Agreement between Automated and Manual Quantification of Corneal Nerve Fibre Length: Implications for Diabetic Neuropathy Research
Abstract Aims Quantification of corneal nerve fiber length (CNFL) by in vivo corneal confocal microscopy represents a promising diabetic neuropathy biomarker, but applicability is limited by resource-intensive image analysis. We aimed to evaluate, in cross-sectional analysis of non-diabetic controls...
Gespeichert in:
| Veröffentlicht in: | Journal of diabetes and its complications 2017-06, Vol.31 (6), p.1066-1073 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1073 |
|---|---|
| container_issue | 6 |
| container_start_page | 1066 |
| container_title | Journal of diabetes and its complications |
| container_volume | 31 |
| creator | Scarr, Daniel Lovblom, Leif E Ostrovski, Ilia Kelly, Dylan Wu, Tong Farooqi, Mohammed A Halpern, Elise M Ngo, Mylan Ng, Eduardo Orszag, Andrej Bril, Vera Perkins, Bruce A |
| description | Abstract Aims Quantification of corneal nerve fiber length (CNFL) by in vivo corneal confocal microscopy represents a promising diabetic neuropathy biomarker, but applicability is limited by resource-intensive image analysis. We aimed to evaluate, in cross-sectional analysis of non-diabetic controls and patients with type 1 and type 2 diabetes with and without neuropathy, the agreement between manual and automated analysis protocols. Methods Sixty-eight controls, 139 type 1 diabetes, and 249 type 2 diabetes participants underwent CNFL measurement (N = 456). Neuropathy status was determined by clinical and electrophysiological criteria. CNFL was determined by manual (CNFLManual , reference standard) and automated (CNFLAuto ) protocols, and results were compared for correlation and agreement using Spearman coefficients and the method of Bland and Altman (CNFLManual subtracted from CNFLAuto ). Results Participants demonstrated broad variability in clinical characteristics associated with neuropathy. The mean age, diabetes duration, and HbA1c were 53 ± 18 years, 15.9 ± 12.6 years, and 7.4 ± 1.7%, respectively, and 218(56%) individuals with diabetes had neuropathy. Mean CNFLManual was 15.1 ± 4.9 mm/mm2 , and mean CNFLAuto was 10.5 ± 3.7 mm/mm2 (CNFLAuto underestimation bias, -4.6 ± 2.6 mm/mm2 corresponding to -29 ± 17%). Percent bias was similar across non-diabetic controls (-33 ± 12%), type 1 (-30 ± 20%), and type 2 diabetes (-28 ± 16%) subgroups (ANOVA p = 0.068), and similarly in diabetes participants with and without neuropathy. Levels of CNFLAuto and CNFLManual were both inversely associated with neuropathy status. Conclusions Although CNFLAuto substantially underestimated CNFLManual , its bias was non-differential between diverse patient groups and its relationship with neuropathy status was preserved. Determination of diagnostic thresholds specific to CNFLAuto should be pursued in diagnostic studies of diabetic neuropathy. |
| doi_str_mv | 10.1016/j.jdiacomp.2016.07.024 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1881770209</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1056872716303038</els_id><sourcerecordid>1901365698</sourcerecordid><originalsourceid>FETCH-LOGICAL-c451t-72bc50dd391babf55f1ab745b74eb5993f4a2f66d2f3fc3180e81715562c32de3</originalsourceid><addsrcrecordid>eNqFkk1v1DAQhiMEoqXwFypLXLhk8UfsJBwQq4WWSguIL4mb5TjjrkNiL7bTaq_8crzaLUi9IMuyR37m9djvFMU5wQuCiXg5LIbeKu2n7YLmeIHrBabVg-KUNDUrK4F_PMx7zEXZ1LQ-KZ7EOGCMBefkcXFCG1bVoq1Oi9_L6wAwgUuog3QL4NByTn5SCXqkXI8-KDerEX2elUvWWK2S9Q55g1Y-OMgnHyHcALqwXQC0BnedNq_Q1bQdj2hExgf01qosb3Wm5-C3Km126AtEUEFvnhaPjBojPDuuZ8X3i3ffVu_L9afLq9VyXeqKk1TWtNMc9z1rSac6w7khqqsrnid0vG2ZqRQ1QvTUMKMZaTA0pCacC6oZ7YGdFS8Outvgf80Qk5xs1DCOyoGfoyRN5mtMcZvR5_fQwc_B5eokaTFhgou2yZQ4UDr4GAMYuQ12UmEnCZZ7l-Qg71ySe5ckrmV2KSeeH-XnboL-b9qdLRl4cwAg_8eNhSCjtuA09DaATrL39v93vL4noUfrsinjT9hB_PceGanE8uu-V_atQgTDeTTsD2vovLM</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1901365698</pqid></control><display><type>article</type><title>Agreement