Browsing by Author "Valderrama Aguirre, Augusto"
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Item Dependence on mobile devices among health science university students: a cross-sectional analytical study(World Institute for Engineering and Technology Education, 2022) Giraldo Jiménez, Claudia F.; Campo Bermúdez, Ingry Y.; Muñoz Hoyos, Mónica; Quintero Puentes, Isabella; Botero Carvajal, Alejandro; Valderrama Aguirre, Augusto; Millán Estupiñan, Juan C.BACKGROUND: The aim of this study was to determine the factors associated with in-hospital mortality after a coronary artery bypass (CABG) in a high-complexity clinic in the city of Santiago de Cali, Colombia. METHODS: A retrospective case-control analytical study was performed. Cases were defined as adult patients that had undergone CABG and died within 30 days of the surgery. Patients aged ≥18 years that had undergone isolated surgeries were included, i.e. procedures without other interventions combined. Patients were excluded from this study if: 1) they had missing data in their medical records; 2) they had previously been in a state of coma; or 3) they had previously undergone cardiac surgery other than a bypass procedure. Exposure variables were measured at three stages: preoperative, intraoperative, and postoperative. RESULTS: The study included 77 cases and 308 controls. The most common cause of death was cardiogenic shock (53.2%), followed by sepsis (27.3%). The multinomial logistic regression model revealed an association of in-hospital mortality with preoperative variables of age >75 years (odds ratio [OR] 2.5, 95% confidence interval [95% CI]: 1.1-5.8, P=0.032), low socioeconomic status (OR=2.3, 95% CI: 1.1-5.2, P=0.034), heart failure (HF) (OR=3.2, 95% CI: 1.5-7.0, P=0.002), unstable angina (OR=4.2, 95% CI: 1.9-9.0, P=0.000), acute myocardial infarction (AMI)≤7 days (OR=3.9, 95% CI: 1.1-13.7, P=0.037), chronic kidney insufficiency (CKI) (OR=2.9, 95% CI: 1.2-7.0, P=0.018), peripheral vascular disease (PVD) (OR=2.8, 95% CI: 1.2-6.8, P=0.019), and urgent/emergent surgery (OR=8.2, 95% CI: 2.0-34.5, P=0.004). Of the intraoperative variables, the model showed an association between the use of inotropic agents (OR=2.8, 95% CI: 1.3-6.4, P=0.011) and cardiogenic shock (OR=50.6, 95% CI: 7.5-339, P=0.000). CONCLUSIONS: This study identifies the factors during preoperative and intraoperative periods that are associated with in-hospital mortality in patients that have undergone CABG.Item Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields(2021-12) Medina Cordoba, Luz K; Chande, Aroon T.; Rishishwar, Lavanya; Mayer, Leonard W; Valderrama Aguirre, Lina C; Valderrama Aguirre, Augusto; Gaby, John Christian; Kostka, Joel E.; Jordan, I. KingPrevious studies have shown the sugarcane microbiome harbors diverse plant growth promoting microorganisms, including nitrogen-fixing bacteria (diazotrophs), which can serve as biofertilizers. The genomes of 22 diazotrophs from Colombian sugarcane fields were sequenced to investigate potential biofertilizers. A genome-enabled computational phenotyping approach was developed to prioritize sugarcane associated diazotrophs according to their potential as biofertilizers. This method selects isolates that have potential for nitrogen fixation and other plant growth promoting (PGP) phenotypes while showing low risk for virulence and antibiotic resistance. Intact nitrogenase (nif) genes and operons were found in 18 of the isolates. Isolates also encode phosphate solubilization and siderophore production operons, and other PGP genes. The majority of sugarcane isolates showed uniformly low predicted virulence and antibiotic resistance compared to clinical isolates. Six strains with the highest overall genotype scores were experimentally evaluated for nitrogen fixation, phosphate solubilization, and the production of siderophores, gibberellic acid, and indole acetic acid. Results from the biochemical assays were consistent and validated computational phenotype predictions. A genotypic and phenotypic threshold was observed that separated strains by their potential for PGP versus predicted pathogenicity. Our results indicate that computational phenotyping is a promising tool for the assessment of bacteria detected in agricultural ecosystems