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The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy
Clinical and Applied Thrombosis/Hemostasis, Volume: 29, Start page: 107602962211315
Swansea University Authors: Matthew Lawrence , Daniel Obaid , Janet Whitley, Suresh Gopala Pillai , Alexander Chase, Rhodri Williams , Karl Hawkins , Adrian Evans
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DOI (Published version): 10.1177/10760296221131563
Abstract
BackgroundUnfavourable clot microstructure is associated with adverse outcomes in ST elevation myocardial infarction (STEMI). We investigated the effect of comorbidities and anti-platelet treatment on clot microstructure in STEMI patients using fractal dimension (df), a novel biomarker of clot micro...
Published in: | Clinical and Applied Thrombosis/Hemostasis |
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ISSN: | 1076-0296 1938-2723 |
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SAGE Publications
2023
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URI: | https://cronfa.swan.ac.uk/Record/cronfa63236 |
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We investigated the effect of comorbidities and anti-platelet treatment on clot microstructure in STEMI patients using fractal dimension (df), a novel biomarker of clot microstructure derived from the visco-elastic properties of whole blood.MethodsPatients with STEMI (n = 187) were recruited sequentially receiving aspirin with Clopidogrel (n = 157) then Ticagrelor (n = 30). Patient characteristics and blood for rheological analysis obtained. We quantified df using sequential frequency sweep tests to obtain the phase angle of the Gel Point which is synonymous with the clot microstructure.ResultsHigher df was observed in males (1.755 ± 0.068) versus females (1.719 ± 0.061, p = .001), in patients with diabetes (1.786 ± 0.067 vs 1.743 ± 0.046, p < .001), hypertension (1.760 ± 0.065 vs 1.738 ± 0.069, p = .03) and previous MI (1.787 ± 0.073 vs 1.744 ± 0.066, p = .011) compared to without. Patients receiving Ticagrelor had lower df than those receiving Clopidogrel (1.708 ± 0.060 vs 1.755 ± 0.067, p < .001). Significant correlation with df was found with haematocrit (r = 0.331, p < .0001), low-density lipoprotein (LDL) (r = 0.155, p = .046) and fibrinogen (r = 0.182, p = .014). Following multiple regression analysis, diabetes, LDL, fibrinogen and haematocrit remained associated with higher df while treatment with Ticagrelor remained associated with lower df.ConclusionsThe biomarker df uniquely evaluates the effect of interactions between treatment and underlying disease on clot microstructure. STEMI patients with diabetes and elevated LDL had higher df, indicating denser clot. Ticagrelor resulted in a lower df than Clopidogrel signifying a less compact clot.</abstract><type>Journal Article</type><journal>Clinical and Applied Thrombosis/Hemostasis</journal><volume>29</volume><journalNumber/><paginationStart>107602962211315</paginationStart><paginationEnd/><publisher>SAGE Publications</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1076-0296</issnPrint><issnElectronic>1938-2723</issnElectronic><keywords/><publishedDay>1</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-01-01</publishedDate><doi>10.1177/10760296221131563</doi><url>http://dx.doi.org/10.1177/10760296221131563</url><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm>Other</apcterm><funders/><projectreference/><lastEdited>2024-10-29T13:33:41.4397808</lastEdited><Created>2023-04-24T21:15:02.9579538</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Biomedical Science</level></path><authors><author><firstname>Matthew</firstname><surname>Lawrence</surname><orcid>0000-0001-7344-2836</orcid><order>1</order></author><author><firstname>Daniel</firstname><surname>Obaid</surname><orcid>0000-0002-3891-1403</orcid><order>2</order></author><author><firstname>Ahmed</firstname><surname>Sabra</surname><order>3</order></author><author><firstname>Janet</firstname><surname>Whitley</surname><orcid/><order>4</order></author><author><firstname>Janet</firstname><surname>Whitley</surname><order>5</order></author><author><firstname>Rhianwen</firstname><surname>Quarry</surname><order>6</order></author><author><firstname>Suresh</firstname><surname>Gopala Pillai</surname><orcid>0000-0002-9753-6949</orcid><order>7</order></author><author><firstname>Alexander</firstname><surname>Chase</surname><order>8</order></author><author><firstname>David</firstname><surname>Smith</surname><order>9</order></author><author><firstname>Rhodri</firstname><surname>Williams</surname><orcid>0000-0002-6912-5288</orcid><order>10</order></author><author><firstname>Karl</firstname><surname>Hawkins</surname><orcid>0000-0003-0174-4151</orcid><order>11</order></author><author><firstname>Roger H.K.</firstname><surname>Morris</surname><order>12</order></author><author><firstname>Adrian</firstname><surname>Evans</surname><order>13</order></author></authors><documents><document><filename>63236__27595__b4cafe3d11404eec8da9cdd7305401f5.pdf</filename><originalFilename>63236.pdf</originalFilename><uploaded>2023-05-24T13:12:57.7680642</uploaded><type>Output</type><contentLength>961027</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by-nc/4.0/</licence></document></documents><OutputDurs/></rfc1807> |