between Automated and Manual Quantification of Corneal Nerve Fibre Length: Implications for Diabetic Neuropathy Research</title><source>MEDLINE</source><source>Access via ScienceDirect (Elsevier)</source><source>ProQuest Central UK/Ireland</source><creator>Scarr, Daniel ; Lovblom, Leif E ; Ostrovski, Ilia ; Kelly, Dylan ; Wu, Tong ; Farooqi, Mohammed A ; Halpern, Elise M ; Ngo, Mylan ; Ng, Eduardo ; Orszag, Andrej ; Bril, Vera ; Perkins, Bruce A</creator><creatorcontrib>Scarr, Daniel ; Lovblom, Leif E ; Ostrovski, Ilia ; Kelly, Dylan ; Wu, Tong ; Farooqi, Mohammed A ; Halpern, Elise M ; Ngo, Mylan ; Ng, Eduardo ; Orszag, Andrej ; Bril, Vera ; Perkins, Bruce A</creatorcontrib><description>Abstract Aims Quantification of corneal nerve fiber length (CNFL) by in vivo corneal confocal microscopy represents a promising diabetic neuropathy biomarker, but applicability is limited by resource-intensive image analysis. We aimed to evaluate, in cross-sectional analysis of non-diabetic controls and patients with type 1 and type 2 diabetes with and without neuropathy, the agreement between manual and automated analysis protocols. Methods Sixty-eight controls, 139 type 1 diabetes, and 249 type 2 diabetes participants underwent CNFL measurement (N = 456). Neuropathy status was determined by clinical and electrophysiological criteria. CNFL was determined by manual (CNFLManual , reference standard) and automated (CNFLAuto ) protocols, and results were compared for correlation and agreement using Spearman coefficients and the method of Bland and Altman (CNFLManual subtracted from CNFLAuto ). Results Participants demonstrated broad variability in clinical characteristics associated with neuropathy. The mean age, diabetes duration, and HbA1c were 53 ± 18 years, 15.9 ± 12.6 years, and 7.4 ± 1.7%, respectively, and 218(56%) individuals with diabetes had neuropathy. Mean CNFLManual was 15.1 ± 4.9 mm/mm2 , and mean CNFLAuto was 10.5 ± 3.7 mm/mm2 (CNFLAuto underestimation bias, -4.6 ± 2.6 mm/mm2 corresponding to -29 ± 17%). Percent bias was similar across non-diabetic controls (-33 ± 12%), type 1 (-30 ± 20%), and type 2 diabetes (-28 ± 16%) subgroups (ANOVA p = 0.068), and similarly in diabetes participants with and without neuropathy. Levels of CNFLAuto and CNFLManual were both inversely associated with neuropathy status. Conclusions Although CNFLAuto substantially underestimated CNFLManual , its bias was non-differential between diverse patient groups and its relationship with neuropathy status was preserved. Determination of diagnostic thresholds specific to CNFLAuto should be pursued in diagnostic studies of diabetic neuropathy.</description><identifier>ISSN: 1056-8727</identifier><identifier>EISSN: 1873-460X</identifier><identifier>DOI: 10.1016/j.jdiacomp.2016.07.024</identifier><identifier>PMID: 28347694</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; Aged ; Automation ; Biomarkers ; Biopsy ; Case-Control Studies ; Clinical medicine ; Cornea ; Cornea - innervation ; Cornea - pathology ; Corneal confocal microscopy ; Corneal nerve fiber length ; Cross-Sectional Studies ; Diabetes ; Diabetes Mellitus, Type 1 - complications ; Diabetes Mellitus, Type 1 - diagnosis ; Diabetes Mellitus, Type 1 - pathology ; Diabetes Mellitus, Type 2 - complications ; Diabetes Mellitus, Type 2 - diagnosis ; Diabetes Mellitus, Type 2 - pathology ; Diabetic Neuropathies - diagnosis ; Diabetic Neuropathies - pathology ; Diabetic neuropathy ; Diabetic Retinopathy - diagnosis ; Diabetic Retinopathy - pathology ; Diagnostic Techniques, Ophthalmological ; Endocrinology & Metabolism ; Female ; Humans ; Image Processing, Computer-Assisted - methods ; Male ; Measurement ; Microscopy ; Microscopy, Confocal ; Middle Aged ; Morphology ; Nerve Fibers - pathology ; Neuropathy ; Neurosciences ; Pattern Recognition, Automated - methods ; Peripheral neuropathy ; Physical Examination - methods</subject><ispartof>Journal of diabetes and its complications, 2017-06, Vol.31 (6), p.1066-1073</ispartof><rights>2016 Elsevier Inc.</rights><rights>Copyright © 2016 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited Jun 1, 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c451t-72bc50dd391babf55f1ab745b74eb5993f4a2f66d2f3fc3180e81715562c32de3</citedby><cites>FETCH-LOGICAL-c451t-72bc50dd391babf55f1ab745b74eb5993f4a2f66d2f3fc3180e81715562c32de3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1901365698?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995,64385,64387,64389,72469</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28347694$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Scarr, Daniel</creatorcontrib><creatorcontrib>Lovblom, Leif E</creatorcontrib><creatorcontrib>Ostrovski, Ilia</creatorcontrib><creatorcontrib>Kelly, Dylan</creatorcontrib><creatorcontrib>Wu, Tong</creatorcontrib><creatorcontrib>Farooqi, Mohammed A</creatorcontrib><creatorcontrib>Halpern, Elise M</creatorcontrib><creatorcontrib>Ngo, Mylan</creatorcontrib><creatorcontrib>Ng, Eduardo</creatorcontrib><creatorcontrib>Orszag, Andrej</creatorcontrib><creatorcontrib>Bril, Vera</creatorcontrib><creatorcontrib>Perkins, Bruce A</creatorcontrib><title>Agreement between Automated and Manual Quantification of Corneal Nerve Fibre Length: Implications for Diabetic Neuropathy Research</title><title>Journal of diabetes and its complications</title><addtitle>J Diabetes Complications</addtitle><description>Abstract Aims Quantification of corneal nerve fiber length (CNFL) by in vivo corneal confocal microscopy represents a promising diabetic neuropathy biomarker, but applicability is limited by resource-intensive image analysis. We aimed to evaluate, in cross-sectional analysis of non-diabetic controls and patients with type 1 and type 2 diabetes with and without neuropathy, the agreement between manual and automated analysis protocols. Methods Sixty-eight controls, 139 type 1 diabetes, and 249 type 2 diabetes participants underwent CNFL measurement (N = 456). Neuropathy status was determined by clinical and electrophysiological criteria. CNFL was determined by manual (CNFLManual , reference standard) and automated (CNFLAuto ) protocols, and results were compared for correlation and agreement using Spearman coefficients and the method of Bland and Altman (CNFLManual subtracted from CNFLAuto ). Results Participants demonstrated broad variability in clinical characteristics associated with neuropathy. The mean age, diabetes duration, and HbA1c were 53 ± 18 years, 15.9 ± 12.6 years, and 7.4 ± 1.7%, respectively, and 218(56%) individuals with diabetes had neuropathy. Mean CNFLManual was 15.1 ± 4.9 mm/mm2 , and mean CNFLAuto was 10.5 ± 3.7 mm/mm2 (CNFLAuto underestimation bias, -4.6 ± 2.6 mm/mm2 corresponding to -29 ± 17%). Percent bias was similar across non-diabetic controls (-33 ± 12%), type 1 (-30 ± 20%), and type 2 diabetes (-28 ± 16%) subgroups (ANOVA p = 0.068), and similarly in diabetes participants with and without neuropathy. Levels of CNFLAuto and CNFLManual were both inversely associated with neuropathy status. Conclusions Although CNFLAuto substantially underestimated CNFLManual , its bias was non-differential between diverse patient groups and its relationship with neuropathy status was preserved. Determination of diagnostic thresholds specific to CNFLAuto should be pursued in diagnostic studies of diabetic neuropathy.