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

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.

Effect of Nurses' Perception of Patient Safety Culture on Reporting of Patient Safety Events / 간호행정학회지

PURPOSE: This study was done to examine factors influencing nurses' perception of patient safety culture in reporting of patient safety events. METHODS: Structured questionnaires were used to collect data from 305 nurses who were involved in direct patient care. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficients and multiple linear regressions with SPSS/WIN version 24.0. RESULTS: Patient safety events were reported as follows: 4.60±0.63 for harmful incidents, 4.02±0.82 for no harm incidents, and 3.59±0.97 for near misses. Patient safety event reporting was significantly positively correlated with patient safety culture. Regression analysis showed, factors influencing reports of harmful incidents were ‘feedback and communication about error’, ‘supervisor/manager expectations’ and ‘carrier of hospital’. Factors influencing reports of no harm incidents were ‘feedback and communication about error’. Factors influencing reports on near-misses were ‘teamwork across units’, ‘overall perceptions of safety’, and ‘feedback and communication about error’. CONCLUSION: Findings show that reports of near misses are relatively low and need to be strengthened. These results provide evidence that reporting on patient safety events would be enhanced through improved patient safety culture. Hospital managers could identify factors that affect reporting of each patient safety event and use it to develop intervention programs for risk management.

A combination of early warning score and lactate to predict intensive care unit transfer of inpatients with severe sepsis/septic shock

BACKGROUND/AIMS: The modified early warning score (MEWS) is used to predict patient intensive care unit (ICU) admission and mortality. Lactate (LA) in the blood lactate (BLA) is measured to evaluate disease severity and treatment efficacy in patients with severe sepsis/septic shock. The usefulness of a combination of MEWS and BLA to predict ICU transfer in severe sepsis/septic shock patients is unclear. We evaluated whether use of a combination of MEWS and BLA enhances prediction of ICU transfer and mortality in hospitalized patients with severe sepsis/septic shock. METHODS: Patients with severe sepsis/septic shock who were screened or contacted by a medical emergency team between January 2012 and August 2012 were enrolled at a university-affiliated hospital with ~2,700 beds, including 28 medical ICU beds. RESULTS: One hundred patients were enrolled and the rate of ICU admittance was 38%. MEWS (7.37 vs. 4.85) and BLA concentration (5 mmol/L vs. 2.19 mmol/L) were significantly higher in patients transferred to ICU than those in patients treated in general wards. The combination of MEWS and BLA was more accurate than MEWS alone in terms of ICU transfer (C-statistics: 0.898 vs. 0.816, p = 0.019). The 28-day mortality rate was 19%. MEWS was the only factor significantly associated with 28-day mortality rate (odds ratio, 1.462; 95% confidence interval, 1.122 to 1.905; p = 0.005). CONCLUSIONS: The combination of MEWS and BLA may enhance prediction of ICU transfer in patients with severe sepsis/septic shock.

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

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.