Quantifying the Benefit of Prehospital Rapid Treatment in Acute Stroke

Modeling the potential efficiency of a blood biomarker-based tool to guide pre-hospital thrombolytic therapy in stroke patients

OBJECTIVES

Stroke treatment with intravenous tissue-type plasminogen activator (tPA) is effective and efficient, but as its benefits are highly time dependent, it is essential to treat the patient promptly after symptom onset. This study evaluates the cost-effectiveness of a blood biomarker test to differentiate ischemic and hemorrhagic stroke to guide pre-hospital treatment with tPA in patients with suspected stroke, compared with standard hospital management. The standard care for patients suffering stroke consists mainly in diagnosis, treatment, hospitalization and monitoring.

METHODS

A Markov model was built with four health states according to the modified Rankin scale, in adult patients with suspected moderate to severe stroke (NIHSS 4-22) within 4.5 hours after symptom onset. A Spanish Health System perspective was used. The time horizon was 15 years. Quality-adjusted life-years (QALYs) and life-years gained (LYGs) were used as a measure of effectiveness. Short- and long-term direct health costs were included. Costs were expressed in Euros (2022). A discount rate of 3% was used. Probabilistic sensitivity analysis and several one-way sensitivity analyses were conducted.

RESULTS

The use of a blood-test biomarker compared with standard care was associated with more QALYs (4.87 vs. 4.77), more LYGs (7.18 vs. 7.07), and greater costs (12,807€ vs. 12,713€). The ICER was 881€/QALY. Probabilistic sensitivity analysis showed that the biomarker test was cost-effective in 82% of iterations using a threshold of 24,000€/QALY.

CONCLUSIONS

The use of a blood biomarker test to guide pre-hospital thrombolysis is cost-effective compared with standard hospital care in patients with ischemic stroke.

Diagnostic Accuracy of Glial Fibrillary Acidic Protein and Ubiquitin Carboxy-Terminal Hydrolase-L1 Serum Concentrations for Differentiating Acute Intracerebral Hemorrhage from Ischemic Stroke

BACKGROUND

Biomarkers indicative of intracerebral hemorrhage (ICH) may help triage acute stroke patients in the pre-hospital phase. We hypothesized that serum concentration of glial fibrillary acidic protein (GFAP) in combination with ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1), measured by a rapid bio-assay, could be used to distinguish ICH from ischemic stroke.

METHODS

This prospective two-center study recruited patients with a clinical diagnosis of acute stroke both in the pre-hospital phase and at hospital admission (within 4 and 6 h after symptom onset, respectively). Blood samples were analyzed for concentrations of GFAP and UCH-L1 using ELISA techniques. The reference standard was the diagnosis of ICH, ischemic stroke, or stroke mimicking condition achieved after clinical workup including brain imaging.

RESULTS

A total of 251 patients were included (mean age [± SD] 72 ± 15 years; 5 ICH, 23 ischemic strokes and 14 stroke mimics in the pre-hospital part; and 59 ICH, 148 ischemic strokes and 2 stroke mimics in the in-hospital part). Mean delay (± SD) from symptom onset to blood withdrawal was 130 ± 79 min for the pre-hospital patients and 136 ± 86 min for the in-hospital patients. Both GFAP and UCH-L1 serum concentrations were higher in patients having ICH as compared to other diagnoses (GFAP: median 330 ng/L [interquartile range 64-7060, range 8-56,100] vs. 27.5 ng/L [14-57.25, 0-781], p < 0.001; UCH-L1: 401 ng/L [265-764, 133-1812] vs. 338 ng/L [213-549.5, 0-2950], p = 0.025). Area-under-the-curve values were 0.866 (95% CI 0.809-0.924, p < 0.001) for GFAP, and 0.590 (0.511-0.670, p = 0.033) for UCH-L1. Regarding overall diagnostic accuracy, UCH-L1 did not add significantly to the performance of GFAP.

CONCLUSIONS

GFAP may differentiate ICH from ischemic stroke and stroke mimics. A point-of-care test to distinguish between ischemic and hemorrhagic strokes might facilitate triage to different treatment pathways or locations, or be used to select patients for trials of ultra-early interventions.

