Predictive value of modified early warning score in identifying high-risk postoperative patients following abdominal surgery

Background: Modified Early Warning Score (MEWS) is an objective bedside tool for detecting early physiological deterioration and guiding timely intervention. Its predictive role in postoperative general surgical patients, particularly after exploratory laparotomy, is underexplored in developing countries. Methods: A prospective observational study was conducted from July 2019 to June 2020 in a tertiary care center. A total of 150 patients undergoing exploratory laparotomy were included. MEWS was calculated using six parameters respiratory rate, systolic blood pressure, heart rate, temperature, urine output and consciousness level at 6-hour intervals postoperatively. Patients were categorized into low-risk (0-2), intermediate-risk (3-4) and high-risk (≥5) groups. Outcomes analyzed included ICU admission and mortality. Results: The mean age of patients was 41.8 years; 50.7% were male. Emergency surgeries constituted 58.7% of cases. MEWS≥5 was present in 23.4% of patients. All six deaths occurred in patients with MEWS≥7 (p<0.001). ICU admission was significantly associated with higher MEWS. MEWS showed strong predictive accuracy for morbidity and mortality in postoperative patients. Conclusions: MEWS is a simple, inexpensive and effective tool for early detection of postoperative deterioration and prioritizing ICU transfer. Higher MEWS strongly correlated with mortality and adverse outcomes.

Authors

Institutions

Publication Details

Journal
International Surgery Journal
Published
2025-09-25
DOI
https://doi.org/10.18203/2349-2902.isj20253019
Primary Topic
Cardiac, Anesthesia and Surgical Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive value of modified early warning score in identifying high-risk postoperative patients following abdominal surgery

Shraddha Patel, Darshan Patel, Hardik Astik, Divyang Dave et al.
International Surgery Journal
Cardiac, Anesthesia and Surgical Outcomes
article

Predictive value of modified early warning score in identifying high-risk postoperative patients following abdominal surgery

Shraddha Patel, Darshan Patel, Hardik Astik, Divyang Dave, Nipun Bansal, Ojas Patel, Varun Joshi
article en

Abstract

Background: Modified Early Warning Score (MEWS) is an objective bedside tool for detecting early physiological deterioration and guiding timely intervention. Its predictive role in postoperative general surgical patients, particularly after exploratory laparotomy, is underexplored in developing countries. Methods: A prospective observational study was conducted from July 2019 to June 2020 in a tertiary care center. A total of 150 patients undergoing exploratory laparotomy were included. MEWS was calculated using six parameters respiratory rate, systolic blood pressure, heart rate, temperature, urine output and consciousness level at 6-hour intervals postoperatively. Patients were categorized into low-risk (0-2), intermediate-risk (3-4) and high-risk (≥5) groups. Outcomes analyzed included ICU admission and mortality. Results: The mean age of patients was 41.8 years; 50.7% were male. Emergency surgeries constituted 58.7% of cases. MEWS≥5 was present in 23.4% of patients. All six deaths occurred in patients with MEWS≥7 (p<0.001). ICU admission was significantly associated with higher MEWS. MEWS showed strong predictive accuracy for morbidity and mortality in postoperative patients. Conclusions: MEWS is a simple, inexpensive and effective tool for early detection of postoperative deterioration and prioritizing ICU transfer. Higher MEWS strongly correlated with mortality and adverse outcomes.

International Surgery JournalVol. 12(10)
Government Medical College (IN)
Openalex Percentile: Top 60%
Cardiac, Anesthesia and Surgical Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.