</description><subject>Adult</subject><subject>Aged</subject><subject>Automation</subject><subject>Biomarkers</subject><subject>Biopsy</subject><subject>Case-Control Studies</subject><subject>Clinical medicine</subject><subject>Cornea</subject><subject>Cornea - innervation</subject><subject>Cornea - pathology</subject><subject>Corneal confocal microscopy</subject><subject>Corneal nerve fiber length</subject><subject>Cross-Sectional Studies</subject><subject>Diabetes</subject><subject>Diabetes Mellitus, Type 1 - complications</subject><subject>Diabetes Mellitus, Type 1 - diagnosis</subject><subject>Diabetes Mellitus, Type 1 - pathology</subject><subject>Diabetes Mellitus, Type 2 - complications</subject><subject>Diabetes Mellitus, Type 2 - diagnosis</subject><subject>Diabetes Mellitus, Type 2 - pathology</subject><subject>Diabetic Neuropathies - diagnosis</subject><subject>Diabetic Neuropathies - pathology</subject><subject>Diabetic neuropathy</subject><subject>Diabetic Retinopathy - diagnosis</subject><subject>Diabetic Retinopathy - pathology</subject><subject>Diagnostic Techniques, Ophthalmological</subject><subject>Endocrinology & Metabolism</subject><subject>Female</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Male</subject><subject>Measurement</subject><subject>Microscopy</subject><subject>Microscopy, Confocal</subject><subject>Middle Aged</subject><subject>Morphology</subject><subject>Nerve Fibers - pathology</subject><subject>Neuropathy</subject><subject>Neurosciences</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Peripheral neuropathy</subject><subject>Physical Examination - methods</subject><issn>1056-8727</issn><issn>1873-460X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkk1v1DAQhiMEoqXwFypLXLhk8UfsJBwQq4WWSguIL4mb5TjjrkNiL7bTaq_8crzaLUi9IMuyR37m9djvFMU5wQuCiXg5LIbeKu2n7YLmeIHrBabVg-KUNDUrK4F_PMx7zEXZ1LQ-KZ7EOGCMBefkcXFCG1bVoq1Oi9_L6wAwgUuog3QL4NByTn5SCXqkXI8-KDerEX2elUvWWK2S9Q55g1Y-OMgnHyHcALqwXQC0BnedNq_Q1bQdj2hExgf01qosb3Wm5-C3Km126AtEUEFvnhaPjBojPDuuZ8X3i3ffVu_L9afLq9VyXeqKk1TWtNMc9z1rSac6w7khqqsrnid0vG2ZqRQ1QvTUMKMZaTA0pCacC6oZ7YGdFS8Outvgf80Qk5xs1DCOyoGfoyRN5mtMcZvR5_fQwc_B5eokaTFhgou2yZQ4UDr4GAMYuQ12UmEnCZZ7l-Qg71ySe5ckrmV2KSeeH-XnboL-b9qdLRl4cwAg_8eNhSCjtuA09DaATrL39v93vL4noUfrsinjT9hB_PceGanE8uu-V_atQgTDeTTsD2vovLM</recordid><startdate>20170601</startdate><enddate>20170601</enddate><creator>Scarr, Daniel</creator><creator>Lovblom, Leif E</creator><creator>Ostrovski, Ilia</creator><creator>Kelly, Dylan</creator><creator>Wu, Tong</creator><creator>Farooqi, Mohammed A</creator><creator>Halpern, Elise M</creator><creator>Ngo, Mylan</creator><creator>Ng, Eduardo</creator><creator>Orszag, Andrej</creator><creator>Bril, Vera</creator><creator>Perkins, Bruce A</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>ASE</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FPQ</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K6X</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20170601</creationdate><title>Agreement between Automated and Manual Quantification of Corneal Nerve Fibre Length: Implications for Diabetic Neuropathy Research</title><author>Scarr, Daniel ; Lovblom, Leif E ; Ostrovski, Ilia ; Kelly, Dylan ; Wu, Tong ; Farooqi, Mohammed A ; Halpern, Elise M ; Ngo, Mylan ; Ng, Eduardo ; Orszag, Andrej ; Bril, Vera ; Perkins, Bruce