Outcomes of patients presenting to Emergency Department depend on early risk stratification and severity assessment. Traditional scoring systems like APACHE-II require laboratory parameters, making them time-consuming for ED use.

The REMS score is a validated physiological scoring system developed by Olsson et al. (2004) to predict in-hospital mortality in emergency patients REMS offers rapid bedside assessment using readily available physiological parameters REMS incorporates age, vital signs, GCS, and oxygen saturation for comprehensive risk assessment.

OBJECTIVES

Primary Objective-To assess the accuracy of REMS in predicting 30-day outcomes in non-surgical ED patients

Secondary Objectives

• To identify predictive components of REMS
• To evaluate hospital complications according to risk category
• To correlate REMS with length of hospital stay

METHODOLOGY

• Study Design: Prospective observational, single centre, cross-sectional study
• Setting: Emergency Medicine Department, M.G.M Medical College and MY Hospital, Indore
• Sample Size: Initial enrollment: 75 patients; Final analysis: 70 patients (7% dropout)

Gender Distribution: Males: 37 , Females: 33

Inclusion Criteria

Adult patients (≥18 years) presenting to Emergency Department

Non-trauma, non-surgical emergency medical admissions

Patients with complete vital sign documentation within 15-20 minutes of arrival

Patients willing to participate with informed consent obtained

Exclusion Criteria

Patients with traumatic injuries

Patients planned for immediate surgical intervention

Cardiac arrest patients unresponsive to cardiopulmonary resuscitation

Patients transferred from other hospitals

Procedure

REMS parameters recorded by trained emergency medicine resident within 15- 20 minutes of ED arrival

Variables assessed: Age, HR, RR, MAP, GCS, SpO₂, body temperature

Patients stratified into low, moderate, and high-risk categories based on REMS

30-day outcomes monitored: mortality, hospital complications, discharge status, length of stay

REMS SCORING SYSTEM

Total Score Range: 0-26 points

Risk Stratification:

• Low (<6)
• Moderate (6-13)
• High (>13)

RESULTS

Study Population (n=70)

Mean Age: 59.2 ± 19.9 years

(Range: 18-95 years)

Gender distribution shows near-equal representation with slight male predominance, 37 (52.9%) vs 33( 47.1%)

Mean REMS: 4.5 ± 3.3

Figure 1: Gender Distribution of Study Population

Table 1: REMS Risk Category Distribution

Figure 2: REMS Risk Category Distribution

Table 2: REMS vs 30-Day Mortality Outcomes

Table 3: Comprehensive Clinical Outcomes by REMS Risk Category

Table 4: Regression Analysis - Predictors of REMS and Outcomes

Figure 5: Regression p-p Plot - REMS Effect on Hospital Length of Stay

Strong linear relationship between REMS score and hospital length of stay.

Each unit increase in REMS prolongs hospitalization by 12% (p=0.001).

DISCUSSION

REMS demonstrated significant predictive value for 30-day mortality in non-trauma ED patients with an overall mortality of 12.9%. Strong risk stratification: Low-risk (0% mortality), Moderate-risk (9.1%), High-risk (66.7%) with p<0.001. Strong correlation between REMS score and 30-day mortality demonstrated; low-risk patients had 0% mortality vs 66.7% in the high-risk group. Progressive mortality escalation across risk categories supports REMS as a reliable triage tool in ED setting. High-risk REMS patients had significantly higher ICU admission rates (89% vs 7% in low-risk), validating clinical decision-making

Hospital Resource Allocation: Length of stay directly correlated with REMS category; high-risk patients required prolonged hospitalisation (8.9 ± 4.1 days). Age, heart rate, and respiratory rate positively correlated with REMS, while SpO₂ and GCS showed a negative correlation

Clinical Complications: 78% of high-risk patients experienced acute complications vs 3.6% in the low-risk group. Each unit increase in REMS is associated with a progressive increment in adverse outcomes and mortality. Clinical Implications: REMS score should guide admission decisions, resource allocation, and early therapeutic interventions in non-trauma ED patients

REFERENCES

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