Literature DB >> 31447916

Using a CriSTAL scoring system to identify pre-morbid conditions associated with a poor outcome after admission to intensive care in people 70 years or older.

K Jankowski1, D C Bryden2.   

Abstract

Older people admitted to intensive care are considered to have lower physiological reserves, an increased susceptibility to infection and longer recovery times, resulting in generally poorer outcomes after intensive care treatment. However, biological heterogeneity makes identification of those with the best chances of survival within their group difficult and risks subjecting those at the end of their lives to unsuccessful treatments. There is no fit-for-purpose outcome prediction tool capable of identifying patients most at risk of these poor outcomes at the point of admission to intensive care. This retrospective study sought to identify factors associated with mortality in older patients (≥70 years) admitted to a teaching hospital critical care unit using objective variables readily available at the point of admission. A total of 15 variables were tested for a significant association with mortality. Of these, eight were identified as significant variables (myocardial infarction within 6 months, an abnormal ECG, congestive cardiac failure (NYHA ≥2), chronic pulmonary disease, chronic liver disease, metastatic cancer, a stay in hospital ≥5 days preceding ICU admission, and frailty (Clinical Frailty Score ≥4)). These variables were used from the basis of a novel outcome prediction model. The aim of such a model would be that it could be used at the point of referral to intensive care to inform considerations regarding admission, and to facilitate conversations with the patient and family regarding realistic treatment expectations.

Entities:  

Keywords:  Mortality; admission; elderly; intensive care

Year:  2018        PMID: 31447916      PMCID: PMC6693104          DOI: 10.1177/1751143718804678

Source DB:  PubMed          Journal:  J Intensive Care Soc        ISSN: 1751-1437


  24 in total

Review 1.  Quality of life in adult survivors of critical illness: a systematic review of the literature.

Authors:  David W Dowdy; Mark P Eid; Artyom Sedrakyan; Pedro A Mendez-Tellez; Peter J Pronovost; Margaret S Herridge; Dale M Needham
Journal:  Intensive Care Med       Date:  2005-04-01       Impact factor: 17.440

2.  Variation in ICU risk-adjusted mortality: impact of methods of assessment and potential confounders.

Authors:  Michael W Kuzniewicz; Eduard E Vasilevskis; Rondall Lane; Mitzi L Dean; Nisha G Trivedi; Deborah J Rennie; Ted Clay; Pamela L Kotler; R Adams Dudley
Journal:  Chest       Date:  2008-04-10       Impact factor: 9.410

3.  Treatment intensity and outcome of patients aged 80 and older in intensive care units: a multicenter matched-cohort study.

Authors:  Ariane Boumendil; Philippe Aegerter; Bertrand Guidet
Journal:  J Am Geriatr Soc       Date:  2005-01       Impact factor: 5.562

4.  A global clinical measure of fitness and frailty in elderly people.

Authors:  Kenneth Rockwood; Xiaowei Song; Chris MacKnight; Howard Bergman; David B Hogan; Ian McDowell; Arnold Mitnitski
Journal:  CMAJ       Date:  2005-08-30       Impact factor: 8.262

5.  Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today's critically ill patients.

Authors:  Jack E Zimmerman; Andrew A Kramer; Douglas S McNair; Fern M Malila
Journal:  Crit Care Med       Date:  2006-05       Impact factor: 7.598

6.  A prognostic model for 1-year mortality in older adults after hospital discharge.

Authors:  Stacie K Levine; Greg A Sachs; Lei Jin; David Meltzer
Journal:  Am J Med       Date:  2007-05       Impact factor: 4.965

7.  Critically ill old and the oldest-old patients in intensive care: short- and long-term outcomes.

Authors:  Dominique Somme; Jean-Michel Maillet; Mathilde Gisselbrecht; Ana Novara; Catherine Ract; Jean-Yves Fagon
Journal:  Intensive Care Med       Date:  2003-11-12       Impact factor: 17.440

8.  SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission.

Authors:  Rui P Moreno; Philipp G H Metnitz; Eduardo Almeida; Barbara Jordan; Peter Bauer; Ricardo Abizanda Campos; Gaetano Iapichino; David Edbrooke; Maurizia Capuzzo; Jean-Roger Le Gall
Journal:  Intensive Care Med       Date:  2005-08-17       Impact factor: 17.440

9.  Very old patients admitted to intensive care in Australia and New Zealand: a multi-centre cohort analysis.

Authors:  Sean M Bagshaw; Steve A R Webb; Anthony Delaney; Carol George; David Pilcher; Graeme K Hart; Rinaldo Bellomo
Journal:  Crit Care       Date:  2009-04-01       Impact factor: 9.097

10.  Identification of high-risk subgroups in very elderly intensive care unit patients.

Authors:  Sophia E de Rooij; Ameen Abu-Hanna; Marcel Levi; Evert de Jonge
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

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