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Research ArticleORIGINAL RESEARCH
Open Access

The Modified Early Warning Score as a Predictive Tool During Unplanned Surgical Intensive Care Unit Admission

Annandita Kumar, Hussam Ghabra, Fiona Winterbottom, Michael Townsend, Philip Boysen and Bobby D. Nossaman
Ochsner Journal June 2020, 20 (2) 176-181; DOI: https://doi.org/10.31486/toj.19.0057
Annandita Kumar
1University of Queensland Faculty of Medicine, Ochsner Clinical School, New Orleans, LA
MD
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Hussam Ghabra
2Department of Anesthesiology, Ochsner Clinic Foundation, New Orleans, LA
MD
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Fiona Winterbottom
1University of Queensland Faculty of Medicine, Ochsner Clinical School, New Orleans, LA
3Department of Pulmonary/Critical Care, Ochsner Clinic Foundation, New Orleans, LA
DNP, MSN
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Michael Townsend
1University of Queensland Faculty of Medicine, Ochsner Clinical School, New Orleans, LA
4Department of Surgery, Ochsner Clinic Foundation, New Orleans, LA
MD
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Philip Boysen
5Department of Anesthesiology, University of Mississippi School of Medicine, Jackson, MS
MD
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Bobby D. Nossaman
1University of Queensland Faculty of Medicine, Ochsner Clinical School, New Orleans, LA
2Department of Anesthesiology, Ochsner Clinic Foundation, New Orleans, LA
MD
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  • For correspondence: bnossaman{at}ochsner.org
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REFERENCES

  1. 1.↵
    1. Mitchell IA,
    2. McKay H,
    3. Van Leuvan C,
    4. et al.
    A prospective controlled trial of the effect of a multi-faceted intervention on early recognition and intervention in deteriorating hospital patients. Resuscitation. 2010 Jun;81(6):658-666. doi: 10.1016/j.resuscitation.2010.03.001.
    OpenUrlCrossRefPubMedWeb of Science
  2. 2.↵
    1. Hammond NE,
    2. Spooner AJ,
    3. Barnett AG,
    4. Corley A,
    5. Brown P,
    6. Fraser JF
    . The effect of implementing a modified early warning scoring (MEWS) system on the adequacy of vital sign documentation. Aust Crit Care. 2013 Feb;26(1):18-22. doi: 10.1016/j.aucc.2012.05.001.
    OpenUrlCrossRefPubMedWeb of Science
  3. 3.
    1. Ludikhuize J,
    2. Smorenburg SM,
    3. de Rooij SE,
    4. de Jonge E
    . Identification of deteriorating patients on general wards; measurement of vital parameters and potential effectiveness of the modified early warning score. J Crit Care. 2012 Aug;27(4):424.e7-13. doi: 10.1016/j.jcrc.2012.01.003.
    OpenUrlCrossRef
  4. 4.↵
    1. van Galen LS,
    2. Struik PW,
    3. Driesen BE,
    4. et al.
    Delayed recognition of deterioration of patients in general wards is mostly caused by human related monitoring failures: a root cause analysis of unplanned ICU admissions. PLoS One. 2016 Aug 18;11(8):e0161393. doi: 10.1371/journal.pone.0161393.
    OpenUrlCrossRef
  5. 5.
    1. Churpek MM,
    2. Yuen TC,
    3. Park SY,
    4. Gibbons R,
    5. Edelson DP
    . Using electronic health record data to develop and validate a prediction model for adverse outcomes in the wards. Crit Care Med. 2014 Apr;42(4):841-848. doi: 10.1097/CCM.0000000000000038.
    OpenUrlCrossRefPubMed
  6. 6.↵
    1. Morgan R,
    2. Lloyd-Williams F,
    3. Wright M,
    4. Morgan-Warren RJ
    . An early warning scoring system for detecting developing critical illness. Clin Intensive Care. 1997;8(2):S100.
