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A Comparative Analysis of Universal and Sentinel Surveillance Data for Coronavirus Disease 2019: Insights From Argentina, Chile, and Mexico (2020–2022)
(Oxford University Press (OUP), 2025-03-10)
Lidia Redondo-Bravo
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Kinda Zureick
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Carla Voto
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Xaviera Molina Avendaño
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Laura Flores-Cisneros
Scopus© Citations 2 5
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Cost-effectiveness of screening, decolonisation and isolation strategies for carbapenem-resistant Enterobacterales and methicillin-resistant Staphylococcus aureus infections in hospitals: a sex-stratified mathematical modelling study
(Elsevier BV, 2025-03)
Kasim Allel
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Patricia Garcia
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Anne Peters
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MUNITA SEPULVEDA, JOSE MANUEL
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Eduardo A. Undurraga
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Risk and impact of stroke across 38 countries and territories of the Americas from 1990 to 2021: a population-based trends analysis from the Global Burden of Disease Study 2021
(Elsevier BV, 2025-03)
Ramón Martinez
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MUÑOZ VENTURELLI, PAULA ANDREA
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Pedro Ordunez
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Felipe Fregni
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Carlos Abanto
Scopus© Citations 22 3
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Reducing global inequities in medical oxygen access: the Lancet Global Health Commission on medical oxygen security
(Elsevier BV, 2025-03)
Hamish R Graham
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Carina King
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Ahmed Ehsanur Rahman
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Freddy Eric Kitutu
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Leith Greenslade
Scopus© Citations 53 1
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Retrospective study on disparities in time-to-treatment by health insurance system in Chilean breast cancer patients
(Medwave Estudios Limitada, 2025-04-10)
ACEVEDO ROMO, JOHANNA PATRICIA
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Teresa Ip
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Lea Maureira
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Cesar Sanchez
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Claudia Osorio
Introduction Breast cancer is the most common malignancy in the Americas, and the second leading cause of cancer death. Disparities in the time to treatment can significantly impact patient outcomes and typically affect lower socioeconomic individuals and/or ethnic minorities. Our study sought to evaluate disparities in time to treatment at three health institutions in Chile according to their type of health insurance (public or private). Methods Our study analyzed a database of breast cancer patients diagnosed between 2017 and 2018. Analyses included descriptive statistics and a linear regression model that incorporated clinical and demographic variables. Additionally, using a proportional risks model, we analyzed the association between clinical variables and mortality. Results Public health insurance (National Health Fund, FONASA) was associated with longer time-to-treatment and extended treatment times versus private health insurance (Social Security Institutions, ISAPRE; p < 0.0001). As expected, a more advanced stage at diagnosis was associated with lower survival. Our proportional risks model found that age was a predictor of breast cancer mortality in stage II patients. Also, total treatment time significantly increased the risk of breast cancer mortality in stage I patients. Conversely, total treatment time did not affect mortality on stages II or III. Conclusions We found significant disparities in the time to treatment of Chilean breast cancer patients using FONASA versus private ISAPRE. FONASA patients experience delays in the initiation of treatment and longer total treatment times compared to their private insurance counterparts. Finally, longer time-to-treatment was associated with more advanced stages and increased mortality.
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Early high-sensitivity troponin elevation and short-term mortality in sepsis: a systematic review with meta-analysis
(Springer Science and Business Media LLC, 2025-02-14)
Abraham I. J. Gajardo
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Santiago Ferrière-Steinert
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Joaquín Valenzuela Jiménez
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Sebastián Heskia Araya
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Thomas Kouyoumdjian Carvajal
Abstract Background Serum cardiac troponin (cTn) elevation is a well-established phenomenon in sepsis. However, the clinical signifcance of this phenomenon with high-sensitivity (hs) assays and the current sepsis defnition needs to be settled. Research Question What is the association between early serum cTn levels measured by hs-assays and the risk of short-term mortality in septic patients? Study Design and Methods We conducted a systematic review using a comprehensive PubMed, Scopus, and Embase search. Studies were eligible if they reported association data on early hs-cTn and mortality in an adult sample with sepsis that met the Sepsis-3 defnition. For the synthesis of the efect of hs-cTn on mortality, we applied random efect models on the pooled unadjusted and adjusted odds ratio (OR and aOR, respectively) of elevated vs. normal hs-cTn serum values, and on the crude standardized mean diference (SMD) of hs-cTn between survivors and non-survivors. Results In total, 6242 patients from 17 studies were included, with short-term mortality rates ranging from 16.9% to 53.8%. Using a crude analysis, non-survivor patients showed higher hs-cTn than survivors (SMD of 0.87, 95%CI: 0.41–1.33). Elevated hs-cTn was associated with increased mortality (OR=1.78, 95% CI: 1.41–2.25). However, this prognostic efect was absent in studies that adjusted for diferent confounders (aOR=1.06, 95% CI: 0.99–1.14). Discussion and Conclusions Non-survivors of sepsis exhibited signifcantly elevated hs-cTn levels. While elevated hs-cTn levels are associated with an increased risk of mortality, they are not independently associated with this outcome in sepsis
