Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Risk Factors of Predicting Intensive Care unit Transfer in Deteriorating Ward Patients

병동 급성악화 환자의 중환자실 전동 위험요인 분석

  • Lee, Ju-Ry (Department of Nursing, Geoje University)
  • Received : 2021.03.14
  • Accepted : 2021.04.20
  • Published : 2021.04.28
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Abstract

Purpose: When a patient with acute deterioration occurs in a ward, the decision to transfer to intensive care unit (ICU) is critical to improve the patient's outcomes. However, when available ICU resources limited, it is difficult to determine which of the deteriorating ward patients to transfer to the ICU. Therefore the purpose of this study was to identify risk factors in predicting deteriorating ward patients transferred to intensive care unit (ICU). Methods: We reviewed retrospectively clinical data of 2,945 deteriorating ward patients who referred medical emergency team. Data were analyzed with multivariate logistic regression. Results: The solid cancer that diagnosed at hospitalization (odds ratio[OR] 0.39; 95% confidence interval [CI] 0.32-0.47), when the cause of deterioration was respiratory problem (1.51; 95% CI 1.17-1.95), high MEWS (1.22; 1.17-1.28) and SpO2/FiO2 score (2.41; 2.23-2.60) were predictive of ICU transfer. Conclusion: These findings suggest that early prediction and treatment of patients with high risk of ICU transfer may improve the prognosis of patients.

목적: 병동에서 급성악화 환자가 발생할 때 환자에게 집중치료가 필요한지 여부에 대한 결정은 환자의 예후를 향상시키기 위해서는 매우 중요하나, 특히 사용 가능한 ICU 자원이 제한적일 때는 ICU 전동 여부를 결정하기에는 어려움이 있다. 따라서 본 연구는 일반병동 급성 악화 환자를 대상으로 중환자실 전동 위험요인을 확인하고자 한다. 연구방법: 후향적 조사연구로서 대상자는 일 상급종합병원 일반병동에 입원한 18세 이상의 성인 환자 중 악화상태를 보여 신속대응팀에 의뢰된 환자 2,945명을 대상으로 하였다. 중환자실 전동 위험요인을 파악하기 위해 다변량 로지스틱 회귀분석을 시행하였다. 연구결과: 다변량 로지스틱 회귀분석 결과 입원시 고형암을 진단받은 경우 (odds ratio [OR] 0.39, 95% CI 0.32-0.47), 악화원인이 호흡문제인 경우 (OR 1.51, 95% CI 1.17-1.95), MEWS (OR 1.22, 95% CI 1.17-1.28)와 SpO2/FiO2 score (OR 2.41, 95% CI 2.23-2.60)가 중환자실 전동 위험요인으로 나타났다. 결론: 본 연구 결과는 중환자실 전동 위험이 높은 환자의 조기 예측을 가능하게 하여 환자의 예후를 향상시키는데 도움이 될 것으로 사료된다.

Keywords

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