A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c451t-72bc50dd391babf55f1ab745b74eb5993f4a2f66d2f3fc3180e81715562c32de3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Automation</topic><topic>Biomarkers</topic><topic>Biopsy</topic><topic>Case-Control Studies</topic><topic>Clinical medicine</topic><topic>Cornea</topic><topic>Cornea - innervation</topic><topic>Cornea - pathology</topic><topic>Corneal confocal microscopy</topic><topic>Corneal nerve fiber length</topic><topic>Cross-Sectional Studies</topic><topic>Diabetes</topic><topic>Diabetes Mellitus, Type 1 - complications</topic><topic>Diabetes Mellitus, Type 1 - diagnosis</topic><topic>Diabetes Mellitus, Type 1 - pathology</topic><topic>Diabetes Mellitus, Type 2 - complications</topic><topic>Diabetes Mellitus, Type 2 - diagnosis</topic><topic>Diabetes Mellitus, Type 2 - pathology</topic><topic>Diabetic Neuropathies - diagnosis</topic><topic>Diabetic Neuropathies - pathology</topic><topic>Diabetic neuropathy</topic><topic>Diabetic Retinopathy - diagnosis</topic><topic>Diabetic Retinopathy - pathology</topic><topic>Diagnostic Techniques, Ophthalmological</topic><topic>Endocrinology & Metabolism</topic><topic>Female</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Male</topic><topic>Measurement</topic><topic>Microscopy</topic><topic>Microscopy, Confocal</topic><topic>Middle Aged</topic><topic>Morphology</topic><topic>Nerve Fibers - pathology</topic><topic>Neuropathy</topic><topic>Neurosciences</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Peripheral neuropathy</topic><topic>Physical Examination - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Scarr, Daniel</creatorcontrib><creatorcontrib>Lovblom, Leif E</creatorcontrib><creatorcontrib>Ostrovski, Ilia</creatorcontrib><creatorcontrib>Kelly, Dylan</creatorcontrib><creatorcontrib>Wu, Tong</creatorcontrib><creatorcontrib>Farooqi, Mohammed A</creatorcontrib><creatorcontrib>Halpern, Elise M</creatorcontrib><creatorcontrib>Ngo, Mylan</creatorcontrib><creatorcontrib>Ng, Eduardo</creatorcontrib><creatorcontrib>Orszag, Andrej</creatorcontrib><creatorcontrib>Bril, Vera</creatorcontrib><creatorcontrib>Perkins, Bruce A</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>British Nursing Index</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>British Nursing Index (BNI) (1985 to Present)</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>British Nursing Index</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of diabetes and its complications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Scarr, Daniel</au><au>Lovblom, Leif E</au><au>Ostrovski, Ilia</au><au>Kelly, Dylan</au><au>Wu, Tong</au><au>Farooqi, Mohammed A</au><au>Halpern, Elise M</au><au>Ngo, Mylan</au><au>Ng, Eduardo</au><au>Orszag, Andrej</au><au>Bril, Vera</au><au>Perkins, Bruce A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Agreement between Automated and Manual Quantification of Corneal Nerve Fibre Length: Implications for Diabetic Neuropathy Research</atitle><jtitle>Journal of diabetes and its complications</jtitle><addtitle>J Diabetes Complications</addtitle><date>2017-06-01</date><risdate>2017</risdate><volume>31</volume><issue>6</issue><spage>1066</spage><epage>1073</epage><pages>1066-1073</pages><issn>1056-8727</issn><eissn>1873-460X</eissn><abstract>Abstract Aims Quantification of corneal nerve fiber length (CNFL) by in vivo corneal confocal microscopy represents a promising diabetic neuropathy biomarker, but applicability is limited by resource-intensive image analysis. We aimed to evaluate, in cross-sectional analysis of non-diabetic controls and patients with type 1 and type 2 diabetes with and without neuropathy, the agreement between manual and automated analysis protocols. Methods Sixty-eight controls, 139 type 1 diabetes, and 249 type 2 diabetes