Monocyte-to-Lymphocyte Ratio in Clot Analysis as a Marker of Cardioembolic Stroke Etiology.
Diagnosis
Embolic stroke
Flow cytometry
Intracranial embolism
Stroke
Thrombectomy
Journal
Translational stroke research
ISSN: 1868-601X
Titre abrégé: Transl Stroke Res
Pays: United States
ID NLM: 101517297
Informations de publication
Date de publication:
12 2022
12 2022
Historique:
received:
23
02
2021
accepted:
10
09
2021
revised:
01
09
2021
pubmed:
30
9
2021
medline:
1
11
2022
entrez:
29
9
2021
Statut:
ppublish
Résumé
The aim of the study was to find markers of high-risk cardioembolic etiology (HRCE) in patients with cryptogenic strokes (CS) through the analysis of intracranial clot by flow cytometry (FC). A prospective single-center study was designed including patients with large vessel occlusion strokes. The percentage of granulocytes, monocytes, lymphocytes, and monocyte-to-lymphocyte ratio (MLr) were analyzed in clots extracted after endovascular treatment (EVT) and in peripheral blood. Large arterial atherosclerosis (LAA) strokes and high-risk cardioembolic (HRCE) strokes were matched by demographics and acute reperfusion treatment data to obtain FC predictors for HRCE. Multilevel decision tree with boosting random forest classifiers was performed with each feature importance for HRCE diagnosis among CS. We tested the validity of the best FC predictor in a cohort of CS that underwent extensive diagnostic workup. Among 211 patients, 178 cases underwent per-protocol workup. The percentage of monocytes (OR 1.06, 95% CI 1.01-1.11) and MLr (OR 1.83, 95% CI 1.12-2.98) independently predicted HRCE diagnosis when LAA clots (n = 28) were matched with HRCE clots (n = 28). Among CS (n = 82), MLr was the feature with the highest weighted importance in the multilevel decision tree as a predictor for HRCE. MLr cutoff point of 1.59 yield sensitivity of 91.23%, specificity of 44%, positive predictive value of 78.79%, and negative predictive value of 68.75 for HRCE diagnosis among CS. MLr ≥ 1.6 in clot analysis predicted HRCE diagnosis (OR, 6.63, 95% CI 1.85-23.71) in a multivariate model adjusted for age. Clot analysis by FC revealed high levels of monocyte-to-lymphocyte ratio as an independent marker of cardioembolic etiology in cryptogenic strokes.
Identifiants
pubmed: 34586594
doi: 10.1007/s12975-021-00946-w
pii: 10.1007/s12975-021-00946-w
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
949-958Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Norrving B, Barrick J, Davalos A, Dichgans M, Cordonnier C, Guekht A, et al. Action plan for stroke in Europe 2018–2030. Eur Stroke J. 2018;3:309–36.
doi: 10.1177/2396987318808719
pubmed: 31236480
pmcid: 6571507
Yang H, Nassif M, Khairy P, de Groot JR, Roos Y, de Winter RJ, et al. Cardiac diagnostic work-up of ischaemic stroke. Eur Heart J. 2018;39(20):1851–60.
doi: 10.1093/eurheartj/ehy043
pubmed: 29788298
Kernan WN, Ovbiagele B, Black HR, Bravata DM, Chimowitz MI, Ezekowitz MD, et al. Guidelines for the prevention of stroke in patients with stroke and transient ischemic attack: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2014;45(7):2160–236.
doi: 10.1161/STR.0000000000000024
pubmed: 24788967
De Meyer SF, Andersson T, Baxter B, Bendszus M, Brouwer P, Brinjikji W, et al. Analyses of thrombi in acute ischemic stroke: a consensus statement on current knowledge and future directions. Int J Stroke. 2017;12:606–14.
doi: 10.1177/1747493017709671
pubmed: 28534706
Dargazanli C, Rigau V, Eker O, RiquelmeBareiro C, Machi P, Gascou G, et al. High CD3+ cells in intracranial thrombi represent a biomarker of atherothrombotic. PLoS One. 2016;11:e0154945.
doi: 10.1371/journal.pone.0154945
pubmed: 27152622
pmcid: 4859469
McKinnon KM. Flow cytometry: an overview CurrProtoc Immunol. 2018;120:511–5111.
