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Derivation and validation of modified early warning score plus SpO2/FiO2 score for predicting acute deterioration of patients with hematological malignancies

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Background/Aims: Scoring systems play an important role in predicting intensive care unit (ICU) admission or estimating the risk of death in critically ill patients with hematological malignancies. We evaluated the modified early warning score (MEWS) for predicting ICU admissions and in-hospital mortality among at-risk patients with hematological malignancies and developed an optimized MEWS. Methods: We retrospectively analyzed derivation cohort patients with hematological malignancies who were managed by a medical emergency team (MET) in the general ward and prospectively validated the data. We compared the traditional MEWS with the MEWS plus SpO2/FiO2 (MEWS_SF) score, which were calculated at the time of MET contact. Results: In the derivation cohort, the areas under the receiver-operating characteristic (AUROC) curves were 0.81 for the MEWS (95% confidence interval [CI], 0.76 to 0.87) and 0.87 for the MEWS_SF score (95% CI, 0.87 to 0.92) for predicting ICU admission. The AUROC curves were 0.70 for the MEWS (95% CI, 0.63 to 0.77) and 0.76 for the MEWS_SF score (95% CI, 0.70 to 0.83) for predicting in-hospital mortality. In the validation cohort, the AUROC curves were 0.71 for the MEWS (95% CI, 0.66 to 0.77) and 0.83 for the MEWS_SF score (95% CI, 0.78 to 0.87) for predicting ICU admission. The AUROC curves were 0.64 for the MEWS (95% CI, 0.57 to 0.70) and 0.74 for the MEWS_SF score (95% CI, 0.69 to 0.80) for predicting in-hospital mortality. Conclusions: Compared to the traditional MEWS, the MEWS_SF score may be a useful tool that can be used in the general ward to identify deteriorating patients with hematological malignancies.

Abstract

Background/Aims: Scoring systems play an important role in predicting intensive care unit (ICU) admission or estimating the risk of death in critically ill patients with hematological malignancies. We evaluated the modified early warning score (MEWS) for predicting ICU admissions and in-hospital mortality among at-risk patients with hematological malignancies and developed an optimized MEWS. Methods: We retrospectively analyzed derivation cohort patients with hematological malignancies who were managed by a medical emergency team (MET) in the general ward and prospectively validated the data. We compared the traditional MEWS with the MEWS plus SpO2/FiO2 (MEWS_SF) score, which were calculated at the time of MET contact. Results: In the derivation cohort, the areas under the receiver-operating characteristic (AUROC) curves were 0.81 for the MEWS (95% confidence interval [CI], 0.76 to 0.87) and 0.87 for the MEWS_SF score (95% CI, 0.87 to 0.92) for predicting ICU admission. The AUROC curves were 0.70 for the MEWS (95% CI, 0.63 to 0.77) and 0.76 for the MEWS_SF score (95% CI, 0.70 to 0.83) for predicting in-hospital mortality. In the validation cohort, the AUROC curves were 0.71 for the MEWS (95% CI, 0.66 to 0.77) and 0.83 for the MEWS_SF score (95% CI, 0.78 to 0.87) for predicting ICU admission. The AUROC curves were 0.64 for the MEWS (95% CI, 0.57 to 0.70) and 0.74 for the MEWS_SF score (95% CI, 0.69 to 0.80) for predicting in-hospital mortality. Conclusions: Compared to the traditional MEWS, the MEWS_SF score may be a useful tool that can be used in the general ward to identify deteriorating patients with hematological malignancies.

참고문헌 (34)

