A Comparison of the Clinical Characteristics of Short-, Mid-, and Long-Term Mortality in Patients Attended by the Emergency Medical Services: An Observational Study.

AIM: The development of predictive models for patients treated by emergency medical services (EMS) is on the rise in the emergency field. However, how these models evolve over time has not been studied. The objective of the present work is to compare the characteristics of patients who present mortality in the short, medium and long term, and to derive and validate a predictive model for each mortality time. METHODS: A prospective multicenter study was conducted, which included adult patients with unselected acute illness who were treated by EMS. The primary outcome was noncumulative mortality from all causes by time windows including 30-day mortality, 31- to 180-day mortality, and 181- to 365-day mortality. Prehospital predictors included demographic variables, standard vital signs, prehospital laboratory tests, and comorbidities. RESULTS: A total of 4830 patients were enrolled. The noncumulative mortalities at 30, 180, and 365 days were 10.8%, 6.6%, and 3.5%, respectively. The best predictive value was shown for 30-day mortality (AUC = 0.930; 95% CI: 0.919-0.940), followed by 180-day (AUC = 0.852; 95% CI: 0.832-0.871) and 365-day (AUC = 0.806; 95% CI: 0.778-0.833) mortality. DISCUSSION: Rapid characterization of patients at risk of short-, medium-, or long-term mortality could help EMS to improve the treatment of patients suffering from acute illnesses.

Long-Term Mortality in Patients Transferred by Emergency Medical Services: Prospective Cohort Study.

OBJECTIVE: This study aimed to determine the long-term mortality (one-year follow-up) associated with patients transferred by Emergency Medical Services (EMS), and to reveal the determinants (causes and risk factors). METHODS: This was a multicenter, prospective, observational, controlled, ambulance-based study of adult patients transferred by ambulance to emergency departments (EDs) from October 2019 through July 2021 for any cause. A total of six Advanced Life Support (ALS) units, 38 Basic Life Support (BLS) units, and five hospitals from Spain were included. Physiological, biochemical, demographic, and reasons for transfer variables were collected. A longitudinal analysis was performed to determine the factors associated to long-term mortality (any cause). RESULTS: The final cohort included 1,406 patients. The one-year mortality rate was 21.6% (n = 304). Mortality over the first two days reached 5.2% of all the patients; between Day 2 and Day 30, reached 5.3%; and between Day 31 and Day 365, reached 11.1%. Low Glasgow values, elevated lactate levels, elevated blood urea nitrogen (BUN) levels, low oxygen saturation, high respiratory rate, as well as being old and suffering from circulatory diseases and neurological diseases were risk factors for long-term mortality. CONCLUSION: The quick identification of patients at risk of long-term worsening could provide an opportunity to customize care through specific follow-up.

Comparison of seven prehospital early warning scores to predict long-term mortality: a prospective, multicenter, ambulance-based study.

METHODS: A prospective, multicenter, ambulance-based study of adult patients with an acute illness involving six advanced life support units and 38 basic life support units, referring to five emergency departments in Spain. RESULTS: The primary outcome was long-term mortality with a 1-year follow-up. The compared scores included: National Early Warning Score 2, VitalPAC early warning score, modified rapid emergency medicine score (MREMS), Sepsis-related Organ Failure Assessment, Cardiac Arrest Risk Triage Score, Rapid Acute Physiology Score, and Triage Early Warning Score. Discriminative power [area under the receiver operating characteristic curve (AUC)] and decision curve analysis (DCA) were used to compare the scores. Additionally, a Cox regression and Kaplan-Meier method were used. Between 8 October 2019, and 31 July 2021, a total of 2674 patients were selected. The MREMS presented the highest AUC of 0.77 (95% confidence interval, 0.75-0.79), significantly higher than those of the other EWS. It also exhibited the best performance in the DCA and the highest hazard ratio for 1-year mortality [3.56 (2.94-4.31) for MREMS between 9 and 18 points, and 11.71 (7.21-19.02) for MREMS > 18]. CONCLUSION: Among seven tested EWS, the use of the MREMS presented better characteristics to predict 1-year mortality; however, all these scores present moderate performances.