BACKGROUND AND AIMS: Unplanned admission to an intensive care unit (ICU) is associated with high mortality, having the highest incidence among patients who are emergency admissions to the hospital. This study was designed to identify factors associated with unplanned ICU admission in emergency admissions to hospital and develop an absolute risk tool to individualise the risk of an event during a hospital stay. METHODS: Emergency department (ED) and in-patient hospital data from a large teaching hospital of consecutive admissions from 1 January 1997 to 31 December 2007 aged over 14 years was included in this study. Patient data extracted from 126826 emergency presentations admitted as in-patients consisted of demographic and clinical variables. RESULTS: During an 11-year period 1582 incident unplanned ICU admissions occurred. Predictors of unplanned ICU admission included older age, being male, having a higher acuity triage category and a history of co-morbid conditions. Emergency department diagnostic groups associated with higher incidence of unplanned ICU admission included: sepsis, acute renal failure, lymphatic-hematopoietic tissue neoplasms, pneumonia, chronic-airways disease and bowel obstruction. The final model used to develop the nomogram had an ROC curve AUC of 0.7. CONCLUSION: This study identified factors associated with unplanned ICU admission and developed a nomogram to individualise risk prior to a patient being transferred from the ED. This nomogram provides clinicians the opportunity prior to transfer from the ED, to either (1) review the appropriateness of the ward level of planned transfer or (2) flag patients for follow-up on the general ward to assess for deterioration.
BACKGROUND AND AIMS: Unplanned admission to an intensive care unit (ICU) is associated with high mortality, having the highest incidence among patients who are emergency admissions to the hospital. This study was designed to identify factors associated with unplanned ICU admission in emergency admissions to hospital and develop an absolute risk tool to individualise the risk of an event during a hospital stay. METHODS: Emergency department (ED) and in-patient hospital data from a large teaching hospital of consecutive admissions from 1 January 1997 to 31 December 2007 aged over 14 years was included in this study. Patient data extracted from 126826 emergency presentations admitted as in-patients consisted of demographic and clinical variables. RESULTS: During an 11-year period 1582 incident unplanned ICU admissions occurred. Predictors of unplanned ICU admission included older age, being male, having a higher acuity triage category and a history of co-morbid conditions. Emergency department diagnostic groups associated with higher incidence of unplanned ICU admission included: sepsis, acute renal failure, lymphatic-hematopoietic tissue neoplasms, pneumonia, chronic-airways disease and bowel obstruction. The final model used to develop the nomogram had an ROC curve AUC of 0.7. CONCLUSION: This study identified factors associated with unplanned ICU admission and developed a nomogram to individualise risk prior to a patient being transferred from the ED. This nomogram provides clinicians the opportunity prior to transfer from the ED, to either (1) review the appropriateness of the ward level of planned transfer or (2) flag patients for follow-up on the general ward to assess for deterioration.
Authors: David N Hager; Pranav Chandrashekar; Robert W Bradsher; Ali M Abdel-Halim; Souvik Chatterjee; Melinda Sawyer; Roy G Brower; Dale M Needham Journal: J Crit Care Date: 2017-08-03 Impact factor: 3.425
Authors: Daniel K Nishijima; Matthew Sena; Joseph M Galante; Kiarash Shahlaie; Jason London; Joy Melnikow; James F Holmes Journal: Ann Emerg Med Date: 2013-12-04 Impact factor: 5.721
Authors: Louise S van Galen; Patricia W Struik; Babiche E J M Driesen; Hanneke Merten; Jeroen Ludikhuize; Johannes I van der Spoel; Mark H H Kramer; Prabath W B Nanayakkara Journal: PLoS One Date: 2016-08-18 Impact factor: 3.240
Authors: James Malycha; Timothy Bonnici; David A Clifton; Guy Ludbrook; J Duncan Young; Peter J Watkinson Journal: BMC Med Inform Decis Mak Date: 2019-05-15 Impact factor: 2.796
Authors: Mariska Weenk; Harry van Goor; Bas Frietman; Lucien Jlpg Engelen; Cornelis Jhm van Laarhoven; Jan Smit; Sebastian Jh Bredie; Tom H van de Belt Journal: JMIR Mhealth Uhealth Date: 2017-07-05 Impact factor: 4.773
Authors: Mariska Weenk; Sebastian J Bredie; Mats Koeneman; Gijs Hesselink; Harry van Goor; Tom H van de Belt Journal: J Med Internet Res Date: 2020-06-10 Impact factor: 5.428