Evaluation of the SpO2/FiO2 ratio as a predictor of intensive care unit transfers in respiratory ward patients for whom the rapid response system has been activated

Won Gun Kwack, Dong Seon Lee, Hyunju Min, Yun Young Choi, Miae Yun, Youlim Kim, Sang Hoon Lee, Inae Song, Jong Sun Park, Young-Jae Cho, You Hwan Jo, Ho Il Yoon, Jae Ho Lee, Choon-Taek Lee, Yeon Joo Lee, Won Gun Kwack, Dong Seon Lee, Hyunju Min, Yun Young Choi, Miae Yun, Youlim Kim, Sang Hoon Lee, Inae Song, Jong Sun Park, Young-Jae Cho, You Hwan Jo, Ho Il Yoon, Jae Ho Lee, Choon-Taek Lee, Yeon Joo Lee

Abstract

Efforts to detect patient deterioration early have led to the development of early warning score (EWS) models. However, these models are disease-nonspecific and have shown variable accuracy in predicting unexpected critical events. Here, we propose a simpler and more accurate method for predicting risk in respiratory ward patients. This retrospective study analyzed adult patients who were admitted to the respiratory ward and detected using the rapid response system (RRS). Study outcomes included transfer to the intensive care unit (ICU) within 24 hours after RRS activation and in-hospital mortality. Prediction power of existing EWS models including Modified EWS (MEWS), National EWS (NEWS), and VitalPAC EWS (ViEWS) and SpO2/FiO2 (SF) ratio were compared to each other using the area under the receiver operating characteristic curve (AUROC). Overall, 456 patients were included; median age was 75 years (interquartile range: 65-80) and 344 (75.4%) were male. Seventy-three (16.0%) and 79 (17.3%) patients were transferred to the ICU and died. The SF ratio displayed better or comparable predictive accuracy for unexpected ICU transfer (AUROC: 0.744) compared to MEWS (0.744 vs. 0.653, P = 0.03), NEWS (0.744 vs. 0.667, P = 0.04), and ViEWS (0.744 vs. 0.675, P = 0.06). For in-hospital mortality, although there was no statistical difference, the AUROC of the SF ratio (0.660) was higher than that of each of the preexisting EWS models. In comparison with the preexisting EWS models, the SF ratio showed better or comparable predictive accuracy for unexpected ICU transfers in the respiratory wards.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. Comparison of the area of…
Fig 1. Comparison of the area of under the receiver operating characteristics curve for intensive care unit transfers within 24 hours of rapid response system activation.
MEWS, Modified Early Warning Score; NEWS, National Early Warning Score; ViEWS, VitalPAC Early Warning Score; AUROC, area under the receiver operating characteristic curve; ICU, intensive care unit. *SF ratio: SpO2/FiO2 ratio.
Fig 2. Comparison of the area of…
Fig 2. Comparison of the area of under the receiver operating characteristics curve for in-hospital mortality.
MEWS, Modified Early Warning Score; NEWS, National Early Warning Score; ViEWS, VitalPAC Early Warning Score; AUROC, area under the receiver operating characteristic curve. *SF ratio: SpO2/FiO2 ratio.