participants underwent CNFL measurement (N = 456). Neuropathy status was determined by clinical and electrophysiological criteria. CNFL was determined by manual (CNFLManual , reference standard) and automated (CNFLAuto ) protocols, and results were compared for correlation and agreement using Spearman coefficients and the method of Bland and Altman (CNFLManual subtracted from CNFLAuto ). Results Participants demonstrated broad variability in clinical characteristics associated with neuropathy. The mean age, diabetes duration, and HbA1c were 53 ± 18 years, 15.9 ± 12.6 years, and 7.4 ± 1.7%, respectively, and 218(56%) individuals with diabetes had neuropathy. Mean CNFLManual was 15.1 ± 4.9 mm/mm2 , and mean CNFLAuto was 10.5 ± 3.7 mm/mm2 (CNFLAuto underestimation bias, -4.6 ± 2.6 mm/mm2 corresponding to -29 ± 17%). Percent bias was similar across non-diabetic controls (-33 ± 12%), type 1 (-30 ± 20%), and type 2 diabetes (-28 ± 16%) subgroups (ANOVA p = 0.068), and similarly in diabetes participants with and without neuropathy. Levels of CNFLAuto and CNFLManual were both inversely associated with neuropathy status. Conclusions Although CNFLAuto substantially underestimated CNFLManual , its bias was non-differential between diverse patient groups and its relationship with neuropathy status was preserved. Determination of diagnostic thresholds specific to CNFLAuto should be pursued in diagnostic studies of diabetic neuropathy.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>28347694</pmid><doi>10.1016/j.jdiacomp.2016.07.024</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1056-8727 |
| ispartof | Journal of diabetes and its complications, 2017-06, Vol.31 (6), p.1066-1073 |
| issn | 1056-8727 1873-460X |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1881770209 |
| source | MEDLINE; Access via ScienceDirect (Elsevier); ProQuest Central UK/Ireland |
| subjects | Adult Aged Automation Biomarkers Biopsy Case-Control Studies Clinical medicine Cornea Cornea - innervation Cornea - pathology Corneal confocal microscopy Corneal nerve fiber length Cross-Sectional Studies Diabetes Diabetes Mellitus, Type 1 - complications Diabetes Mellitus, Type 1 - diagnosis Diabetes Mellitus, Type 1 - pathology Diabetes Mellitus, Type 2 - complications Diabetes Mellitus, Type 2 - diagnosis Diabetes Mellitus, Type 2 - pathology Diabetic Neuropathies - diagnosis Diabetic Neuropathies - pathology Diabetic neuropathy Diabetic Retinopathy - diagnosis Diabetic Retinopathy - pathology Diagnostic Techniques, Ophthalmological Endocrinology & Metabolism Female Humans Image Processing, Computer-Assisted - methods Male Measurement Microscopy Microscopy, Confocal Middle Aged Morphology Nerve Fibers - pathology Neuropathy Neurosciences Pattern Recognition, Automated - methods Peripheral neuropathy Physical Examination - methods |
| title | Agreement between Automated and Manual Quantification of Corneal Nerve Fibre Length: Implications for Diabetic Neuropathy Research |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-20T10%3A37%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Agreement%20between%20Automated%20and%20Manual%20Quantification%20of%20Corneal%20Nerve%20Fibre%20Length:%20Implications%20for%20Diabetic%20Neuropathy%20Research&rft.jtitle=Journal%20of%20diabetes%20and%20its%20complications&rft.au=Scarr,%20Daniel&rft.date=2017-06-01&rft.volume=31&rft.issue=6&rft.spage=1066&rft.epage=1073&rft.pages=1066-1073&rft.issn=1056-8727&rft.eissn=1873-460X&rft_id=info:doi/10.1016/j.jdiacomp.2016.07.024&rft_dat=%3Cproquest_cross%3E1901365698%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1901365698&rft_id=info:pmid/28347694&rft_els_id=S1056872716303038&rfr_iscdi=true |