additional, Garcia-Latorre, Ethel, additional, Gonzalez-Perez, Gabriela, additional, Hernández-Pérez, José, additional, and Irles, Claudine, additional

Published
2017
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9. Key Clinical Factors Predicting Adipokine and Oxidative Stress Marker Concentrations among Normal, Overweight and Obese Pregnant Women Using Artificial Neural Networks.

Author

Solis-Paredes, Mario, Estrada-Gutierrez, Guadalupe, Perichart-Perera, Otilia, Montoya-Estrada, Araceli, Guzmán-Huerta, Mario, Borboa-Olivares, Héctor, Bravo-Flores, Eyerahi, Cardona-Pérez, Arturo, Zaga-Clavellina, Veronica, Garcia-Latorre, Ethel, Gonzalez-Perez, Gabriela, Hernández-Pérez, José Alfredo, and Irles, Claudine

Subjects
ADIPOKINES, OXIDATIVE stress, OBESITY in women, PREGNANT women, ARTIFICIAL neural networks, BODY mass index, BODY weight, GESTATIONAL age
Abstract

Maternal obesity has been related to adverse neonatal outcomes and fetal programming. Oxidative stress and adipokines are potential biomarkers in such pregnancies; thus, the measurement of these molecules has been considered critical. Therefore, we developed artificial neural network (ANN) models based on maternal weight status and clinical data to predict reliable maternal blood concentrations of these biomarkers at the end of pregnancy. Adipokines (adiponectin, leptin, and resistin), and DNA, lipid and protein oxidative markers (8-oxo-2'-deoxyguanosine, malondialdehyde and carbonylated proteins, respectively) were assessed in blood of normal weight, overweight and obese women in the third trimester of pregnancy. A Back-propagation algorithm was used to train ANN models with four input variables (age, pre-gestational body mass index (p-BMI), weight status and gestational age). ANN models were able to accurately predict all biomarkers with regression coefficients greater than R² = 0.945. P-BMI was the most significant variable for estimating adiponectin and carbonylated proteins concentrations (37%), while gestational age was the most relevant variable to predict resistin and malondialdehyde (34%). Age, gestational age and p-BMI had the same significance for leptin values. Finally, for 8-oxo-2'-deoxyguanosine prediction, the most significant variable was age (37%). These models become relevant to improve clinical and nutrition interventions in prenatal care. [ABSTRACT FROM AUTHOR]

Published
2018
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