Literature DB >> 25656920

Evolution and prognosis of long intensive care unit stay patients suffering a deterioration: A multicenter study.

Alberto Hernández-Tejedor1, Lluís Cabré-Pericas2, María Cruz Martín-Delgado3, Ana María Leal-Micharet4, Alejandro Algora-Weber5.   

Abstract

PURPOSE: The prognosis of a patient who deteriorates during a prolonged intensive care unit (ICU) stay is difficult to predict. We analyze the prognostic value of the serialized Sequential Organ Failure Assessment (SOFA) score and other variables in the early days after a complication and to build a new predictive score.
MATERIALS AND METHODS: EPIPUSE (Evolución y pronóstico de los pacientes con ingreso prolongado en UCI que sufren un empeoramiento, Evolution and prognosis of long intensive care unit stay patients suffering a deterioration) study is a prospective, observational study during a 3-month recruitment period in 75 Spanish ICUs. We focused on patients admitted in the ICU for 7 days or more with complications of adverse events that involve organ dysfunction impairment. Demographics, clinical variables, and serialized SOFA after a supervening clinical deterioration were recorded. Univariate and multivariate analyses were performed, and a predictive model was created with the most discriminating variables.
RESULTS: We included 589 patients who experienced 777 cases of severe complication or adverse event. The entire sample was randomly divided into 2 subsamples, one for development purposes (528 cases) and the other for validation (249 cases). The predictive model maximizing specificity is calculated by minimum SOFA + 2 * cardiovascular risk factors + 2 * history of any oncologic disease or immunosuppressive treatment + 3 * dependence for basic activities of daily living. The area under the receiver operating characteristic curve is 0.82. A 14-point cutoff has a positive predictive value of 100% (92.7%-100%) and negative predictive value of 51% (46.4%-55.5%) for death.
CONCLUSIONS: EPIPUSE model can predict mortality with a specificity and positive predictive value of 99% in some groups of patients.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bioethics; Decision making; Life-sustaining treatment; Multiple organ dysfunction syndrome; Organ dysfunction scores

Mesh:

Substances:

Year:  2015        PMID: 25656920     DOI: 10.1016/j.jcrc.2015.01.011

Source DB:  PubMed          Journal:  J Crit Care        ISSN: 0883-9441            Impact factor:   3.425


  3 in total

1.  Limitation of life support techniques at admission to the intensive care unit: a multicenter prospective cohort study.

Authors:  Olga Rubio; Anna Arnau; Sílvia Cano; Carles Subirà; Begoña Balerdi; María Eugenía Perea; Miguel Fernández-Vivas; María Barber; Noemí Llamas; Susana Altaba; Ana Prieto; Vicente Gómez; Mar Martin; Marta Paz; Belen Quesada; Valentí Español; Juan Carlos Montejo; José Manuel Gomez; Gloria Miro; Judith Xirgú; Ana Ortega; Pedro Rascado; Juan María Sánchez; Alfredo Marcos; Ana Tizon; Pablo Monedero; Elisabeth Zabala; Cristina Murcia; Ines Torrejon; Kenneth Planas; José Manuel Añon; Gonzalo Hernandez; María-Del-Mar Fernandez; Consuelo Guía; Vanesa Arauzo; José Miguel Perez; Rosa Catalan; Javier Gonzalez; Rosa Poyo; Roser Tomas; Iñaki Saralegui; Jordi Mancebo; Charles Sprung; Rafael Fernández
Journal:  J Intensive Care       Date:  2018-04-13

2.  Effects of alprostadil combined with hyperbaric oxygen on hearing recovery and hemorheology in patients with sudden sensorineural hearing loss and analysis of related influencing factors.

Authors:  Tao Feng; Qinqin Zhang; Jiasha Wei; Xiao Wang; Yang Geng
Journal:  Exp Ther Med       Date:  2022-01-27       Impact factor: 2.447

Review 3.  State of the Art of Machine Learning-Enabled Clinical Decision Support in Intensive Care Units: Literature Review.

Authors:  Na Hong; Chun Liu; Jianwei Gao; Lin Han; Fengxiang Chang; Mengchun Gong; Longxiang Su
Journal:  JMIR Med Inform       Date:  2022-03-03
  3 in total

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