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2024-10-29T13:33:41.4397808 v2 63236 2023-04-24 The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy 262d0cae7663ded863d6e2de15757f3c 0000-0001-7344-2836 Matthew Lawrence Matthew Lawrence true false 1cb4b49224d4f3f2b546ed0f39e13ea8 0000-0002-3891-1403 Daniel Obaid Daniel Obaid true false bda7069a6ac3481b27c9986c9bc51e49 Janet Whitley Janet Whitley true false f567f8d5db61d62ef08e811676fd8430 0000-0002-9753-6949 Suresh Gopala Pillai Suresh Gopala Pillai true false a3b0da49be6a585449e0a4588880df17 Alexander Chase Alexander Chase true false 642bf793695f412ed932f1ea4d9bc3f1 0000-0002-6912-5288 Rhodri Williams Rhodri Williams true false 77c39404a9a98c6e2283d84815cba053 0000-0003-0174-4151 Karl Hawkins Karl Hawkins true false 21761f6eb805546a561c9f036e85405b Adrian Evans Adrian Evans true false 2023-04-24 MEDS BackgroundUnfavourable clot microstructure is associated with adverse outcomes in ST elevation myocardial infarction (STEMI). We investigated the effect of comorbidities and anti-platelet treatment on clot microstructure in STEMI patients using fractal dimension (df), a novel biomarker of clot microstructure derived from the visco-elastic properties of whole blood.MethodsPatients with STEMI (n = 187) were recruited sequentially receiving aspirin with Clopidogrel (n = 157) then Ticagrelor (n = 30). Patient characteristics and blood for rheological analysis obtained. We quantified df using sequential frequency sweep tests to obtain the phase angle of the Gel Point which is synonymous with the clot microstructure.ResultsHigher df was observed in males (1.755 ± 0.068) versus females (1.719 ± 0.061, p = .001), in patients with diabetes (1.786 ± 0.067 vs 1.743 ± 0.046, p < .001), hypertension (1.760 ± 0.065 vs 1.738 ± 0.069, p = .03) and previous MI (1.787 ± 0.073 vs 1.744 ± 0.066, p = .011) compared to without. Patients receiving Ticagrelor had lower df than those receiving Clopidogrel (1.708 ± 0.060 vs 1.755 ± 0.067, p < .001). Significant correlation with df was found with haematocrit (r = 0.331, p < .0001), low-density lipoprotein (LDL) (r = 0.155, p = .046) and fibrinogen (r = 0.182, p = .014). Following multiple regression analysis, diabetes, LDL, fibrinogen and haematocrit remained associated with higher df while treatment with Ticagrelor remained associated with lower df.ConclusionsThe biomarker df uniquely evaluates the effect of interactions between treatment and underlying disease on clot microstructure. STEMI patients with diabetes and elevated LDL had higher df, indicating denser clot. Ticagrelor resulted in a lower df than Clopidogrel signifying a less compact clot. Journal Article Clinical and Applied Thrombosis/Hemostasis 29 107602962211315 SAGE Publications 1076-0296 1938-2723 1 1 2023 2023-01-01 10.1177/10760296221131563 http://dx.doi.org/10.1177/10760296221131563 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Other 2024-10-29T13:33:41.4397808 2023-04-24T21:15:02.9579538 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Biomedical Science Matthew Lawrence 0000-0001-7344-2836 1 Daniel Obaid 0000-0002-3891-1403 2 Ahmed Sabra 3 Janet Whitley 4 Janet Whitley 5 Rhianwen Quarry 6 Suresh Gopala Pillai 0000-0002-9753-6949 7 Alexander Chase 8 David Smith 9 Rhodri Williams 0000-0002-6912-5288 10 Karl Hawkins 0000-0003-0174-4151 11 Roger H.K. Morris 12 Adrian Evans 13 63236__27595__b4cafe3d11404eec8da9cdd7305401f5.pdf 63236.pdf 2023-05-24T13:12:57.7680642 Output 961027 application/pdf Version of Record true This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). true eng https://creativecommons.org/licenses/by-nc/4.0/ |
title |
The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy |
spellingShingle |
The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy Matthew Lawrence Daniel Obaid Janet Whitley Suresh Gopala Pillai Alexander Chase Rhodri Williams Karl Hawkins Adrian Evans |
title_short |
The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy |
title_full |
The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy |
