Quantitative Optical Coherence Tomography Angiography (OCTA) Parameters in a Black Diabetic Population and Correlations with Systemic Diseases
This is a cross-sectional, prospective study of a population of black diabetic participants without diabetic retinopathy aimed to investigate optical coherence tomography angiography (OCTA) characteristics and correlations with systemic diseases in this population. These parameters could serve as no...
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| Veröffentlicht in: | Cells (Basel, Switzerland) Switzerland), 2021-03, Vol.10 (3), p.551, Article 551 |
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| description | This is a cross-sectional, prospective study of a population of black diabetic participants without diabetic retinopathy aimed to investigate optical coherence tomography angiography (OCTA) characteristics and correlations with systemic diseases in this population. These parameters could serve as novel biomarkers for microvascular complications; especially in black populations which are more vulnerable to diabetic microvascular complications. Linear mixed models were used to obtain OCTA mean values +/- standard deviation and analyze statistical correlations to systemic diseases. Variables showing significance on univariate mixed model analysis were further analyzed with multivariate mixed models. 92 eyes of 52 black adult subjects were included. After multivariate analysis; signal strength intensity (SSI) and heart disease had statistical correlations to superficial capillary plexus vessel density in our population. SSI and smoking status had statistical correlations to deep capillary plexus vessel density in a univariate analysis that persisted in part of the imaging subset in a multivariate analysis. Hyperlipidemia; hypertension; smoking status and pack-years; diabetes duration; creatinine; glomerular filtration rate; total cholesterol; hemoglobin A1C; and albumin-to-creatinine ratio were not significantly associated with any OCTA measurement in multivariate analysis. Our findings suggest that OCTA measures may serve as valuable biomarkers to track systemic vascular functioning in diabetes mellitus in black patients. |
| doi_str_mv | 10.3390/cells10030551 |
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These parameters could serve as novel biomarkers for microvascular complications; especially in black populations which are more vulnerable to diabetic microvascular complications. Linear mixed models were used to obtain OCTA mean values +/- standard deviation and analyze statistical correlations to systemic diseases. Variables showing significance on univariate mixed model analysis were further analyzed with multivariate mixed models. 92 eyes of 52 black adult subjects were included. After multivariate analysis; signal strength intensity (SSI) and heart disease had statistical correlations to superficial capillary plexus vessel density in our population. SSI and smoking status had statistical correlations to deep capillary plexus vessel density in a univariate analysis that persisted in part of the imaging subset in a multivariate analysis. Hyperlipidemia; hypertension; smoking status and pack-years; diabetes duration; creatinine; glomerular filtration rate; total cholesterol; hemoglobin A1C; and albumin-to-creatinine ratio were not significantly associated with any OCTA measurement in multivariate analysis. Our findings suggest that OCTA measures may serve as valuable biomarkers to track systemic vascular functioning in diabetes mellitus in black patients.</description><identifier>ISSN: 2073-4409</identifier><identifier>EISSN: 2073-4409</identifier><identifier>DOI: 10.3390/cells10030551</identifier><identifier>PMID: 33806492</identifier><language>eng</language><publisher>BASEL: Mdpi</publisher><subject>Age ; Angiography ; Biomarkers ; Cardiovascular disease ; Cell Biology ; Cholesterol ; complication ; Coronary artery disease ; Creatinine ; Diabetes ; Diabetes mellitus ; Diabetic retinopathy ; Glomerular filtration rate ; Heart ; Heart diseases ; Hemoglobin ; Hyperlipidemia ; Life Sciences & Biomedicine ; Medical imaging ; microvascular ; Microvasculature ; Multivariate analysis ; optical coherence tomography ; Patients ; Population density ; Population studies ; Retinopathy ; Science & Technology ; Smoking ; Software ; Statistical analysis ; Statistics ; Systemic diseases ; Tomography ; Variables</subject><ispartof>Cells (Basel, Switzerland), 2021-03, Vol.10 (3), p.551, Article 551</ispartof><rights>2021. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>7</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000633450300001</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c481t-ea1baa59027c201a352c5aa23dadb005eada3b2c2c9a429b3f85a8a6d7282a183</citedby><cites>FETCH-LOGICAL-c481t-ea1baa59027c201a352c5aa23dadb005eada3b2c2c9a429b3f85a8a6d7282a183</cites><orcidid>0000-0001-7373-9429</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998203/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998203/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,729,782,786,866,887,2106,2118,27933,27934,39267,53800,53802</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33806492$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Shaw, Lincoln T.</creatorcontrib><creatorcontrib>Khanna, Saira</creatorcontrib><creatorcontrib>Chun, Lindsay Y.</creatorcontrib><creatorcontrib>Dimitroyannis, Rose C.</creatorcontrib><creatorcontrib>Rodriguez, Sarah H.</creatorcontrib><creatorcontrib>Massamba, Nathalie</creatorcontrib><creatorcontrib>Hariprasad, Seenu M.