    OpenUrl
  7. 7.↵
    1. van Rooijen CR,
    2. de Ruijter W,
    3. van Dam B
    . Evaluation of the threshold value for the early warning score on general wards. Neth J Med. 2013 Jan;71(1):38-43.
    OpenUrl
  8. 8.↵
    1. Buist MD,
    2. Jarmolowski E,
    3. Burton PR,
    4. Bernard SA,
    5. Waxman BP,
    6. Anderson J
    . Recognising clinical instability in hospital patients before cardiac arrest or unplanned admission to intensive care. A pilot study in a tertiary-care hospital. Med J Aust. 1999 Jul 5;171(1):22-25.
    OpenUrlPubMedWeb of Science
  9. 9.↵
    1. Subbe CP,
    2. Kruger M,
    3. Rutherford P,
    4. Gemmel L
    . Validation of a modified early warning score in medical admissions. QJM. 2001 Oct;94(10):521-526. doi: 10.1093/qjmed/94.10.521.
    OpenUrlCrossRefPubMedWeb of Science
  10. 10.↵
    1. Pittard AJ
    . Out of our reach? Assessing the impact of introducing a critical care outreach service. Anaesthesia. 2003 Sep;58(9):882-885. doi: 10.1046/j.1365-2044.2003.03331.x.
    OpenUrlCrossRefPubMedWeb of Science
  11. 11.↵
    1. McGaughey J,
    2. Alderdice F,
    3. Fowler R,
    4. Kapila A,
    5. Mayhew A,
    6. Moutray M
    . Outreach and early warning systems (EWS) for the prevention of intensive care admission and death of critically ill adult patients on general hospital wards. Cochrane Database Syst Rev. 2007 Jul 18;(3):CD005529. doi: 10.1002/14651858.CD005529.pub2.
    OpenUrlCrossRefPubMed
  12. 12.↵
    1. Le Lagadec MD,
    2. Dwyer T
    . Scoping review: the use of early warning systems for the identification of in-hospital patients at risk of deterioration. Aust Crit Care. 2017 Jul;30(4):211-218. doi: 10.1016/j.aucc.2016.10.003.
    OpenUrlCrossRef
  13. 13.↵
    1. Baghi H,
    2. Noorbaloochi S,
    3. Moore JB
    . Statistical and nonstatistical significance: implications for health care researchers. Qual Manag Health Care. 2007 Apr-Jun;16(2):104-112.
    OpenUrlPubMed
  14. 14.↵
    1. Visintainer PF,
    2. Tejani N
    . Understanding and using confidence intervals in clinical research. J Matern Fetal Med. 1998 Jul-Aug;7(4):201-206. doi: 10.1002/(SICI)1520-6661(199807/08)7:4<201::AID-MFM8>3.0.CO;2-M.
    OpenUrlCrossRefPubMed
  15. 15.↵
    1. Kim HY
    . Statistical notes for clinical researchers: effect size. Restor Dent Endod. 2015 Nov;40(4):328-331. doi: 10.5395/rde.2015.40.4.328.
    OpenUrlCrossRef
  16. 16.↵
    1. Sullivan GM,
    2. Feinn R
    . Using effect size-or why the P value is not enough. J Grad Med Educ. 2012;4(3):279-282. doi: 10.4300/JGME-D-12-00156.1.
    OpenUrlCrossRefPubMed
  17. 17.↵
    1. Merkow RP,
    2. Hall BL,
    3. Cohen ME,
    4. et al.
    Relevance of the C-statistic when evaluating risk-adjustment models in surgery. J Am Coll Surg. 2012 May;214(5):822-830. doi: 10.1016/j.jamcollsurg.2011.12.041.
    OpenUrlCrossRefPubMed
  18. 18.↵
    1. Altman DG,
    2. Bland JM
    . Diagnostic tests 3: receiver operating characteristic plots. BMJ. 1994 Jul 16;309(6948):188. doi: 10.1136/bmj.309.6948.188.