1Scopus© Citations 19
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Machine learning-based identification of efficient and restrictive physiological subphenotypes in acute respiratory distress syndrome
(Springer Science and Business Media LLC, 2025-03-01)
Gabriela Meza-Fuentes
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DELGADO BECERRA, OROZIMBA IRIS
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Mario Barbé
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Ignacio Sánchez
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RETAMAL LUCERO, MAURICIO ANTONIO
Acute respiratory distress syndrome (ARDS) is a severe condition with high morbidity and mortality, characterized by significant clinical heterogeneity. This heterogeneity complicates treatment selection and patient inclusion in clinical trials. Therefore, the objective of this study is to identify physiological subphenotypes of ARDS using machine learning, and to determine ventilatory variables that can effectively discriminate between these subphenotypes in a bedside setting with high performance, highlighting potential utility for future clinical stratification approaches.</jats:p> Methodology A retrospective cohort study was conducted using data from our ICU, covering admissions from 2017 to 2021. The study included 224 patients over 18 years of age diagnosed with ARDS according to the Berlin criteria and undergoing invasive mechanical ventilation (IMV). Data on physiological and ventilatory variables were collected during the first 24 h IMV. We applied machine learning techniques to categorize subphenotypes in ARDS patients. Initially, we employed the unsupervised Gaussian Mixture Classification Model approach to group patients into subphenotypes. Subsequently, we applied supervised models such as XGBoost to perform root cause analysis, evaluate the classification of patients into these subgroups, and measure their performance.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Our models identified two ARDS subphenotypes with significant clinical differences and significant outcomes. Subphenotype Efficient (<jats:italic>n</jats:italic> = 172) was characterized by lower mortality, lower clinical severity and presented a less restrictive pattern with better gas exchange compared to Subphenotype Restrictive (<jats:italic>n</jats:italic> = 52), which showed the opposite. The models demonstrated high performance with an area under the ROC curve of 0.94, sensitivity of 94.2% and specificity of 87.5%, in addition to an F1 score of 0.85. The most influential variables in the discrimination of subphenotypes were distension pressure, respiratory frequency and exhaled carbon dioxide volume.Conclusion This study presents an approach to improve subphenotype categorization in ARDS. The generation of clustering and prediction models by machine learning involving clinical, ventilatory mechanics, and gas exchange variables allowed for more accurate stratification of patients. These findings have the potential to optimize individualized treatment selection and improve clinical outcomes in patients with ARDS.</jats:p> Graphical Abstract
Scopus© Citations 2 5
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Cáncer de vesícula: ¿Es momento de modificar el GES?
(SciELO Agencia Nacional de Investigacion y Desarrollo (ANID), 2024-10)
Camila P. Samaniego
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Xabier de Aretxabala
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Felipe Castillo
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Álvaro Paredes
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M. Trinidad González
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Guía de práctica clínica para el tratamiento de infecciones por bacilos Gram negativos del Comité Ampliado de Antimicrobianos de la Sociedad Chilena de Infectología
(SciELO Agencia Nacional de Investigacion y Desarrollo (ANID), 2024-10)
Daniela Pavez
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Catalina Gutiérrez
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Loreto Rojas
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Mirta Acuña
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Dona Benadof
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Concurrent nutrition and physical rehabilitation interventions for patients with critical illness
(Ovid Technologies (Wolters Kluwer Health), 2024-12-16)
GONZALEZ SEGUEL, FELIPE ANDRES
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Kirby P. Mayer
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Renee D. Stapleton
The effects of either physical rehabilitation or nutrition on outcomes in patients with critical illness are variable and remain unclear. The potential for the combination of exercise and nutritional delivered concurrently to provide benefit is provocative, but data are only emerging. Herein, we provide a summary of evidence from 2023 and 2024 on combined physical rehabilitation and nutrition during and following critical illness. Recent findings While latest trials on physical rehabilitation alone reported conflicting findings, recent nutrition trials found no difference between higher and lower protein delivery and even suggested harm in patients with acute kidney injury. In 2023 and 2024, we identified four studies (one randomized controlled trial) combining physical rehabilitation and nutrition (mainly protein supplementation) within the ICU setting. Overall, these suggested benefits, including reduction of muscle size loss, ICU acquired weakness, delirium, and improved mobility levels, although these benefits did not extend to mortality and hospital length of stay. No recent trials combining physical rehabilitation and nutrition for patients after ICU were identified.</jats:p>
Scopus© Citations 6 1

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