Abstract:
Introduction: MEWS has been developed to ensure timely identification of patients at risk of deterioration and to prevent delay in intervention or transfer of critically ill patients. This score has been evaluated in many settings, but little is known of its applicability to hospitals in low resource settings. The objective of the study is to predict the prognosis of patients admitted to the surgical wards post abdominal surgery using Modified Early Warning Score.
Methods: This was a prospective observational descriptive study for 5 months duration for all patients undergoing abdominal surgery at University Teaching Hospital of Kigali. Patient’s age, gender, MEWS calculation, diagnosis, procedure and comorbidities were recoded. The MEWS was recorded 12 hourly for 72 hours. Complications were recorded during the postoperative hospital stay. The cumulative MEWS score was stratified into 3 categories: high risk (above 7), medium risk (4-6) and low risk (0-3). Regression analysis was used to study the relationship between MEWS and major complications.
Results: During the study period, 177 were enrolled in the study. 110 (62.15%) were male and 67 (37.85%) were female. Mean age was 41.23 years. Emergent operations accounted for 73.45% of operations. Complications were recorded in 26 (14.69%) of patients. 18 (10.17%) patients were admitted to ICU/HDU from wards and unplanned intubation were performed in 1.69% of patients. In-hospital postoperative mortality rate was 6.21%. MEWS ranged from 0 to 14 with a median of 3 on the day one postoperative, from 0 to 10 with a median of 2.85 on the day two postoperative and from 0 to 10 with a median of 2 on the day three postoperative. MEWS was associated with post-operative admission in ICU/HDU (P = 0.000). MEWS was associated with in-hospital postoperative mortality(P = 0.000). Hospital stay extended significantly in relation to increasing MEWS (P= 0.000).
Conclusion: The MEWS can be effectively used in patients admitted in surgical wards in a low resource setting hospitals as an important risk management tool to ensure timely identification of patients at risk of deterioration and to prevent delay in intervention or transfer of critically ill patients.
