Initial Emergency Room Triage of Acute Ischemic Stroke

The impact on clinical outcomes after 1 year of implementation of an artificial intelligence solution for the detection of intracranial hemorrhage

BACKGROUND

To assess the effect of a commercial artificial intelligence (AI) solution implementation in the emergency department on clinical outcomes in a single level 1 trauma center.

METHODS

A retrospective cohort study for two time periods-pre-AI (1.1.2017-1.1.2018) and post-AI (1.1.2019-1.1.2020)-in a level 1 trauma center was performed. The ICH algorithm was applied to 587 consecutive patients with a confirmed diagnosis of ICH on head CT upon admission to the emergency department. Study variables included demographics, patient outcomes, and imaging data. Participants admitted to the emergency department during the same time periods for other acute diagnoses (ischemic stroke (IS) and myocardial infarction (MI)) served as control groups. Primary outcomes were 30- and 120-day all-cause mortality. The secondary outcome was morbidity based on Modified Rankin Scale for Neurologic Disability (mRS) at discharge.

RESULTS

Five hundred eighty-seven participants (289 pre-AI-age 71 ± 1, 169 men; 298 post-AI-age 69 ± 1, 187 men) with ICH were eligible for the analyzed period. Demographics, comorbidities, Emergency Severity Score, type of ICH, and length of stay were not significantly different between the two time periods. The 30- and 120-day all-cause mortality were significantly reduced in the post-AI group when compared to the pre-AI group (27.7% vs 17.5%; p = 0.004 and 31.8% vs 21.7%; p = 0.017, respectively). Modified Rankin Scale (mRS) at discharge was significantly reduced post-AI implementation (3.2 vs 2.8; p = 0.044).

CONCLUSION

The added value of this study emphasizes the introduction of artificial intelligence (AI) computer-aided triage and prioritization software in an emergent care setting that demonstrated a significant reduction in a 30- and 120-day all-cause mortality and morbidity for patients diagnosed with intracranial hemorrhage (ICH). Along with mortality rates, the AI software was associated with a significant reduction in the Modified Ranking Scale (mRs).

Radio frequency identification technology reduce intravenous thrombolysis time in acute ischemic stroke

PURPOSE

To inspect whether time management with radio frequency identification technology (RFID) reduces symptom onset-to-intravenous thrombolysis time (OTT) in acute ischemic stroke (AIS).

METHODS

In the retrospective study, patients with AIS, transferred by Emergency Medical Services (EMS) to Hunan Provincial People's Hospital between September 2019 to June 2022, divided into three groups, as traditional group, in-hospital RFID group and whole process RFID group. Baseline characteristics and time metrics were compared.

RESULTS

After the whole emergency process applied with RFID time management, Door to intravenous thrombolysis time (DNT) was reduced from 125.00±43.16 min to 32.59±25.45 min (F = 121.857, p<0.001), and OTT was reduced from 235.53±57.27 min to 144.31±47.96 min (F = 10.377, p<0.001).

CONCLUSIONS

Time management with RFID is effective in reducing OTT in AIS patients with thrombolysis treatment.

Rapid Risk Stratification of Acute Ischemic Stroke Patients in the Emergency Department: The Incremental Prognostic Role of Left Atrial Reservoir Strain

OBJECTIVES

To determine the prognostic value of positive global left atrial strain (LA-GSA+), measured by two-dimensional speckle tracking echocardiography (2D-STE) in a population of acute ischemic stroke (AIS) patients without atrial fibrillation (AF), in the setting of Emergency Department (ED).

METHODS

All consecutive AIS patients with sinus rhythm on ECG and without AF history entered this prospective study. All patients underwent complete blood tests and transthoracic echocardiography implemented with 2D-STE analysis of LA strain parameters within 6-12 h after symptoms onset. At 6-months follow-up, we evaluated the composite endpoint of all-cause mortality plus cardiovascular re-hospitalizations.

RESULTS

A total of 102 AIS patients (76.4 ± 10.8 yrs, 47% males) were prospectively included. LA-GSA+ was markedly reduced in AIS patients (20.8 ± 7.7%), without any statistically significant difference between the stroke subtypes. At 6-months follow-up, 7 deaths and 27 re-hospitalizations occurred. On multivariate Cox regression analysis, variables independently associated with outcome were: LA-GSA+ (per unit) (HR 0.29, 95% CI 0.19-0.39) and C-reactive protein (CRP) (per 0.1 mg/dl) (HR 1.45, 95% CI 1.15-1.75) as continuous variables; statin therapy (HR 0.45, 95%CI 0.28-0.62), and type 2 diabetes (HR 1.65, 95% CI 1.15-2.35) as categorical variables. A LA-GSA+ ≤20.0% predicted the occurrence of the above-mentioned outcome at 6-months follow-up with 94% sensitivity and 81% specificity (AUC=0.84). Interestingly, GSA+ showed a strong inverse correlation with CRP levels (r = -0.86).

CONCLUSIONS

A LA-GSA+ ≤20% reflects a more advanced atrial cardiomyopathy and might provide a rapid and reliable prognostic risk stratification of AIS patients without AF history in the setting of ED.