Background: Emergency department (ED) presentations after a ground-level fall (GLF) are common. Falls were suggested to be another possible presenting feature of a myocardial infarction (MI), as unrecognized MIs are common in older adults. Elevated high-sensitivity cardiac troponin (hs-cTn) concentrations could help determine the etiology of a GLF in ED. We investigated the prevalence of both MI and elevated high-sensitivity cardiac troponin T (hs-cTnT) and I (hs-cTnI), as well as the diagnostic accuracy of hs-cTnT and hs-cTnI regarding MI, and their prognostic value in older ED patients presenting after a GLF.
Methods: This was a prospective, international, multicenter, cohort study with a follow-up of up to 1 year. Patients aged 65 years or older presenting to the ED after a GLF were prospectively enrolled. Two outcome assessors independently reviewed all discharge records to ascertain final gold standard diagnoses. Hs-cTnT and hs-cTnI levels were determined from thawed samples for every patient.
Results: In total, 558 patients were included. Median (IQR) age was 83 (77-89) years, and 67.7% were female. Elevated hs-cTnT levels were found in 384 (68.8%) patients, and elevated hs-cTnI levels in 86 (15.4%) patients. Three patients (0.5%) were ascertained the gold standard diagnosis MI. Within 30 days, 18 (3.2%) patients had died. Nonsurvivors had higher hs-cTnT and hs-cTnI levels compared with survivors (hs-cTnT 40 [23-85] ng/L in nonsurvivors and 20 [13-33] ng/L in survivors; hs-cTnI 25 [14-54] ng/L in nonsurvivors and 8 [4-16] ng/L in survivors; p < 0.001 for both).
Conclusions: A majority of patients (n = 364, 68.8%) presenting to the ED after a fall had elevated hs-cTnT levels and 86 (15.4%) elevated hs-cTnI levels. However, the incidence of MI in these patients was low (n = 3, 0.5%). Our data do not support the opinion that falls may be a common presenting feature of MI. We discourage routine troponin testing in this population. However, hs-cTnT and hs-cTnI were both found to have prognostic properties for mortality prediction up to 1 year.