</creatorcontrib><creatorcontrib>Skondra, Dimitra</creatorcontrib><title>Quantitative Optical Coherence Tomography Angiography (OCTA) Parameters in a Black Diabetic Population and Correlations with Systemic Diseases</title><title>Cells (Basel, Switzerland)</title><addtitle>CELLS-BASEL</addtitle><addtitle>Cells</addtitle><description>This is a cross-sectional, prospective study of a population of black diabetic participants without diabetic retinopathy aimed to investigate optical coherence tomography angiography (OCTA) characteristics and correlations with systemic diseases in this population. 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Hyperlipidemia; hypertension; smoking status and pack-years; diabetes duration; creatinine; glomerular filtration rate; total cholesterol; hemoglobin A1C; and albumin-to-creatinine ratio were not significantly associated with any OCTA measurement in multivariate analysis. Our findings suggest that OCTA measures may serve as valuable biomarkers to track systemic vascular functioning in diabetes mellitus in black patients.</description><subject>Age</subject><subject>Angiography</subject><subject>Biomarkers</subject><subject>Cardiovascular disease</subject><subject>Cell Biology</subject><subject>Cholesterol</subject><subject>complication</subject><subject>Coronary artery disease</subject><subject>Creatinine</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetic retinopathy</subject><subject>Glomerular filtration rate</subject><subject>Heart</subject><subject>Heart diseases</subject><subject>Hemoglobin</subject><subject>Hyperlipidemia</subject><subject>Life Sciences & Biomedicine</subject><subject>Medical imaging</subject><subject>microvascular</subject><subject>Microvasculature</subject><subject>Multivariate analysis</subject><subject>optical coherence tomography</subject><subject>Patients</subject><subject>Population density</subject><subject>Population studies</subject><subject>Retinopathy</subject><subject>Science & Technology</subject><subject>Smoking</subject><subject>Software</subject><subject>Statistical analysis</subject><subject>Statistics</subject><subject>Systemic diseases</subject><subject>Tomography</subject><subject>Variables</subject><issn>2073-4409</issn><issn>2073-4409</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>HGBXW</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNkktv1DAURiMEolXpki2yxKYIDfgRJ_EGaUh5VKo0RQxr68a5mfGQxFM7adU_wW_G6bSjDiu88evoXD--JHnN6AchFP1osG0Do1RQKdmz5JjTXMzSlKrnT8ZHyWkIGxpbwTJG5cvkSIiCZqnix8mfHyP0gx1gsDdIFtvBGmhJ6dbosTdIlq5zKw_b9R2Z9yv7OD5blMv5O3IFHjoc0AdiewLkcwvmNzm3UGEUkSu3HdtodnGvr6PVe9zNA7m1w5r8vAsDdpE8twEhYHiVvGigDXj60J8kv75-WZbfZ5eLbxfl_HJm0oINMwRWAUhFeW44ZSAkNxKAixrqilKJUIOouOFGQcpVJZpCQgFZnfOCAyvESXKx89YONnrrbQf-Tjuw-n7B-ZUGH6_Qos5ExpqaYyMrluZVroypY7kqlYrzPJtcn3au7Vh1WBvsBw_tgfRwp7drvXI3Oleq4FREwdmDwLvrEcOgOxumr4Ue3Rg0l7SQmWR8qvX2H3TjRt_Hp9I8VYplXGU8UrMdZbwLwWOzPwyjegqOPghO5N88vcGefoxJBN7vgFusXBOMnbKxx2KyMiFSGW2xTbri_-nyPnuuL93YD-Ivv6jhhg</recordid><startdate>20210304</startdate><enddate>20210304</enddate><creator>Shaw, Lincoln T.</creator><creator>Khanna, Saira</creator><creator>Chun, Lindsay Y.</creator><creator>Dimitroyannis, Rose C.</creator><creator>Rodriguez, Sarah H.</creator><creator>Massamba, Nathalie</creator><creator>Hariprasad, Seenu M.</creator><creator>Skondra, Dimitra</creator><general>Mdpi</general><general>MDPI AG</general><general>MDPI</general><scope>BLEPL</scope><scope>DTL</scope><scope>HGBXW</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7373-9429</orcidid></search><sort><creationdate>20210304</creationdate><title>Quantitative Optical Coherence Tomography Angiography (OCTA) Parameters in a Black Diabetic Population and Correlations with Systemic Diseases</title><author>Shaw, Lincoln T. ; 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These parameters could serve as novel biomarkers for microvascular complications; especially in black populations which are more vulnerable to diabetic microvascular complications. Linear mixed models were used to obtain OCTA mean values +/- standard deviation and analyze statistical correlations to systemic diseases. Variables showing significance on univariate mixed model analysis were further analyzed with multivariate mixed models. 92 eyes of 52 black adult subjects were included. After multivariate analysis; signal strength intensity (SSI) and heart disease had statistical correlations to superficial capillary plexus vessel density in our population. SSI and smoking status had statistical correlations to deep capillary plexus vessel density in a univariate analysis that persisted in part of the imaging subset in a multivariate analysis. Hyperlipidemia; hypertension; smoking status and pack-years; diabetes duration; creatinine; glomerular filtration rate; total cholesterol; hemoglobin A1C; and albumin-to-creatinine ratio were not significantly associated with any OCTA measurement in multivariate analysis. Our findings suggest that OCTA measures may serve as valuable biomarkers to track systemic vascular functioning in diabetes mellitus in black patients.</abstract><cop>BASEL</cop><pub>Mdpi</pub><pmid>33806492</pmid><doi>10.3390/cells10030551</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-7373-9429</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Age Angiography Biomarkers Cardiovascular disease Cell Biology Cholesterol complication Coronary artery disease Creatinine Diabetes Diabetes mellitus Diabetic retinopathy Glomerular filtration rate Heart Heart diseases Hemoglobin Hyperlipidemia Life Sciences & Biomedicine Medical imaging microvascular Microvasculature Multivariate analysis optical coherence tomography Patients Population density Population studies Retinopathy Science & Technology Smoking Software Statistical analysis Statistics Systemic diseases Tomography Variables |
| title | Quantitative Optical Coherence Tomography Angiography (OCTA) Parameters in a Black Diabetic Population and Correlations with Systemic Diseases |
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