Functional slit lamp biomicroscopy metrics correlate with cardiovascular risk. 2019

Veena C Karanam, and Leonardo Tamariz, and Hatim Batawi, and Jianhua Wang, and Anat Galor
Miami VA, Veterans Affairs Medical Center, Miami, FL, USA.

Our aim was to correlate cardiovascular risk factor estimation with bulbar conjunctival blood flow metrics as measured through Functional Slit Lamp Biomicroscopy (FSLB). Cross-sectional study of individuals with otherwise healthy eyelid and corneal anatomy recruited from the Miami Veterans Affairs (VA) Healthcare System eye clinic. We measured conjunctival microvascular hemodynamics by mounting a camera on a slit lamp and cardiovascular risk using the Framingham risk score. Our main outcome measures were correlations between conjunctival vessel parameters (axial and cross-sectional blood flow velocity, blood flow rate) and Framingham score. We included 84 patients who underwent FSLB. The mean age was 60 years, the majority were male (88%) and approximately half the patients were black (54%). Mean vessel diameter was similar between all Framingham score categories. Axial and cross-sectional blood flow velocities and blood flow rate were lower in individuals with higher Framingham risk score. Specifically, mean cross-sectional blood flow velocity in individuals with a low Framingham risk score was 0.37 ± 0.0.9 mm/s, with an intermediate score was 0.30 ± 0.09 mm/s, and with a high score was 0.29 ± 0.10 mm/s, p = 0.04. Mean blood flow rate in individuals with a low Framingham risk score was 133.4 ± 59.6 pl/s, with an intermediate score was 123.6 ± 39.3 pl/s, and with a high score was 121.9 ± 52.6 pl/s, p = 0.04. The beta coefficient of the blood flow rate for change in Framingham score was -0.73; 95% CI-1.34-0.13, p = 0.02, adjusted for race. FSLB correlates with cardiovascular risk estimation. Future studies should evaluate if FSLB can predict cardiovascular outcomes.

UI MeSH Term Description Entries
D007091 Image Processing, Computer-Assisted A technique of inputting two-dimensional or three-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer. Biomedical Image Processing,Computer-Assisted Image Processing,Digital Image Processing,Image Analysis, Computer-Assisted,Image Reconstruction,Medical Image Processing,Analysis, Computer-Assisted Image,Computer-Assisted Image Analysis,Computer Assisted Image Analysis,Computer Assisted Image Processing,Computer-Assisted Image Analyses,Image Analyses, Computer-Assisted,Image Analysis, Computer Assisted,Image Processing, Biomedical,Image Processing, Computer Assisted,Image Processing, Digital,Image Processing, Medical,Image Processings, Medical,Image Reconstructions,Medical Image Processings,Processing, Biomedical Image,Processing, Digital Image,Processing, Medical Image,Processings, Digital Image,Processings, Medical Image,Reconstruction, Image,Reconstructions, Image
D008297 Male Males
D008833 Microcirculation The circulation of the BLOOD through the MICROVASCULAR NETWORK. Microvascular Blood Flow,Microvascular Circulation,Blood Flow, Microvascular,Circulation, Microvascular,Flow, Microvascular Blood,Microvascular Blood Flows,Microvascular Circulations
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D011237 Predictive Value of Tests In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test. Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D011446 Prospective Studies Observation of a population for a sufficient number of persons over a sufficient number of years to generate incidence or mortality rates subsequent to the selection of the study group. Prospective Study,Studies, Prospective,Study, Prospective
D001783 Blood Flow Velocity A value equal to the total volume flow divided by the cross-sectional area of the vascular bed. Blood Flow Velocities,Flow Velocities, Blood,Flow Velocity, Blood,Velocities, Blood Flow,Velocity, Blood Flow
D002318 Cardiovascular Diseases Pathological conditions involving the CARDIOVASCULAR SYSTEM including the HEART; the BLOOD VESSELS; or the PERICARDIUM. Adverse Cardiac Event,Cardiac Events,Major Adverse Cardiac Events,Adverse Cardiac Events,Cardiac Event,Cardiac Event, Adverse,Cardiac Events, Adverse,Cardiovascular Disease,Disease, Cardiovascular,Event, Cardiac
D003228 Conjunctiva The mucous membrane that covers the posterior surface of the eyelids and the anterior pericorneal surface of the eyeball. Bulbar Conjunctiva,Palpebral Conjunctiva,Plica Semilunaris of Conjunctiva,Plicae Semilunares of Conjunctiva,Tunica Conjunctiva,Conjunctiva, Bulbar,Conjunctiva, Palpebral,Conjunctivas
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional

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