Re-Evaluating Stroke Systems of Care: Association of Transfer Status With Thrombectomy Outcomes at an Urban Comprehensive Stroke Center

Introduction Given the efficacy of mechanical thrombectomies (MT) for large vessel occlusions (LVO), there is concern that the Hub and Spoke model of stroke care, which prioritizes initial assessment of the acute ischemic stroke (AIS) patient at a primary stroke center, would cause a delay in arterial reperfusion, thus leading to worse outcomes. In this study that occurred at our comprehensive stroke center in New York, we compared the clinical outcomes of patients that were either directly admitted for thrombectomy versus those who were transferred from another institution. Methods Retrospective review of the electronic medical record (EMR) was performed on all adult patients treated with endovascular therapy for ischemic stroke between January 2016 and February 2020. A bivariate analysis was performed to compare patients in the direct admit versus transfer group. A multivariable logistic regression model was developed to determine which factors affect 90-day modified Rankin score (mRS) and to evaluate if transfer status was an independent predictor in this model. Results Three hundred and twenty-five patients were included in this study; 127 patients belonged to the direct admit group while 198 were in the transfer group. Thirteen patients (20%) in the direct admit group had a 90-day mRS score of 0-2 and so did 29 patients (25.2%) in the transfer group; thus, no statistically significant difference found in clinical outcomes between both groups (p-value = 0.427). In a multivariable logistic regression model that accounts for age, gender, smoking status, baseline mRS, presenting National Institute of Health Stroke Scale (NIHSS), procedure duration, thrombolysis in cerebral infarction (TICI) score, post-NIHSS and decompressive hemicraniectomy, transfer status was not found to be predictive of clinical outcomes (OR 0.727 95% CI 0.349-1.516; p-value = 0.396).  Conclusion Transfer status is not significantly associated with 90-day outcome. Since Hub and Spoke is not associated with worse outcomes compared to direct admit, it remains a viable model for providing effective care to stroke patients in an urban setting.

Blood Biomarkers to Differentiate Ischemic and Hemorrhagic Strokes

OBJECTIVE

To validate a panel of blood biomarkers to differentiate between ischemic stroke (IS) and intracerebral hemorrhage (ICH) in patients with suspected stroke.

METHODS

Patients with suspected stroke admitted within 4.5 hours after onset were enrolled. Blood samples were collected at hospital admission. Glial fibrillary acid protein (GFAP), retinol binding protein 4 (RBP-4), N-terminal proB-type natriuretic peptide (NT-proBNP), and endostatin were measured by immunoassays. Cutoff points were obtained for 100% specificity for IS. A high-sensitivity assay to measure GFAP and rapid point-of-care tests (POCTs) to measure RBP-4 and NT-proBNP were used in subsets of patients. Biomarker panels were evaluated in another cohort of 62 stroke mimics.

RESULTS

A total of 189 patients (154 IS and 35 ICH) were enrolled. Patients with IS had higher RBP-4, NT-proBNP, and endostatin and lower GFAP levels than patients with ICH. The best biomarker combination for the identification of IS was RBP-4+NT-proBNP, which was able to identify 29.7% of patients with IS with 100% specificity. In the subset of patients for whom GFAP was measured with the high-sensitivity assay, RBP-4, NT-proBNP, and GFAP identified 51.5% of patients with IS with 100% specificity. When stroke mimics were included, specificities were reduced to 98.4 and 96.8%, respectively. POCTs of RBP-4 and NT-proBNP showed results similar results to those of conventional ELISAs.

CONCLUSIONS

A biomarker panel including RBP-4, NT-proBNP, and GFAP provided moderate but potentially useful sensitivity rates at 100% specificity for IS diagnosis. If confirmed in future studies, this strategy might allow prehospital treatment in selected patients.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that a biomarker panel including RBP-4, NT-proBNP, and GFAP distinguishes IS from ICH with moderate accuracy.