References

    1. Ferkol T, Schraufnagel D. The global burden of respiratory disease. Annals of the American Thoracic Society. 2014;11(3):404–6. 10.1513/AnnalsATS.201311-405PS
    1. Health Insurance Reveiw and Assessment Service. Medical Statistics information. 2017; 11: 17 Available from: .
    1. Morgan R, Williams F, Wright M. An early warning scoring system for detecting developing critical illness. Clin Intensive Care. 1997;8(2):100.
    1. Subbe C, Kruger M, Rutherford P, Gemmel L. Validation of a modified Early Warning Score in medical admissions. Qjm. 2001;94(10):521–6.
    1. Prytherch DR, Smith GB, Schmidt PE, Featherstone PI. ViEWS—Towards a national early warning score for detecting adult inpatient deterioration. Resuscitation. 2010;81(8):932–7. 10.1016/j.resuscitation.2010.04.014
    1. Williams B, Alberti G, Ball C, Bell D, Binks R, Durham L. National Early Warning Score (NEWS): standardising the assessment of acute-illness severity in the NHS London: The Royal College of Physicians: 2012.
    1. Mapp ID, Davis LL, Krowchuk H. Prevention of unplanned intensive care unit admissions and hospital mortality by early warning systems. Dimensions of Critical Care Nursing. 2013;32(6):300–9. 10.1097/DCC.0000000000000004
    1. Stenhouse C, Coates S, Tivey M, Allsop P, Parker T. Prospective evaluation of a modified Early Warning Score to aid earlier detection of patients developing critical illness on a general surgical ward. Br J Anaesth. 2000;84(5):663.
    1. Jo S, Jeong T, Lee JB, Jin Y, Yoon J, Park B. Validation of modified early warning score using serum lactate level in community-acquired pneumonia patients. The National Early Warning Score-Lactate score. The American journal of emergency medicine. 2016;34(3):536–41.
    1. Lee YJ, Lee DS. Differences in the Clinical Characteristics of Rapid Response System Activation in Patients Admitted to Medical or Surgical Services. 2017;32(4):688–94.
    1. Jubran A. Pulse oximetry. Critical care (London, England). 2015;19:272.
    1. Rice TW, Wheeler AP, Bernard GR, Hayden DL, Schoenfeld DA, Ware LB. Comparison of the SpO2/FIO2 ratio and the PaO2/FIO2 ratio in patients with acute lung injury or ARDS. Chest. 2007;132(2):410–7. 10.1378/chest.07-0617
    1. Chen W, Janz DR, Shaver CM, Bernard GR, Bastarache JA, Ware LB. Clinical Characteristics and Outcomes Are Similar in ARDS Diagnosed by Oxygen Saturation/Fio2 Ratio Compared With Pao2/Fio2 Ratio. Chest. 2015;148(6):1477–83. 10.1378/chest.15-0169
    1. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of chronic diseases. 1987;40(5):373–83.
    1. Kim Y, Lee DS, Min H, Choi YY, Lee EY, Song I, et al. Effectiveness Analysis of a Part-Time Rapid Response System During Operation Versus Nonoperation. Critical care medicine. 2017;45(6):e592–e9. 10.1097/CCM.0000000000002314
    1. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44(3):837–45.
    1. Perkins NJ, Schisterman EF. The inconsistency of "optimal" cutpoints obtained using two criteria based on the receiver operating characteristic curve. American journal of epidemiology. 2006;163(7):670–5. 10.1093/aje/kwj063
    1. 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 medicine. 2002;28(11):1629–34. 10.1007/s00134-002-1496-y
    1. Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388–92.
    1. Franklin C, Mathew J. Developing strategies to prevent inhospital cardiac arrest: analyzing responses of physicians and nurses in the hours before the event. Critical care medicine. 1994;22(2):244–7.
    1. Yoo JW, Lee JR, Jung YK, Choi SH, Son JS, Kang BJ, et al. A combination of early warning score and lactate to predict intensive care unit transfer of inpatients with severe sepsis/septic shock. The Korean journal of internal medicine. 2015;30(4):471–7. 10.3904/kjim.2015.30.4.471
    1. 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. Emergency medicine journal: EMJ. 2013;30(2):123–9. 10.1136/emermed-2011-200760
    1. Nickel CH, Kellett J, Cooksley T, Bingisser R, Henriksen DP, Brabrand M. Combined use of the National Early Warning Score and D-dimer levels to predict 30-day and 365-day mortality in medical patients. Resuscitation. 2016;106:49–52. 10.1016/j.resuscitation.2016.06.012
    1. Kim WY, Lee J, Lee JR, Jung YK, Kim HJ, Huh JW, et al. A risk scoring model based on vital signs and laboratory data predicting transfer to the intensive care unit of patients admitted to gastroenterology wards. Journal of critical care. 2017;40:213–7. 10.1016/j.jcrc.2017.04.024
    1. Boyko EJ. Ruling out or ruling in disease with the most sensitive or specific diagnostic test: short cut or wrong turn? Medical decision making: an international journal of the Society for Medical Decision Making. 1994;14(2):175–9.
    1. Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, Fan E, et al. Acute respiratory distress syndrome: the Berlin Definition. Jama. 2012;307(23):2526–33. 10.1001/jama.2012.5669
    1. Morgan TJ. The oxyhaemoglobin dissociation curve in critical illness. Critical care and resuscitation: journal of the Australasian Academy of Critical Care Medicine. 1999;1(1):93–100.

Source: PubMed

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