Comparison of qSOFA, MEWS and NEWS Score for Diagnosis and Prediction of Mortality in Sepsis in a LMIC settings

Sepsis is a terrifying medical emergency where the body's own defense system turns against itself in response to an infection. Instead of fighting a specific germ, the immune system goes into overdrive, causing inflammation that damages healthy tissues and organs. This cascade can lead to organ failure and a dangerous drop in blood pressure, often killing patients within hours if not treated immediately. Because the window for effective treatment is so narrow, doctors rely on simple bedside tools to spot the danger early. These tools are essentially checklists that assign points based on vital signs like heart rate, breathing speed, temperature, and mental clarity. The higher the score, the sicker the patient appears to be. While these scoring systems have been tested extensively in wealthy nations with advanced hospitals, it has remained unclear whether they work just as well in lower-income countries, where resources are scarcer and patient populations may differ.

In a recent study conducted at a major hospital in Dhaka, Bangladesh, a team of researchers set out to test three of these common scoring systems to see which one best predicts who will get sepsis and who will survive it. The study took place over a year and a half, involving 142 patients who were suspected of having sepsis upon arrival. The researchers did not just look at the patients' charts; they calculated three different scores for every single person right at the moment they were admitted. One score, called qSOFA, is a very quick check focusing on just three things: breathing rate, blood pressure, and mental status. Another, known as MEWS, looks at six different physical signs, including urine output and consciousness. The third, NEWS, is the most detailed, tracking seven variables that include oxygen levels and whether the patient needs extra oxygen to breathe. The team then followed these patients for a week or until they were discharged to see who developed sepsis and, tragically, who died.

The results painted a clear picture of how these tools perform in a real-world setting in South Asia. The researchers found that the patients who actually had sepsis were significantly older, more likely to be male, and more likely to be smokers than those who did not. When the team compared the scores, they saw that patients with sepsis had much higher numbers across the board than those without. However, the key discovery was about which tool was the best at its specific job. For the task of simply diagnosing sepsis—telling a doctor, "This person has the condition"—the NEWS score proved to be the most accurate. It correctly identified the vast majority of sepsis cases while rarely mislabeling healthy people as sick. The researchers found that a NEWS score of eight or higher was the sweet spot for making this diagnosis in their hospital.

When the focus shifted to predicting who would not survive, the story changed slightly. While all three scores were able to distinguish between those who lived and those who died, the MEWS score emerged as the superior tool for forecasting mortality. Patients who died had significantly higher MEWS scores than those who survived, and this score provided the most reliable overall accuracy for predicting the outcome. The study suggests that while the quick and simple qSOFA score is good at catching a wide net of potential cases, it often flags people who are not actually in danger, which can lead to unnecessary treatments. In contrast, the more detailed NEWS score is better at confirming the diagnosis, and the MEWS score is the most trustworthy guide for understanding the severity of the situation and the likelihood of survival.

The authors emphasize that these findings are specific to their hospital setting and the patients they treated. They noted that their study had limitations, such as the fact that they only calculated the scores once at the beginning of the hospital stay and did not track how the numbers changed over time. They also acknowledged that their sample size was relatively small and came from a single location, which means the results might look different in a rural clinic or a different country. Despite these constraints, the work provides a crucial piece of the puzzle for doctors working in resource-limited environments. It suggests that there is no single "perfect" score for every situation; instead, the best choice depends on the goal. If the priority is to catch every possible case of sepsis early, the NEWS system offers the best balance of accuracy. If the goal is to understand which patients are at the highest risk of dying so that care can be prioritized, the MEWS system appears to be the most effective guide. Ultimately, the study reinforces the need to test these tools in local contexts rather than assuming that a system designed for one part of the world will work exactly the same way everywhere else.