Monogenic, Polygenic, and MicroRNA Markers for Ischemic Stroke

Ischemic stroke (IS) is a leading disease with high mortality and disability, as well as with limited therapeutic window. Biomarkers for earlier diagnosis of IS have long been pursued. Family and twin studies confirm that genetic variations play an important role in IS pathogenesis. Besides DNA mutations found previously by genetic linkage analysis for monogenic IS (Mendelian inheritance), recent studies using genome-wide associated study (GWAS) and microRNA expression profiling have resulted in a large number of DNA and microRNA biomarkers in polygenic IS (sporadic IS), especially in different IS subtypes and imaging phenotypes. The present review summarizes genetic markers discovered by clinical studies and discusses their pathogenic molecular mechanisms involved in developmental or regenerative anomalies of blood vessel walls, neuronal apoptosis, excitotoxic death, inflammation, neurogenesis, and angiogenesis. The possible impact of environment on genetics is addressed as well. We also include a perspective on further studies and clinical application of these IS biomarkers.

Glial fibrillary acidic protein for the early diagnosis of intracerebral hemorrhage: Systematic review and meta-analysis of diagnostic test accuracy

Background and aims

Glial fibrillary acidic protein (GFAP) has shown promise in several studies for its ability to diagnose intracerebral hemorrhage (ICH). We evaluated the diagnostic accuracy of blood GFAP level to differentiate (ICH) from acute ischemic stroke (AIS) and stroke mimics, both overall, and in the first three hours after symptom onset.

Methods

We searched multiple databases, without language restriction, from inception until December 2017. Hierarchical summary receiver operating characteristic (HSROC) modeling was used to meta-analyze results. We conducted subgroup analyses restricted to blood samples collected within 0–60, 60–120, and 120–180 min time groups after symptom onset, to evaluate diagnostic accuracy in the early pre-hospital phase. Between and within study heterogeneity was explored using meta-regression.

Results

The search identified 199 potentially relevant citations from which 11 studies involving 1297 participants (350 ICH, 947 AIS, or mimic) were included. The pooled sensitivity, specificity, and area under the HSROC curve were 0.756 (95% CI 0.630–0.849), 0.945 (95% CI 0.858–0.980), and 0.904 (95% CI 0.878–0.931), respectively. Differences in assays used, but not the other covariates, partially explained between-study heterogeneity ( p = 0.034). The summary estimates for the 0–60, 60–120, and 120–180 min subgroups were comparable to the primary analysis and there was no statistically significant difference in diagnostic accuracy between subgroups.

Conclusions

GFAP is a promising diagnostic biomarker for ICH diagnosis in the early pre-hospital phase. Test accuracy is affected by assay subtype, but there are still unexplained sources of heterogeneity. High quality, international multi-center trials are warranted to develop and validate a point-of-care GFAP assay for the rapid triage and evaluation of acute stroke in the pre-hospital setting.

Time Gain Needed for In-Ambulance Telemedicine: Cost-Utility Model

Background

Stroke is a very time-sensitive pathology, and many new solutions target the optimization of prehospital stroke care to improve the stroke management process. In-ambulance telemedicine, defined by live bidirectional audio-video between a patient and a neurologist in a moving ambulance and the automated transfer of vital parameters, is a promising new approach to speed up and improve the quality of acute stroke care. Currently, no evidence exists on the cost effectiveness of in-ambulance telemedicine.

Objective

We aim to develop a first cost effectiveness model for in-ambulance telemedicine and use this model to estimate the time savings needed before in-ambulance telemedicine becomes cost effective.

Methods

Current standard stroke care is compared with current standard stroke care supplemented with in-ambulance telemedicine using a cost-utility model measuring costs and quality-adjusted life-years (QALYs) from a health care perspective. We combine a decision tree with a Markov model. Data from the UZ Brussel Stroke Registry (2282 stroke patients) and linked hospital claims data at individual level are combined with literature data to populate the model. A 2-way sensitivity analysis varying both implementation costs and time gain is performed to map the different cost-effective combinations and identify the time gain needed for cost effectiveness and dominance. For several modeled time gains, the cost-effectiveness acceptability curve is calculated and mapped in 1 figure.

