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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT04292600
Other study ID # POCKiT
Secondary ID
Status Completed
Phase
First received
Last updated
Start date May 1, 2021
Est. completion date January 31, 2023

Study information

Verified date March 2023
Source POCKiT diagnostics Ltd
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Stroke is the third leading cause of death and the first cause of physical disability and dementia worldwide. Ischemic stroke caused by large vessel occlusion (LVO) is responsible for the vast majority of deaths and disabilities. A very effective and safe treatment, called mechanical thrombectomy (MT) is available for LVO patients. Nevertheless, no blood biomarkers able to identify LVO patients rapidly and to direct them to CT angiography and thrombectomy currently exist. The TIME study is an observational prospective cohort study. All Patients referred to the emergency department or stroke unit with a suspected stroke as identified by paramedics, nurses or clinicians will be enrolled in the study. A panel of blood biomarkers will be analysed retrospectively via standard laboratory assays. The main outcome of the TIME study will be the evaluation of the clinical diagnostic performance of a panel of blood biomarkers, in conjunction with clinical data, for the identification of large vessel occlusion ischemic stroke subtype. This study will allow the identification and evaluation of a final panel of biomarkers and will prompt the development of a test for LVO stroke diagnosis.


Description:

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Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
POCKiT diagnostics' algorithm for LVO detection
Measurement of blood biomarkers and integration within Pockit diagnostics' algorithm for LVO detection

Locations

Country Name City State
United States University of Alabama in Birmingham Comprehensive Stroke Center Birmingham Alabama
United States BAC Telemed - Brandon Regional Hospital Brandon Florida
United States University of Mississippi Medical Center Jackson Mississippi

Sponsors (4)

Lead Sponsor Collaborator
POCKiT diagnostics Ltd Bay Area Consulting Telemedicine, University of Alabama at Birmingham, University of Mississippi Medical Center

Country where clinical trial is conducted

United States, 

References & Publications (3)

Gropen TI, Boehme A, Martin-Schild S, Albright K, Samai A, Pishanidar S, Janjua N, Brandler ES, Levine SR. Derivation and Validation of the Emergency Medical Stroke Assessment and Comparison of Large Vessel Occlusion Scales. J Stroke Cerebrovasc Dis. 2018 Mar;27(3):806-815. doi: 10.1016/j.jstrokecerebrovasdis.2017.10.018. Epub 2017 Nov 22. — View Citation

Malhotra K, Gornbein J, Saver JL. Ischemic Strokes Due to Large-Vessel Occlusions Contribute Disproportionately to Stroke-Related Dependence and Death: A Review. Front Neurol. 2017 Nov 30;8:651. doi: 10.3389/fneur.2017.00651. eCollection 2017. — View Citation

Nogueira RG, Jadhav AP, Haussen DC, Bonafe A, Budzik RF, Bhuva P, Yavagal DR, Ribo M, Cognard C, Hanel RA, Sila CA, Hassan AE, Millan M, Levy EI, Mitchell P, Chen M, English JD, Shah QA, Silver FL, Pereira VM, Mehta BP, Baxter BW, Abraham MG, Cardona P, Veznedaroglu E, Hellinger FR, Feng L, Kirmani JF, Lopes DK, Jankowitz BT, Frankel MR, Costalat V, Vora NA, Yoo AJ, Malik AM, Furlan AJ, Rubiera M, Aghaebrahim A, Olivot JM, Tekle WG, Shields R, Graves T, Lewis RJ, Smith WS, Liebeskind DS, Saver JL, Jovin TG; DAWN Trial Investigators. Thrombectomy 6 to 24 Hours after Stroke with a Mismatch between Deficit and Infarct. N Engl J Med. 2018 Jan 4;378(1):11-21. doi: 10.1056/NEJMoa1706442. Epub 2017 Nov 11. — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Diagnostic accuracy measures for LVO detection vs non-LVO stroke activations Accuracy of pre-defined algorithm thresholds for LVO identification from the population of all suspected strokes (Ischemics non-LVO, Hemorrhagic, Mimics, TIAs) 1 year
Secondary Optimisation of the cut-off points of the diagnostic algorithm for LVO detection Determine optimal cut-off points for diagnostic algorithm for detection of LVO vs non-LVO 1 year
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