Literature DB >> 10786960

Susceptibility to critical illness: reserve, response and therapy.

J F Bion1.   

Abstract

Risk of critical illness is determined both by genetic and environmental influences, particularly those relating to infectious and cardiovascular diseases. Physiologically-based scoring systems cannot measure prior risk because they do not quantify physiological reserve independently of the acute illness. Genetic profiling could be useful for risk assessment. Early detection of critical illness involves identifying physiological 'triggers' for referral; this requires the education of nursing and medical staff in their significance. Analysis of the relationship between risk factors and interventions may need complex modelling techniques. Therapeutic strategies depend on the nature of the underlying problem: the most useful are likely to be those which enhance tissue oxygen delivery and resistance to infection.

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Year:  2000        PMID: 10786960     DOI: 10.1007/s001340051120

Source DB:  PubMed          Journal:  Intensive Care Med        ISSN: 0342-4642            Impact factor:   17.440


  11 in total

1.  Association of impaired functional status at hospital discharge and subsequent rehospitalization.

Authors:  Erik H Hoyer; Dale M Needham; Levan Atanelov; Brenda Knox; Michael Friedman; Daniel J Brotman
Journal:  J Hosp Med       Date:  2014-02-26       Impact factor: 2.960

2.  Dynamic data during hypotensive episode improves mortality predictions among patients with sepsis and hypotension.

Authors:  Louis Mayaud; Peggy S Lai; Gari D Clifford; Lionel Tarassenko; Leo Anthony Celi; Djillali Annane
Journal:  Crit Care Med       Date:  2013-04       Impact factor: 7.598

3.  Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients.

Authors:  Sabina Hunziker; Leo A Celi; Joon Lee; Michael D Howell
Journal:  Crit Care       Date:  2012-05-18       Impact factor: 9.097

4.  Red cell distribution width is associated with presence, stage, and grade in patients with renal cell carcinoma.

Authors:  Fang-Ming Wang; Gongjun Xu; Yan Zhang; Lu-Lin Ma
Journal:  Dis Markers       Date:  2014-12-16       Impact factor: 3.434

5.  The Predictive Role of Red Cell Distribution Width in Mortality among Chronic Kidney Disease Patients.

Authors:  Yao-Peng Hsieh; Chia-Chu Chang; Chew-Teng Kor; Yu Yang; Yao-Ko Wen; Ping-Fang Chiu
Journal:  PLoS One       Date:  2016-12-01       Impact factor: 3.240

6.  The Role of Red Cell Distribution Width as a Predictor of Mortality for Critically Ill Patients in an Inner-city Hospital.

Authors:  Syed Atif Safdar; Tejas Modi; Lakshmi Durga Sriramulu; Hamid Shaaban; Raymund Sison; Varun Modi; Marc Adelman; Gunwant Guron
Journal:  J Nat Sci Biol Med       Date:  2017 Jul-Dec

7.  Red cell distribution width as a predictor of multiple organ dysfunction syndrome in patients undergoing heart valve surgery.

Authors:  Piotr Duchnowski; Tomasz Hryniewiecki; Mariusz Kuśmierczyk; Piotr Szymanski
Journal:  Biol Open       Date:  2018-10-16       Impact factor: 2.422

8.  Red cell distribution width and early mortality in elderly patients with severe sepsis and septic shock.

Authors:  Sejin Kim; Kyoungmi Lee; Inbyung Kim; Siyoung Jung; Moon-Jung Kim
Journal:  Clin Exp Emerg Med       Date:  2015-09-30

9.  Biological pathways underlying the association of red cell distribution width and adverse clinical outcome: Results of a prospective cohort study.

Authors:  Giedre Zurauskaite; Marc Meier; Alaadin Voegeli; Daniel Koch; Sebastian Haubitz; Alexander Kutz; Luca Bernasconi; Andreas Huber; Mario Bargetzi; Beat Mueller; Philipp Schuetz
Journal:  PLoS One       Date:  2018-01-17       Impact factor: 3.240

10.  Usefulness of FRAIL Scale in Heart Valve Diseases.

Authors:  Piotr Duchnowski; Piotr Szymański; Mariusz Kuśmierczyk; Tomasz Hryniewiecki
Journal:  Clin Interv Aging       Date:  2020-07-09       Impact factor: 4.458

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