Your browser doesn't support javascript.
loading
Predict Score: A New Biological and Clinical Tool to Help Predict Risk of Intensive Care Transfer for COVID-19 Patients.
Gette, Mickael; Fernandes, Sara; Marlinge, Marion; Duranjou, Marine; Adi, Wijayanto; Dambo, Maelle; Simeone, Pierre; Michelet, Pierre; Bruder, Nicolas; Guieu, Regis; Fromonot, Julien.
Afiliación
  • Gette M; Laboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
  • Fernandes S; Center for Research and Studies on Health Services and Quality of Life, Aix-Marseille University, 13005 Marseille, France.
  • Marlinge M; Laboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
  • Duranjou M; INSERM, INRAE, C2VN, Aix-Marseille University, 13005 Marseille, France.
  • Adi W; Laboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
  • Dambo M; Laboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
  • Simeone P; Laboratory of Biochemistry, Timone University Hospital, APHM, 13005 Marseille, France.
  • Michelet P; Department of Anesthesiology and Intensive Care, Timone University Hospital, Aix Marseille University APHM, 13005 Marseille, France.
  • Bruder N; INSERM, INRAE, C2VN, Aix-Marseille University, 13005 Marseille, France.
  • Guieu R; Department of Emergency Medicine and Intensive Care, Timone University Hospital, APHM, 13005 Marseille, France.
  • Fromonot J; Department of Anesthesiology and Intensive Care, Timone University Hospital, Aix Marseille University APHM, 13005 Marseille, France.
Biomedicines ; 9(5)2021 May 18.
Article en En | MEDLINE | ID: mdl-34070021
BACKGROUND: The COVID-19 crisis has strained world health care systems. This study aimed to develop an innovative prediction score using clinical and biological parameters (PREDICT score) to anticipate the need of intensive care of COVID-19 patients already hospitalized in standard medical units. METHODS: PREDICT score was based on a training cohort and a validation cohort retrospectively recruited in 2020 in the Marseille University Hospital. Multivariate analyses were performed, including clinical, and biological parameters, comparing a baseline group composed of COVID-19 patients exclusively treated in standard medical units to COVID-19 patients that needed intensive care during their hospitalization. RESULTS: Independent variables included in the PREDICT score were: age, Body Mass Index, Respiratory Rate, oxygen saturation, C-reactive protein, neutrophil-lymphocyte ratio and lactate dehydrogenase. The PREDICT score was able to correctly identify more than 83% of patients that needed intensive care after at least 1 day of standard medical hospitalization. CONCLUSIONS: The PREDICT score is a powerful tool for anticipating the intensive care need for COVID-19 patients already hospitalized in a standard medical unit. It shows limitations for patients who immediately need intensive care, but it draws attention to patients who have an important risk of needing intensive care after at least one day of hospitalization.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Biomedicines Año: 2021 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Biomedicines Año: 2021 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Suiza