Results

Under the base-case scenario (implementation cost of US $159,425) and taking a lifetime horizon into account, in-ambulance telemedicine is a cost-effective strategy compared to standard stroke care alone starting from a time gain of 6 minutes. After 12 minutes, in-ambulance telemedicine becomes dominant, and this results in a mean decrease of costs by US –$30 (95% CI –$32 to –$29) per patient with 0.00456 (95% CI 0.00448 to 0.00463) QALYs on average gained per patient. In over 82% of all probabilistic simulations, in-ambulance telemedicine remains under the cost-effectiveness threshold of US $47,747.

Conclusions

Our model suggests that in-ambulance telemedicine can be cost effective starting from a time gain of 6 minutes and becomes a dominant strategy after approximately 15 minutes. This indicates that in-ambulance telemedicine has the potential to become a cost-effective intervention assuming time gains in clinical implementations are realized in the future.

Ultra-acute diagnostics for stroke: Large-scale implementation of prehospital biomarker sampling

OBJECTIVES

Blood-based biomarkers could enable early and cost-effective diagnostics for acute stroke patients in the prehospital setting to support early initiation of treatments. To facilitate development of ultra-acute biomarkers, we set out to implement large-scale prehospital blood sampling and determine feasibility and diagnostic timesavings of this approach.

MATERIALS AND METHODS

Emergency medical services (EMS) personnel of the Helsinki metropolitan area were trained to collect prehospital blood samples from thrombolysis candidates using a cannula adapter technique. Time delays, sample quality, and logistics were investigated between May 20, 2013 and May 19, 2014.

RESULTS

Prehospital blood sampling and study recruiting were successfully performed for 430 thrombolysis candidates, of which 50% had ischemic stroke, 14.4% TIA, 13.5% hemorrhagic stroke, and 22.1% stroke mimics. A total of 66.3% of all samples were collected during non-office hours. The median (interquartile range) emergency call to prehospital sample time was 33 minutes (25-41), and the median time from reported symptom onset or wake-up to prehospital sample was 53 minutes (38-85; n=394). Prehospital sampling was performed 31 minutes (25-42) earlier than hospital admission blood sampling and 37 minutes (30-47) earlier than admission neuroimaging. Hemolysis rate in serum and plasma samples was 6.5% and 9.3% for EMS samples, and 0.7% and 1.6% for admission samples.

CONCLUSIONS

Prehospital biomarker sampling can be implemented in all EMS units and provides a median timesaving of more than 30 minutes to first blood sample. Large prehospital sample sets will enable development of novel ambulance biomarkers to improve early differential diagnosis and treatment of thrombolysis candidates.

Glial Fibrillary Acidic Protein Serum Levels Distinguish between Intracerebral Hemorrhage and Cerebral Ischemia in the Early Phase of Stroke

BACKGROUND

Recent studies have suggested that glial fibrillary acidic protein (GFAP) serum concentrations distinguish between intracerebral hemorrhage (ICH) and ischemic stroke (IS) shortly after symptom onset. In this prospective multicenter trial we validated GFAP in an independent patient cohort and assessed the quantitative relationship between GFAP release, bleeding size, and localization.

METHODS

We included patients with a persistent neurological deficit (NIH Stroke Scale ≥4) suggestive of stroke within 6 h of symptom onset. Blood samples were drawn at hospital admission. GFAP serum concentrations were measured using an electrochemiluminometric immunoassay. Primary endpoint was the final diagnosis established at hospital discharge (ICH, IS, or stroke mimic).

RESULTS

202 patients were included (45 with ICH, 146 with IS, 11 stroke mimics). GFAP concentrations were significantly higher in ICH than in IS patients [median (interquartile range) 0.16 μg/L (0.04-3.27) vs 0.01 μg/L (0.01-0.01), P <0.001]. A GFAP cutoff of 0.03 μg/L provided a sensitivity of 77.8% and a specificity of 94.2% in distinguishing ICH from IS and stroke mimics [ROC analysis area under the curve 0.872 (95% CI, 0.802-0.942), P <0.001]. GFAP serum concentrations were positively correlated with ICH volume. Lobar ICH volumes were larger and thus associated with higher GFAP concentrations as compared to deep ICH.

CONCLUSIONS

Serum GFAP was confirmed to be a biomarker indicating ICH in patients presenting with acute stroke symptoms. Very small ICH may be missed owing to less tissue destruction.