Suzuki A, Fukuzawa K, Yamashita T, Yoshida A, Sasaki N, Emoto T, et al. Circulating intermediate CD1411CD161 monocytes are increased in patients with atrial fibrillation and reflect the functional remodeling of the left atrium. Europace. 2017;19:40–7.
pubmed: 26826137
Gijsberts CM, Ellenbroek G, Ten Berg MJ, Huisman A, van Solinge WW, Lam CS, et al. Effect of monocyte-to-lymphocyte ratio on heart failure characteristics and hospitalizations in a coronary angiography cohort. Am J Cardiol. 2017;120(6):911–6.
doi: 10.1016/j.amjcard.2017.06.020
pubmed: 28779870
Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, Bambakidis NC, Becker K, et al. Stroke. 2019;50:e344–418.
doi: 10.1161/STROKEAHA.118.022606
pubmed: 31662037
Almekhlafi MA, Mishra S, Desai JA, Nambiar V, Volny O, Goel A, et al. Not all “successful” angiographic reperfusion patients are an equal validation of a modified TICI scoring system. Interv Neuroradiol. 2014;20(1):21–7.
doi: 10.15274/INR-2014-10004
pubmed: 24556296
pmcid: 3971136
Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke. 1993;24:35–41.
Ay H, Benner T, Arsava EM, Furie KL, Singhal AB, Jensen MB, et al. A computerized algorithm for etiologic classification of ischemic stroke: the Causative Classification of Stroke System. Stroke. 2007;38(11):2979–84.
doi: 10.1161/STROKEAHA.107.490896
pubmed: 17901381
Pagola J, Juega J, Francisco-Pascual J, Moya A, Sanchis M, Bustamante A, et al. Yield of atrial fibrillation detection with Textile Wearable Holter from the acute phase of stroke: Pilot study of Crypto-AF registry. Int J Cardiol. 2017;251:45–50.
doi: 10.1016/j.ijcard.2017.10.063
pubmed: 29107360
Mir H, Siemieniuk RAC, Ge L, Foroutan F, Fralick M, Syed T, et al. Patent foramen ovale closure, antiplatelet therapy or anticoagulation in patients with patent foramen ovale and cryptogenic stroke: a systematic review and network meta-analysis incorporating complementary external evidence. BMJ Open. 2018;8(7):e023761.
doi: 10.1136/bmjopen-2018-023761
pubmed: 30049703
pmcid: 6067350
Hedley BD, Keeney M. Technical issues: flow cytometry and rare event analysis. Int J Lab Hematol. 2013;35:344–50.
doi: 10.1111/ijlh.12068
pubmed: 23590661
Yaghi S, Elkind MS. Cryptogenic stroke: a diagnostic challenge. Neurol Clin Pract. 2014;4(5):386–93.
doi: 10.1212/CPJ.0000000000000086
pubmed: 25317376
pmcid: 4196459
Boeckh-Behrens T, Kleine JF, Zimmer C, Neff F, Scheipl F, Pelisek J, et al. Thrombus histology suggests cardioembolic cause in cryptogenic stroke. Stroke. 2016;47(7):1864–71.
doi: 10.1161/STROKEAHA.116.013105
pubmed: 27197854
Shahid, F., Lip, G. Y. H. and Shantsila, E. Role of monocytes in heart failure and atrial fibrillation. J Am Heart Assoc. 2018;7(3).
Ketelhuth DF, Hansson GK. Adaptive response of T and B Cells in Atherosclerosis. Circ Res. 2016;118(4):668–78.
doi: 10.1161/CIRCRESAHA.115.306427
pubmed: 26892965
Zhao TX, Mallat Z. Targeting the immune system in atherosclerosis: JACC State-of-the-Art Review. J Am Coll Cardiol. 2019;73:1691–706.
doi: 10.1016/j.jacc.2018.12.083
pubmed: 30947923
Kita T, Yamashita T, Sasaki N, Kasahara K, Sasaki Y, Yodoi K, et al. Regression of atherosclerosis with anti-CD3 antibody via augmenting a regulatory T-cell response in mice. Cardiovasc Res. 2014;1021:07–17.
Douna H, Amersfoort J, Schaftenaar FH, Kröner MJ, Kiss MG, et al. B- and T-lymphocyte attenuator stimulation protects against atherosclerosis by regulating follicular B cells. Cardiovasc Res. 2020;116:295–305.
pubmed: 31150053
Fitzgerald S, Dai D, Wang S, Douglas A, Kadirvel R, Layton KF, et al. Platelet-rich emboli in cerebral large vessel occlusion are associated with a large artery atherosclerosis source. Stroke. 2019;50:1907–10.
doi: 10.1161/STROKEAHA.118.024543
pubmed: 31138084
pmcid: 6910081