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Cumulative Prognostic Score Predicting Mortality in Patients Older Than 80 Years Admitted to the ICU.
de Lange, Dylan W; Brinkman, Sylvia; Flaatten, Hans; Boumendil, Ariane; Morandi, Alessandro; Andersen, Finn H; Artigas, Antonio; Bertolini, Guido; Cecconi, Maurizio; Christensen, Steffen; Faraldi, Loredana; Fjølner, Jesper; Jung, Christian; Marsh, Brian; Moreno, Rui; Oeyen, Sandra; Öhman, Christina Agvald; Bollen Pinto, Bernardo; de Smet, Anne Marie G A; Soliman, Ivo W; Szczeklik, Wojciech; Valentin, Andreas; Watson, Ximena; Zafeiridis, Tilemachos; Guidet, Bertrand.
Afiliação
  • de Lange DW; Department of Intensive Care Medicine, University Medical Center, University Utrecht, Utrecht, The Netherlands.
  • Brinkman S; Department of Medical Informatics, Amsterdam Public Health Research Institute, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
  • Flaatten H; Department of Clinical Medicine, University of Bergen, Bergen, Norway.
  • Boumendil A; Department of Anaesthesia and Intensive Care, Haukeland University Hospital, Bergen, Norway.
  • Morandi A; Assistance Publique - Hôpitaux de Paris, Hôpital Saint-Antoine, Service de Réanimation Médicale, Paris, France.
  • Andersen FH; Department of Rehabilitation, Hospital Ancelle di Cremona, Cremona, Italy.
  • Artigas A; Geriatric Research Group, Brescia, Italy.
  • Bertolini G; Department of Anaesthesia and Intensive Care, Ålesund Hospital, Ålesund, Norway.
  • Cecconi M; Department of Circulation and Medical Imaging, NTNU, Trondheim, Norway.
  • Christensen S; Department of Intensive Care Medecine, CIBER Enfermedades Respiratorias, Corporacion Sanitaria Universitaria Parc Tauli, Autonomous University of Barcelona, Sabadell, Spain.
  • Faraldi L; Laboratorio di Epidemiologia Clinica, Centro di Coordinamento GiViTI Dipartimento di Salute Pubblica, IRCCS - Istituto di Ricerche Farmacologiche "Mario Negri", Ranica (Bergamo), Italy.
  • Fjølner J; St George's University Hospital, London, United Kingdom.
  • Jung C; Department of Anaesthesia and Intensive Care Medicine, Aarhus University Hospital, Denmark.
  • Marsh B; ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy.
  • Moreno R; Department of Anaesthesia and Intensive Care Medicine, Aarhus University Hospital, Denmark.
  • Oeyen S; Department of Cardiology, Pulmonology and Angiology, University Hospital, Düsseldorf, Germany.
  • Öhman CA; Mater Misericordiae University Hospital, Dublin, Ireland.
  • Bollen Pinto B; Unidade de Cuidados Intensivos Neurocriticos e Trauma, Hospital de São José, Centro Hospitalar Universitário de Lisboa Central Nova Medical School, Lisbon, Portugal.
  • de Smet AMGA; Department of Intensive Care 1K12IC, Ghent University Hospital, Ghent, Belgium.
  • Soliman IW; Karolinska University Hospital, Stockholm, Sweden.
  • Szczeklik W; Geneva University Hospitals, Geneva, Switzerland.
  • Valentin A; Department of Critical Care, University Medical Center Groningen, University Groningen, Groningen, The Netherlands.
  • Watson X; Department of Intensive Care Medicine, University Medical Center, University Utrecht, Utrecht, The Netherlands.
  • Zafeiridis T; Intensive Care and Perioperative Medicine Division, Jagiellonian University Medical College, Kraków, Poland.
  • Guidet B; Kardinal Schwarzenberg Hospital, Schwarzach, Austria.
J Am Geriatr Soc ; 67(6): 1263-1267, 2019 06.
Article em En | MEDLINE | ID: mdl-30977911
OBJECTIVES: To develop a scoring system model that predicts mortality within 30 days of admission of patients older than 80 years admitted to intensive care units (ICUs). DESIGN: Prospective cohort study. SETTING: A total of 306 ICUs from 24 European countries. PARTICIPANTS: Older adults admitted to European ICUs (N = 3730; median age = 84 years [interquartile range = 81-87 y]; 51.8% male). MEASUREMENTS: Overall, 24 variables available during ICU admission were included as potential predictive variables. Multivariable logistic regression was used to identify independent predictors of 30-day mortality. Model sensitivity, specificity, and accuracy were evaluated with receiver operating characteristic curves. RESULTS: The 30-day-mortality was 1562 (41.9%). In multivariable analysis, these variables were selected as independent predictors of mortality: age, sex, ICU admission diagnosis, Clinical Frailty Scale, Sequential Organ Failure Score, invasive mechanical ventilation, and renal replacement therapy. The discrimination, accuracy, and calibration of the model were good: the area under the curve for a score of 10 or higher was .80, and the Brier score was .18. At a cut point of 10 or higher (75% of all patients), the model predicts 30-day mortality in 91.1% of all patients who die. CONCLUSION: A predictive model of cumulative events predicts 30-day mortality in patients older than 80 years admitted to ICUs. Future studies should include other potential predictor variables including functional status, presence of advance care plans, and assessment of each patient's decision-making capacity.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prognóstico / Mortalidade Hospitalar / Escores de Disfunção Orgânica Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prognóstico / Mortalidade Hospitalar / Escores de Disfunção Orgânica Idioma: En Ano de publicação: 2019 Tipo de documento: Article