    OpenUrlFREE Full Text
  19. 19.↵
    1. Copeland KT,
    2. Checkoway H,
    3. McMichael AJ,
    4. Holbrook RH
    . Bias due to misclassification in the estimation of relative risk. Am J Epidemiol. 1977 May;105(5):488-495. doi: 10.1093/oxfordjournals.aje.a112408.
    OpenUrlCrossRefPubMedWeb of Science
  20. 20.
    1. Lyles RH,
    2. Tang L,
    3. Superak HM,
    4. et al.
    Validation data-based adjustment for outcome misclassification in logistic regression: an illustration. Epidemiology. 2011 Jul;22(4):589-597. doi: 10.1097/EDE.0b013e3182117c85.
    OpenUrlCrossRefPubMedWeb of Science
  21. 21.↵
    1. Romero-Brufau S,
    2. Huddleston JM,
    3. Escobar GJ,
    4. Liebow M
    . Why the C-statistic is not informative to evaluate early warning scores and what metrics to use. Crit Care. 2015 Aug 13;19:285. doi: 10.1186/s13054-015-0999-1.
    OpenUrlCrossRef
  22. 22.↵
    1. Bland JM,
    2. Altman DG
    . Statistics notes: bootstrap resampling methods. BMJ. 2015 Jun 2;350:h2622. doi: 10.1136/bmj.h2622.
    OpenUrlFREE Full Text
  23. 23.↵
    1. Steyerberg EW,
    2. Harrell FE Jr.
    . Prediction models need appropriate internal, internal-external, and external validation. J Clin Epidemiol. 2016 Jan;69:245-247. doi: 10.1016/j.jclinepi.2015.04.005.
    OpenUrlCrossRefPubMed
  24. 24.↵
    1. Colquhoun D
    . An investigation of the false discovery rate and the misinterpretation of p-values. R Soc Open Sci. 2014 Nov 19;1(3):140216. doi: 10.1098/rsos.140216.
    OpenUrlCrossRefPubMed
  25. 25.↵
    1. Glickman ME,
    2. Rao SR,
    3. Schultz MR
    . False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. J Clin Epidemiol. 2014 Aug;67(8):850-857. doi: 10.1016/j.jclinepi.2014.03.012.
    OpenUrlCrossRefPubMed
  26. 26.↵
    1. Chan KS,
    2. Tan CK,
    3. Fang CS,
    4. et al.
    Readmission to the intensive care unit: an indicator that reflects the potential risks of morbidity and mortality of surgical patients in the intensive care unit. Surg Today. 2009;39(4):295-299. doi: 10.1007/s00595-008-3876-6.
    OpenUrlCrossRefPubMedWeb of Science
  27. 27.
    1. Pavoni V,
    2. Gianesello L,
    3. Paparella L,
    4. Buoninsegni LT,
    5. Mori E,
    6. Gori G
    . Outcome and quality of life of elderly critically ill patients: an Italian prospective observational study. Arch Gerontol Geriatr. 2012 Mar-Apr;54(2):e193-198. doi: 10.1016/j.archger.2011.11.013.
    OpenUrlCrossRefPubMed
  28. 28.
    1. Alban RF,
    2. Nisim AA,
    3. Ho J,
    4. Nishi GK,
    5. Shabot MM
    . Readmission to surgical intensive care increases severity-adjusted patient mortality. J Trauma. 2006 May;60(5):1027-1031. doi: 10.1097/01.ta.0000218217.42861.b7.
    OpenUrlCrossRefPubMed
  29. 29.
    1. Kaben A,
    2. Correa F,
    3. Reinhart K,
    4. Settmacher U,
    5. Gummert J,
    6. Kalff R,
    7. et al.
    Readmission to a surgical intensive care unit: incidence, outcome and risk factors. Crit Care. 2008;12(5):R123. doi: 10.1186/cc7023.
    OpenUrlCrossRefPubMed
  30. 30.