title_fullStr |
The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy |
title_full_unstemmed |
The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy |
title_sort |
The Impact of Patient Characteristics and Antiplatelet Regimes on Clot Microstructure in Patients Treated for ST Elevation Myocardial Infarction: Clot Microstructure can Evaluate Therapeutic Efficacy |
author_id_str_mv |
262d0cae7663ded863d6e2de15757f3c 1cb4b49224d4f3f2b546ed0f39e13ea8 bda7069a6ac3481b27c9986c9bc51e49 f567f8d5db61d62ef08e811676fd8430 a3b0da49be6a585449e0a4588880df17 642bf793695f412ed932f1ea4d9bc3f1 77c39404a9a98c6e2283d84815cba053 21761f6eb805546a561c9f036e85405b |
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262d0cae7663ded863d6e2de15757f3c_***_Matthew Lawrence 1cb4b49224d4f3f2b546ed0f39e13ea8_***_Daniel Obaid bda7069a6ac3481b27c9986c9bc51e49_***_Janet Whitley f567f8d5db61d62ef08e811676fd8430_***_Suresh Gopala Pillai a3b0da49be6a585449e0a4588880df17_***_Alexander Chase 642bf793695f412ed932f1ea4d9bc3f1_***_Rhodri Williams 77c39404a9a98c6e2283d84815cba053_***_Karl Hawkins 21761f6eb805546a561c9f036e85405b_***_Adrian Evans |
author |
Matthew Lawrence Daniel Obaid Janet Whitley Suresh Gopala Pillai Alexander Chase Rhodri Williams Karl Hawkins Adrian Evans |
author2 |
Matthew Lawrence Daniel Obaid Ahmed Sabra Janet Whitley Janet Whitley Rhianwen Quarry Suresh Gopala Pillai Alexander Chase David Smith Rhodri Williams Karl Hawkins Roger H.K. Morris Adrian Evans |
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Clinical and Applied Thrombosis/Hemostasis |
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29 |
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107602962211315 |
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2023 |
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Swansea University |
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1076-0296 1938-2723 |
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10.1177/10760296221131563 |
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SAGE Publications |
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Faculty of Medicine, Health and Life Sciences |
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facultyofmedicinehealthandlifesciences |
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Faculty of Medicine, Health and Life Sciences |
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Faculty of Medicine, Health and Life Sciences |
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Swansea University Medical School - Biomedical Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Biomedical Science |
url |
http://dx.doi.org/10.1177/10760296221131563 |
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description |
BackgroundUnfavourable clot microstructure is associated with adverse outcomes in ST elevation myocardial infarction (STEMI). We investigated the effect of comorbidities and anti-platelet treatment on clot microstructure in STEMI patients using fractal dimension (df), a novel biomarker of clot microstructure derived from the visco-elastic properties of whole blood.MethodsPatients with STEMI (n = 187) were recruited sequentially receiving aspirin with Clopidogrel (n = 157) then Ticagrelor (n = 30). Patient characteristics and blood for rheological analysis obtained. We quantified df using sequential frequency sweep tests to obtain the phase angle of the Gel Point which is synonymous with the clot microstructure.ResultsHigher df was observed in males (1.755 ± 0.068) versus females (1.719 ± 0.061, p = .001), in patients with diabetes (1.786 ± 0.067 vs 1.743 ± 0.046, p < .001), hypertension (1.760 ± 0.065 vs 1.738 ± 0.069, p = .03) and previous MI (1.787 ± 0.073 vs 1.744 ± 0.066, p = .011) compared to without. Patients receiving Ticagrelor had lower df than those receiving Clopidogrel (1.708 ± 0.060 vs 1.755 ± 0.067, p < .001). Significant correlation with df was found with haematocrit (r = 0.331, p < .0001), low-density lipoprotein (LDL) (r = 0.155, p = .046) and fibrinogen (r = 0.182, p = .014). Following multiple regression analysis, diabetes, LDL, fibrinogen and haematocrit remained associated with higher df while treatment with Ticagrelor remained associated with lower df.ConclusionsThe biomarker df uniquely evaluates the effect of interactions between treatment and underlying disease on clot microstructure. STEMI patients with diabetes and elevated LDL had higher df, indicating denser clot. Ticagrelor resulted in a lower df than Clopidogrel signifying a less compact clot. |
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2023-01-01T02:36:48Z |
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11.048453 |