  1. Benoit DD, "Outcome and early prognostic indicators in patients with a hematologic malignancy admitted to the intensive care unit for a life-threatening complication", Crit Care Med, 31, pp.104~112 (2003)
  2. Dizon DS, "Clinical Cancer Advances 2016 : annual report on progress against cancer from the American Society of Clinical Oncology", J Clin Oncol, 34, pp.987~1011 (2016)
  3. Young MP, "Inpatient transfers to the intensive care unit : delays are associated with increased mortality and morbidity", J Gen Intern Med, 18, pp.77~83 (2003)
  4. Franklin C, "Developing strategies to prevent inhospital cardiac arrest : analyzing responses of physicians and nurses in the hours before the event", Crit Care Med, 22, pp.244~247 (1994)
  5. Azoulay E, "Changing use of intensive care for hematological patients : the example of multiple myeloma", Intensive Care Med, 25, pp.1395~1401 (1999)
  6. Wise MP, "Guidelines on the management and admission to intensive care of critically ill adult patients with haematological malignancy in the UK", Br J Haematol, 171, pp.179~188 (2015)
  7. van Galen LS, "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, 11, pp.e0161393~ (2016)
  8. McNeill G, "Do either early warning systems or emergency response teams improve hospital patient survival? A systematic review", Resuscitation, 84, pp.1652~1667 (2013)
  9. DeVita MA, "Use of medical emergency team responses to reduce hospital cardiopulmonary arrests", Qual Saf Health Care, 13, pp.251~254 (2004)
  10. 이주리, "일반병동 내 중증 패혈증 또는 패혈성 쇼크 환자의 중환자실 전동 예측에 대한 수정조기경고점수(Modified Early Warning Score)의 타당성", Journal of Korean Academy of Nursing, 44(2), pp.219~227 (2014), 한국간호과학회
  11. Subbe CP, "Validation of a modified early warning score in medical admissions", QJM, 94, pp.521~526 (2001)
  12. Burch VC, "Modified early warning score predicts the need for hospital admission and inhospital mortality", Emerg Med J, 25, pp.674~678 (2008)
  13. Mapp ID, "Prevention of unplanned intensive care unit admissions and hospital mortality by early warning systems", Dimens Crit Care Nurs, 32, pp.300~309 (2013)
  14. Gardner-Thorpe J, "The value of modified early warning score(MEWS)in surgical in-patients : a prospective observational study", Ann R Coll Surg Engl, 88, pp.571~575 (2006)
  15. "Acutely Ill Patients in Hospital: Recognition of and Response to Acute Illness in Adults in Hospital" (2007)[URL]
  16. Gao H, "Systematic review and evaluation of physiological track and trigger warning systems for identifying at-risk patients on the ward", Intensive Care Med, 33, pp.667~679 (2007)
  17. Jansen JO, "Detecting critical illness outside the ICU : the role of track and trigger systems", Curr Opin Crit Care, 16, pp.184~190 (2010)
  18. Huh JW, "Activation of a medical emergency team using an electronic medical recording-based screening system", Crit Care Med, 42, pp.801~808 (2014)
  19. Oken MM, "Toxicity and response criteria of the Eastern Cooperative Oncology Group", Am J Clin Oncol, 5, pp.649~655 (1982)
  20. Singer M, "The third International Consensus definitions for sepsis and septic shock (Sepsis-3)", JAMA, 315, pp.801~810 (2016)
  21. Vincent JL, "The SOFA (sepsis-related organ failure assessment) score to describe organ dysfunction", failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine, 1996, pp.22, 707~710
  22. Rice TW, "Comparison of the SpO2", FIO2 ratio and the PaO2, Chest, pp.2007, 132[DOI]
  23. Hanley JA, "The meaning and use of the area under a receiver operating characteristic (ROC) curve", Radiology, 143, pp.29~36 (1982)
  24. Kroschinsky F, "Outcome and prognostic features of intensive care unit treatment in patients with hematological malignancies", Intensive Care Med, 28, pp.1294~1300 (2002)
  25. Azoulay E, "Outcomes of critically ill patients with hematologic malignancies : prospective multicenter data from France and Belgium", J Clin Oncol, 31, pp.2810~2818 (2013)
  26. Bokhari SW, "Impact of critical care reconfiguration and trackand-trigger outreach team intervention on outcomes of haematology patients requiring intensive care admission", Ann Hematol, 89, pp.505~512 (2010)
  27. Cornish M, "Predictors of poor outcomes in critically ill adults with hematologic malignancy", Can Respir J, 2016, pp.9431385~ (2016)
  28. Gruson D, "Predictive factors of intensive care unit admission in patients with haematological malignancies and pneumonia", Intensive Care Med, 30, pp.965~971 (2004)
  29. Hampshire PA, "Admission factors associated with hospital mortality in patients with haematological malignancy admitted to UK adult, general critical care units : a secondary analysis of the ICNARC Case Mix Programme Database", Crit Care, 13, pp.R137~ (2009)
  30. Sanz F, "Accuracy of PaO2", FiO2calculated from SpO2 for severity assessment in ED patients with pneumonia, 2015, pp.20, 813~818
  31. Mulligan A, "Validation of a physiological track and trigger score to identify developing critical illness in haematology patients", Intensive Crit Care Nurs, 26, pp.196~206 (2010)
  32. Morgan RJM, "An early warning score for the early detection of patients with impending illness", Clin Intensive Care, 8, pp.100~ (1997)
  33. Cooksley T, "Effectiveness of modified early warning score in predicting outcomes in oncology patients", QJM, 105, pp.1083~1088 (2012)
  34. Palmisano JM, "Influence of tidal volume, respiratory rate, and supplemental oxygen flow on delivered oxygen fraction using a mouth to mask ventilation device", J Emerg Med, 11, pp.685~689 (1993)

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