    1. Lissauer ME,
    2. Diaz JJ,
    3. Narayan M,
    4. Shah PK,
    5. Hanna NN
    . Surgical intensive care unit admission variables predict subsequent readmission. Am Surg. 2013 Jun;79(6):583-588.
    OpenUrl
  31. 31.↵
    1. Brunelli A,
    2. Ferguson MK,
    3. Rocco G,
    4. et al.
    A scoring system predicting the risk for intensive care unit admission for complications after major lung resection: a multicenter analysis. Ann Thorac Surg. 2008 Jul;86(1):213-218. doi: 10.1016/j.athoracsur.2008.03.063.
    OpenUrlCrossRefPubMedWeb of Science
  32. 32.↵
    1. Cuthbertson BH,
    2. Boroujerdi M,
    3. McKie L,
    4. Aucott L,
    5. Prescott G
    . Can physiological variables and early warning scoring systems allow early recognition of the deteriorating surgical patient? Crit Care Med. 2007 Feb;35(2):402-409. doi: 10.1097/01.CCM.0000254826.10520.87.
    OpenUrlCrossRefPubMedWeb of Science
  33. 33.↵
    1. Ludikhuize J,
    2. Brunsveld-Reinders AH
    , et al; Cost and Outcomes of Medical Emergency Teams Study Group. Outcomes associated with the nationwide introduction of rapid response systems in the Netherlands. 2015 Dec;43(12):2544-2551. doi: 10.1097/CCM.0000000000001272.
    OpenUrlCrossRef
  34. 34.↵
    1. Ludikhuize J,
    2. de Jonge E,
    3. Goossens A
    . Measuring adherence among nurses one year after training in applying the modified early warning score and situation-background-assessment-recommendation instruments. Resuscitation. 2011 Nov;82(11):1428-1433. doi: 10.1016/j.resuscitation.2011.05.026.
    OpenUrlCrossRefPubMed
  35. 35.↵
    1. Eusebi P
    . Diagnostic accuracy measures. Cerebrovasc Dis. 2013;36(4):267-272. doi: 10.1159/000353863.
    OpenUrlCrossRefPubMed
  36. 36.↵
    1. Kellett J,
    2. Wang F,
    3. Woodworth S,
    4. Huang W
    . Changes and their prognostic implications in the abbreviated VitalPAC early warning score (ViEWS) after admission to hospital of 18,827 surgical patients. Resuscitation. 2014 Apr;85(4):544-548. doi: 10.1016/j.resuscitation.2012.12.002.
    OpenUrlCrossRef
  37. 37.↵
    1. Escobar GJ,
    2. LaGuardia JC,
    3. Turk BJ,
    4. Ragins A,
    5. Kipnis P,
    6. Draper D
    . Early detection of impending physiologic deterioration among patients who are not in intensive care: development of predictive models using data from an automated electronic medical record. J Hosp Med. 2012 May-Jun;7(5):388-395. doi: 10.1002/jhm.1929.
    OpenUrlCrossRefPubMed
  38. 38.↵
    1. Sackett DL,
    2. Deeks JJ,
    3. Altman DG
    . Down with odds ratios! BMJ Evid Based Med. 1996 Sept/Oct;1(6):164-146.
    OpenUrlAbstract/FREE Full Text
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The Modified Early Warning Score as a Predictive Tool During Unplanned Surgical Intensive Care Unit Admission
Annandita Kumar, Hussam Ghabra, Fiona Winterbottom, Michael Townsend, Philip Boysen, Bobby D. Nossaman
Ochsner Journal Jun 2020, 20 (2) 176-181; DOI: 10.31486/toj.19.0057

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The Modified Early Warning Score as a Predictive Tool During Unplanned Surgical Intensive Care Unit Admission
Annandita Kumar, Hussam Ghabra, Fiona Winterbottom, Michael Townsend, Philip Boysen, Bobby D. Nossaman
Ochsner Journal Jun 2020, 20 (2) 176-181; DOI: 10.31486/toj.19.0057
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Keywords

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