GUILLERMO
MUÑIZ ALBAICETA
Profesor Titular de Universidad
Hospital Universitario Pío del Río Hortega
Valladolid, EspañaPublications en collaboration avec des chercheurs de Hospital Universitario Pío del Río Hortega (13)
2024
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Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
Critical Care, Vol. 28, Núm. 1
2023
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A second update on mapping the human genetic architecture of COVID-19
Nature
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Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic: a matched analysis
The European respiratory journal, Vol. 61, Núm. 3
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Key Factors Associated With Pulmonary Sequelae in the Follow-Up of Critically Ill COVID-19 Patients
Archivos de Bronconeumologia, Vol. 59, Núm. 4, pp. 205-215
2022
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ICU-Acquired Pneumonia Is Associated with Poor Health Post-COVID-19 Syndrome
Journal of Clinical Medicine, Vol. 11, Núm. 1
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Major candidate variables to guide personalised treatment with steroids in critically ill patients with COVID-19: CIBERESUCICOVID study
Intensive Care Medicine, Vol. 48, Núm. 7, pp. 850-864
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Methodology of a Large Multicenter Observational Study of Patients with COVID-19 in Spanish Intensive Care Units
Archivos de Bronconeumologia, Vol. 58, pp. 22-31
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Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study
The Lancet Regional Health - Europe, Vol. 18
2021
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Pressure injury prediction models for critically-ill patients should consider both the case-mix and local factors
Intensive and Critical Care Nursing
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Pulmonary Function and Radiologic Features in Survivors of Critical COVID-19: A 3-Month Prospective Cohort
Chest, Vol. 160, Núm. 1, pp. 187-198
2018
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Immunocompromised patients with acute respiratory distress syndrome: Secondary analysis of the LUNG SAFE database
Critical Care, Vol. 22, Núm. 1
2015
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Common variants of NFE2L2 gene predisposes to acute respiratory distress syndrome in patients with severe sepsis
Critical Care, Vol. 19, Núm. 1
2009
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Predicting the probability of survival in intensive care unit patients from a small number of variables and training examples
Artificial Intelligence in Medicine, Vol. 45, Núm. 1, pp. 63-76