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Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain.
Rodríguez, Alejandro; Ruiz-Botella, Manuel; Martín-Loeches, Ignacio; Jimenez Herrera, María; Solé-Violan, Jordi; Gómez, Josep; Bodí, María; Trefler, Sandra; Papiol, Elisabeth; Díaz, Emili; Suberviola, Borja; Vallverdu, Montserrat; Mayor-Vázquez, Eric; Albaya Moreno, Antonio; Canabal Berlanga, Alfonso; Sánchez, Miguel; Del Valle Ortíz, María; Ballesteros, Juan Carlos; Martín Iglesias, Lorena; Marín-Corral, Judith; López Ramos, Esther; Hidalgo Valverde, Virginia; Vidaur Tello, Loreto Vidaur; Sancho Chinesta, Susana; Gonzáles de Molina, Francisco Javier; Herrero García, Sandra; Sena Pérez, Carmen Carolina; Pozo Laderas, Juan Carlos; Rodríguez García, Raquel; Estella, Angel; Ferrer, Ricard.
  • Rodríguez A; ICU Hospital Universitario Joan XXIII/IISPV/URV, Mallafre Guasch 4, 43007, Tarragona, Spain. ahr1161@yahoo.es.
  • Ruiz-Botella M; CIBERESUCICOVID, Barcelona, Spain. ahr1161@yahoo.es.
  • Martín-Loeches I; Tarragona Health Data Research Working Group (THeDaR), ICU Hospital Universitario Joan XXIII, Tarragona, Spain.
  • Jimenez Herrera M; Department of Intensive Care Medicine, Multidisciplinary Intensive Care Research Organization (MICRO), St. James's Hospital, Dublin, Ireland.
  • Solé-Violan J; Dean Nursing Faculty, Universitat Rovira i Virgili, Tarragona, Spain.
  • Gómez J; ICU Hospital Universitario Dr. Negrín, Las Palmas de Gran Canaria, Spain.
  • Bodí M; Tarragona Health Data Research Working Group (THeDaR), ICU Hospital Universitario Joan XXIII, Tarragona, Spain.
  • Trefler S; ICU Hospital Universitario Joan XXIII/IISPV/URV, Mallafre Guasch 4, 43007, Tarragona, Spain.
  • Papiol E; CIBERESUCICOVID, Barcelona, Spain.
  • Díaz E; ICU Hospital Universitario Joan XXIII/IISPV/URV, Mallafre Guasch 4, 43007, Tarragona, Spain.
  • Suberviola B; ICU Hospital Universitario Vall d'Hebron, Barcelona, Spain.
  • Vallverdu M; ICU Hospital Parc Tauli, Sabadell, Spain.
  • Mayor-Vázquez E; ICU Hospital Marqués de Valdecilla, Santander, Spain.
  • Albaya Moreno A; ICU Hospital Universitario Arnau de Vilanova, Lleida, Spain.
  • Canabal Berlanga A; ICU Hospital Verge de la Cinta, Tortosa, Spain.
  • Sánchez M; ICU Hospital Universitario de Guadalajara, Guadalajara, Spain.
  • Del Valle Ortíz M; ICU Hospital de La Princesa, Madrid, Spain.
  • Ballesteros JC; ICU Hospital Clinico San Carlos, Madrid, Spain.
  • Martín Iglesias L; ICU Hospital Universitario de Burgos, Burgos, Spain.
  • Marín-Corral J; ICU Hospital Clínico de Salamanca, Salamanca, Spain.
  • López Ramos E; ICU Hospital Universitario Central de Asturias, Oviedo, Spain.
  • Hidalgo Valverde V; ICU Hospital del Mar, Barcelona, Spain.
  • Vidaur Tello LV; ICU Hospital Príncipe de Asturias, Alcalá de Henares, Spain.
  • Sancho Chinesta S; ICU Hospital Complejo Asistencial de Segovia, Segovia, Spain.
  • Gonzáles de Molina FJ; ICU Hospital Universitario de Donostia, Donosia, Spain.
  • Herrero García S; ICU Hospital Universitario y Politécnico La Fe, Valencia, Spain.
  • Sena Pérez CC; ICU Hospital Universitario de Terrasa, Terrasa, Spain.
  • Pozo Laderas JC; ICU Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain.
  • Rodríguez García R; ICU Hospital Nuestra Señora del Prado, Talavera de la Reina, Spain.
  • Estella A; ICU Hospital Universitario Reina Sofía, Córdoba, Spain.
  • Ferrer R; ICU Complejo Hospitalario Universitario a Coruña, A Coruña, Spain.
Crit Care ; 25(1): 63, 2021 02 15.
Article in English | MEDLINE | ID: covidwho-1085162
ABSTRACT

BACKGROUND:

The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes.

METHODS:

Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 ICUs in Spain. The objective was to utilize an unsupervised clustering analysis to derive clinical COVID-19 phenotypes and to analyze patient's factors associated with mortality risk. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves.

RESULTS:

The database included a total of 2022 patients (mean age 64 [IQR 5-71] years, 1423 (70.4%) male, median APACHE II score (13 [IQR 10-17]) and SOFA score (5 [IQR 3-7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the A (mild) phenotype (537; 26.7%) included older age (< 65 years), fewer abnormal laboratory values and less development of complications, B (moderate) phenotype (623, 30.8%) had similar characteristics of A phenotype but were more likely to present shock. The C (severe) phenotype was the most common (857; 42.5%) and was characterized by the interplay of older age (> 65 years), high severity of illness and a higher likelihood of development shock. Crude ICU mortality was 20.3%, 25% and 45.4% for A, B and C phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications.

CONCLUSION:

The presented machine learning model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a "one-size-fits-all" model in practice.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: Europa Language: English Journal: Crit Care Year: 2021 Document Type: Article Affiliation country: S13054-021-03487-8

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: Europa Language: English Journal: Crit Care Year: 2021 Document Type: Article Affiliation country: S13054-021-03487-8