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Identification of acute respiratory distress syndrome subphenotypes de novo using routine clinical data: a retrospective analysis of ARDS clinical trials.
Duggal, Abhijit; Kast, Rachel; Van Ark, Emily; Bulgarelli, Lucas; Siuba, Matthew T; Osborn, Jeff; Rey, Diego Ariel; Zampieri, Fernando G; Cavalcanti, Alexandre Biasi; Maia, Israel; Paisani, Denise M; Laranjeira, Ligia N; Serpa Neto, Ary; Deliberato, Rodrigo Octávio.
Afiliación
  • Duggal A; Department of Critical Care Medicine, Cleveland Clinic, Cleveland, Ohio, USA duggala2@ccf.org.
  • Kast R; Department of Clinical Data Science, Endpoint Health, Palo Alto, California, USA.
  • Van Ark E; Department of Clinical Data Science, Endpoint Health, Palo Alto, California, USA.
  • Bulgarelli L; Department of Clinical Data Science, Endpoint Health, Palo Alto, California, USA.
  • Siuba MT; Department of Critical Care Medicine, Cleveland Clinic, Cleveland, Ohio, USA.
  • Osborn J; Department of Clinical Data Science, Endpoint Health, Palo Alto, California, USA.
  • Rey DA; Department of Clinical Data Science, Endpoint Health, Palo Alto, California, USA.
  • Zampieri FG; HCor Research Institute, Sao Paulo, Brazil.
  • Cavalcanti AB; HCor Research Institute, Sao Paulo, Brazil.
  • Maia I; Hospital do Coracao, Sao Paulo, São Paulo, Brazil.
  • Paisani DM; HCor Research Institute, Sao Paulo, Brazil.
  • Laranjeira LN; HCor Research Institute, Sao Paulo, Brazil.
  • Serpa Neto A; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria, Australia.
  • Deliberato RO; Critical Care Medicine, Hospital Israelita Albert Einstein, Sao Paulo, Brazil.
BMJ Open ; 12(1): e053297, 2022 Jan 06.
Article en En | MEDLINE | ID: mdl-34992112
OBJECTIVES: The acute respiratory distress syndrome (ARDS) is a heterogeneous condition, and identification of subphenotypes may help in better risk stratification. Our study objective is to identify ARDS subphenotypes using new simpler methodology and readily available clinical variables. SETTING: This is a retrospective Cohort Study of ARDS trials. Data from the US ARDSNet trials and from the international ART trial. PARTICIPANTS: 3763 patients from ARDSNet data sets and 1010 patients from the ART data set. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was 60-day or 28-day mortality, depending on what was reported in the original trial. K-means cluster analysis was performed to identify subgroups. Sets of candidate variables were tested to assess their ability to produce different probabilities for mortality in each cluster. Clusters were compared with biomarker data, allowing identification of subphenotypes. RESULTS: Data from 4773 patients were analysed. Two subphenotypes (A and B) resulted in optimal separation in the final model, which included nine routinely collected clinical variables, namely heart rate, mean arterial pressure, respiratory rate, bilirubin, bicarbonate, creatinine, PaO2, arterial pH and FiO2. Participants in subphenotype B showed increased levels of proinflammatory markers, had consistently higher mortality, lower number of ventilator-free days at day 28 and longer duration of ventilation compared with patients in the subphenotype A. CONCLUSIONS: Routinely available clinical data can successfully identify two distinct subphenotypes in adult ARDS patients. This work may facilitate implementation of precision therapy in ARDS clinical trials.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Síndrome de Dificultad Respiratoria Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: BMJ Open Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Síndrome de Dificultad Respiratoria Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Humans Idioma: En Revista: BMJ Open Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido