Ju Ry Lee; Hye Ran Choi

doi:10.4040/jkan.2014.44.2.219

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Original Article
Validation of a Modified Early Warning Score to Predict ICU Transfer for Patients with Severe Sepsis or Septic Shock on General Wards: Ju Ry Lee, Hye Ran Choi; Journal of Korean Academy of Nursing 2014;44(2):219-227.
DOI: https://doi.org/10.4040/jkan.2014.44.2.219
Published online: April 30, 2014

¹Medical Alert Team, Asan Medical Center, Seoul, Korea.

²College of Medicine, University of Ulsan, Seoul, Korea.

Address reprint requests to: Choi, Hye Ran. Department of Clinical Nursing, College of Medicine, University of Ulsan, 88 Olympic-ro, 43-gil, Songpa-gu, Seoul 138-736, Korea. Tel: +82-2-3010-5334, Fax: +82-2-3010-5332, reniechoi@hanmail.net

• Received: December 4, 2013 • Revised: December 16, 2013 • Accepted: March 31, 2014

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0/) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

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Abstract
NOTES
REFERENCES

Abstract

Purpose
To assess whether the Modified Early Warning Score (MEWS) predicts the need for intensive care unit (ICU) transfer for patients with severe sepsis or septic shock admitted to general wards.
Methods
A retrospective chart review of 100 general ward patients with severe sepsis or septic shock was implemented. Clinical information and MEWS according to point of time between ICU group and general ward group were reviewed. Data were analyzed using multivariate logistic regression and the area under the receiver operating characteristic curves with SPSS/WIN 18.0 program.
Results
Thirty-eight ICU patients and sixty-two general ward patients were included. In multivariate logistic regression, MEWS (odds ratio [OR] 2.02, 95% confidence interval [CI] 1.43-2.85), lactic acid (OR 1.83, 95% CI 1.22-2.73) and diastolic blood pressure (OR 0.89, 95% CI 0.80-1.00) were predictive of ICU transfer. The sensitivity and the specificity of MEWS used with cut-off value of six were 89.5% and 67.7% for ICU transfer.
Conclusion
MEWS is an effective predictor of ICU transfer. A clinical algorithm could be created to respond to high MEWS and intervene with appropriate changes in clinical management.
Keywords: Hospital rapid response team; Sepsis; Septic shock; Modified early warning score; Intensive care unit

This manuscript is a revision of the first author's master's thesis from University of Ulsan.

REFERENCES

1. Minino AM, Heron MP, Murphy SL, Kochanek KD. Deaths: Final data for 2004. Natl Vital Stat Rep. 2007;55(19):1–119.
2. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: Analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;29(7):1303–1310.Article PubMed
3. Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D, et al. 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference. Intensive Care Med. 2003;29(4):530–538. http://dx.doi.org/10.1007/s00134-003-1662-xArticle PubMed PDF
4. Levy MM, Dellinger RP, Townsend SR, Linde-Zwirble WT, Marshall JC, Bion J, et al. The surviving sepsis campaign: Results of an international guideline-based performance improvement program targeting severe sepsis. Intensive Care Med. 2010;36(2):222–231. http://dx.doi.org/10.1007/s00134-009-1738-3Article PubMed PMC PDF
5. Esteban A, Frutos-Vivar F, Ferguson ND, Peñuelas O, Lorente JA, Gordo F, et al. Sepsis incidence and outcome: Contrasting the intensive care unit with the hospital ward. Crit Care Med. 2007;35(5):1284–1289. http://dx.doi.org/10.1097/01.ccm.0000260960.94300.deArticle PubMed
6. Goldhill DR, Worthington L, Mulcahy A, Tarling M, Sumner A. The patient-at-risk team: Identifying and managing seriously ill ward patients. Anaesthesia. 1999;54(9):853–860.Article PubMed PDF
7. Hong SK, Hong SB, Lim CM, Koh Y. The characteristics and prognostic factors of severe sepsis in patients who were admitted to a medical intensive care unit of a tertiary hospital. Korean J Crit Care Med. 2009;24(1):28–32. http://dx.doi.org/10.4266/kjccm.2009.24.1.28Article
8. Hillman KM, Bristow PJ, Chey T, Daffurn K, Jacques T, Norman SL, et al. Duration of life-threatening antecedents prior to intensive care admission. Intensive Care Med. 2002;28(11):1629–1634. http://dx.doi.org/10.1007/s00134-002-1496-yArticle PubMed PDF
9. Calle P, Cerro L, Valencia J, Jaimes F. Usefulness of severity scores in patients with suspected infection in the emergency department: A systematic review. J Emerg Med. 2012;42(4):379–391. http://dx.doi.org/10.1016/j.jemermed.2011.03.033Article PubMed
10. Smith GB, Osgood VM, Crane S. ALERT-a multiprofessional training course in the care of the acutely ill adult patient. Resuscitation. 2002;52(3):281–286.Article PubMed
11. Lee A, Bishop G, Hillman KM, Daffurn K. The medical emergency team. Anaesth Intensive Care. 1995;23(2):183–186.Article PubMed PDF
12. Bellomo R, Goldsmith D, Uchino S, Buckmaster J, Hart G, Opdam H, et al. Prospective controlled trial of effect of medical emergency team on postoperative morbidity and mortality rates. Crit Care Med. 2004;32(4):916–921.Article PubMed
13. Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified early warning score in medical admissions. QJM. 2001;94(10):521–526.Article PubMed
14. Smith GB, Prytherch DR, Schmidt PE, Featherstone PI. Review and performance evaluation of aggregate weighted 'track and trigger' systems. Resuscitation. 2008;77(2):170–179. http://dx.doi.org/10.1016/j.resuscitation.2007.12.004Article PubMed
15. Gardner-Thorpe J, Love N, Wrightson J, Walsh S, Keeling N. The value of modified early warning score (MEWS) in surgical in-patients: A prospective observational study. Ann R Coll Surg Engl. 2006;88(6):571–575. http://dx.doi.org/10.1308/003588406x130615Article PubMed PMC
16. Corfield AR, Lees F, Zealley I, Houston G, Dickie S, Ward K, et al. Utility of a single early warning score in patients with sepsis in the emergency department. Emerg Med J. 2013;03 09 Forthcoming. http://dx.doi.org/10.1136/emermed-2012-202186Article
17. Duncan KD, McMullan C, Mills BM. Early warning systems: The next level of rapid response. Nursing. 2012;42(2):38–44. http://dx.doi.org/10.1097/01.nurse.0000410304.26165.33
18. Jo S, Lee JB, Jin YH, Jeong TO, Yoon JC, Jun YK, et al. Modified early warning score with rapid lactate level in critically ill medical patients: The ViEWS-L score. Emerg Med J. 2013;30(2):123–129. http://dx.doi.org/10.1136/emermed-2011-200760Article PubMed
19. Potter PA, Perry AG. Fundamentals of nursing. 5th ed. St. Louis, MO: Mosby; 2001.
20. Franklin C, Mathew J. Developing strategies to prevent inhospital cardiac arrest: Analyzing responses of physicians and nurses in the hours before the event. Crit Care Med. 1994;22(2):244–247.Article PubMed
21. Harrison GA, Jacques TC, Kilborn G, McLaws ML. The prevalence of recordings of the signs of critical conditions and emergency responses in hospital wards-the SOCCER study. Resuscitation. 2005;65(2):149–157. http://dx.doi.org/10.1016/j.resuscitation.2004.11.017Article PubMed
22. Cuthbertson BH, Boroujerdi M, McKie L, Aucott L, Prescott G. Can physiological variables and early warning scoring systems allow early recognition of the deteriorating surgical patient? Crit Care Med. 2007;35(2):402–409. http://dx.doi.org/10.1097/01.ccm.0000254826.10520.87Article PubMed
23. Sebat F, Musthafa AA, Johnson D, Kramer AA, Shoffner D, Eliason M, et al. Effect of a rapid response system for patients in shock on time to treatment and mortality during 5 years. Crit Care Med. 2007;35(11):2568–2575. http://dx.doi.org/10.1097/01.ccm.0000287593.54658.89Article PubMed
24. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: A severity of disease classification system. Crit Care Med. 1985;13(10):818–829.Article PubMed
25. Fawcett T. An introduction to ROC analysis. Pattern Recognit Lett. 2006;27(8):861–874. http://dx.doi.org/10.1016/j.patrec.2005.10.010Article
26. Xinke MEN, Jing YNG, Huaxiong WU, Xiaoying ZHU, Gang WEI, Dehong LIU, et al. Comparison of modified early warning score (MEWS) and APACHE ll score in evaluation severity and prediction out-come of emergency potential severity disease. J Jiangsu Clin Med. 2005;8:1–4.

Figure 1

Receiver operator characteristic curve for ability to predict ICU admission. A point is cut-off value of 5 (sensitivity 94.7% and specificity 50.0%), B point is cut-off value of 6 (sensitivity 82.5% and specificity 80.5%), and C point is cut-off value of 7 (sensitivity 64.0% and specificity 87.5%).

Table 1

Modified Early Warning Score

AVPU=Alert, verbal, pain, unresponsive.

Table 2

Baseline Characteristics of Sample

^*Yates' correction; ^†Fisher's exact test; M (IQR)=Median (Interquartile range); ICU=Intensive care unit; APACHE=Acute physiology and chronic health evaluation.

Table 3

Physiological Parameters and MEWS Dichotomized according to Point of Time

^*Zero point=Systolic blood pressure<90 mmHg at first measurement; ICU=Intensive care unit; Median (IQR)=Median (Interquartile range); SBP=Systolic blood pressure; DBP=Diastolic blood pressure; HR=Heart rate; RR=Respiratory rate; bpm=breaths per minute; BT=Body temperature; GCS=Glasgow coma scale; MEWS=Modified early warning score.

Table 4

Logistic Regression Analysis for ICU Transfer

^*Zero point=Systolic blood pressure<90 mmHg at first measurement; ICU=Intensive care unit; MET=Medical emergency team; OR=Odds ratio; CI=Confidence interval; SBP=Systolic blood pressure; DBP=Diastolic blood pressure; HR=Heart rate; RR=Respiratory rate; bpm=breaths per minute; GCS=Glasgow coma scale; MEWS=Modified early warning score; APACHE=Acute physiology and chronic health evaluation.

Figure & Data

REFERENCES

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Validation of a Modified Early Warning Score to Predict ICU Transfer for Patients with Severe Sepsis or Septic Shock on General Wards

J Korean Acad Nurs. 2014;44(2):219-227. Published online April 30, 2014

DOI: https://doi.org/10.4040/jkan.2014.44.2.219

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Validation of a Modified Early Warning Score to Predict ICU Transfer for Patients with Severe Sepsis or Septic Shock on General Wards

Figure 1 Receiver operator characteristic curve for ability to predict ICU admission. A point is cut-off value of 5 (sensitivity 94.7% and specificity 50.0%), B point is cut-off value of 6 (sensitivity 82.5% and specificity 80.5%), and C point is cut-off value of 7 (sensitivity 64.0% and specificity 87.5%).

Figure 1

Validation of a Modified Early Warning Score to Predict ICU Transfer for Patients with Severe Sepsis or Septic Shock on General Wards

Table 1

Modified Early Warning Score

AVPU=Alert, verbal, pain, unresponsive.

Table 2

Baseline Characteristics of Sample

^*Yates' correction; ^†Fisher's exact test; M (IQR)=Median (Interquartile range); ICU=Intensive care unit; APACHE=Acute physiology and chronic health evaluation.

Table 3

Physiological Parameters and MEWS Dichotomized according to Point of Time

Table 4

Logistic Regression Analysis for ICU Transfer

Table 1 Modified Early Warning Score

AVPU=Alert, verbal, pain, unresponsive.

Table 2 Baseline Characteristics of Sample

^*Yates' correction; ^†Fisher's exact test; M (IQR)=Median (Interquartile range); ICU=Intensive care unit; APACHE=Acute physiology and chronic health evaluation.

Table 3 Physiological Parameters and MEWS Dichotomized according to Point of Time