Gestalt clinical severity score (GCSS) as a predictor of patient severity of illness or injury

• Published in: The American journal of emergency medicine Vol. 66; pp. 11 - 15
• Main Authors: Shiber, Joseph, Fontane, Emily, Patel, Jignesh, Akinleye, Adeolu, Kerwin, Andy, Chiu, William, Scalea, Thomas
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.04.2023; Elsevier Limited
• Subjects: Accuracy; Adolescent; Adult; Age groups; Decision making; Emergency communications systems; Emergency medical care; Emergency medical services; Emergency Service, Hospital; Gender; Gestalt; Hospitalization; Humans; Illnesses; Injury and illness; Injury Severity Score; Mechanical ventilation; Medical prognosis; Patient Acuity; Patients; Pediatrics; Physical restraints; Physicians; Pilot Projects; Regression analysis; Retrospective Studies; Severity scoring; Trauma; Trauma Centers; Variables; Vital signs; Young Adult; Gestalt; Severity scoring; Injury and illness
• ISSN: 0735-6757; 1532-8171
• DOI: 10.1016/j.ajem.2023.01.005

To determine if clinical judgement is accurate to predict the severity of injury or illness, and can be used at patient arrival when other formal scoring systems are not yet available. A multicenter pilot study using a prospective observational convenience sample of patients arriving by EMS to the emergency department (ED) or Trauma Center. Two urban, Level 1 trauma centers at academic tertiary care hospitals. Medical and trauma patients age 18 and older transported by EMS (N = 216). Exclusion criteria (prior to arrival): intubation, assisted ventilation (BVM or NPPV), CPR in progress, prisoners, or previously present motor or speech deficits. Completion of a novel 15-point scale of Verbal, Motor, and Facial Expression within 1–2 min of arrival by a clinician outside of the treatment team. Primary endpoint was the immediate disposition from the ED or Trauma Center: Home, Brief Observation (<24 h), Admission to Floor, ICU (OR and IR as surrogates since these patients ultimately go to the ICU), or Morgue. Univariate analysis revealed a strong, positive monotonic correlation between GCSS and disposition (Rho = 0.693, p < .0001). Multivariable logistic regression revealed the “best” model included GCSS and age (group 18–44 years old versus all the other age groups) (p < .0001). There was a 156% increase in the odds of being discharged home (versus being admitted) for a one-unit increase in GCSS (OR = 2.56, 95% CI 1.94, 3.37). Physicians can make accurate predictions of severity of injury and illness using a gestalt method and the scoring system we have developed as patient disposition correlates well with GCSS score. GCSS is most accurate with the 18–44 age group. •Disposition correlates well with our GCSS score.•GCSS is most accurate with the 18–44 age group.•Age > 44 years increases the likelihood of admission.•Confounding factors are intoxication and dementia.•Need to validate scoring with larger study and determine if level of training influences accuracy.