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Poh SSJ, Teo KYC, Goh RA, Lee QX, Hamzah H, Sim SSC, Tan CS, Tan NC, Wong TY, Tan GSW. Predicting the need for diabetic macular oedema treatment from photographic screening in the Singapore Integrated Diabetic Retinopathy Programme (SiDRP). Eye (Lond) 2025:10.1038/s41433-025-03725-1. [PMID: 40021782 DOI: 10.1038/s41433-025-03725-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2024] [Revised: 02/07/2025] [Accepted: 02/12/2025] [Indexed: 03/03/2025] Open
Abstract
OBJECTIVE To identify diabetic maculopathy features from photographic screening that are predictive of treatment on referral to a tertiary care centre. METHODS Retrospective review of participants who underwent screening by Singapore Integrated Diabetic Retinopathy Programme from 2015 to 2019. Participants underwent visual acuity (VA) test and non-stereoscopic retinal photographs. Maculopathy features include haemorrhages, microaneurysm and hard exudates (HE), stratified by inner and outer zone (1 and 1-2 disc diameter from fovea respectively) and VA of 6/12. Diabetic macular oedema (DMO) treatment was defined as intravitreal injection or macular photocoagulation up to 540 days from point of referral. RESULTS 16,712 patients screened had referable eye disease. Out of 3518 maculopathy suspects, 281 (8.0%) received DMO treatment within 540 days. Those treated for DMO had shorter duration of diabetes (6.90 vs. 9.13 years, p < 0.001), higher total cholesterol (4.65 ± 1.20 vs. 4.36 ± 1.13 mmol/L, p = 0.001) and LDL cholesterol (2.59 ± 1.05 vs. 2.37 ± 0.93 mmol/L, p < 0.05) than those without treatment. High-risk features, including inner zone haemorrhages with VA ≤ 6/12 (HR 12.0, 95% CI: 5.5-25.9) and inner zone hard exudates (HR 7.4, 95% CI: 3.4-15.8), significantly increased the likelihood of requiring DMO treatment compared to low-risk features. Higher body mass index is protective of DMO treatment in mild non-proliferative diabetic retinopathy (HR 0.84, 95% CI: 0.73-0.97). CONCLUSION Haemorrhages, microaneurysms and HE within inner zone are important photographic features predictive of DMO treatment. VA is an important stratification for screening especially in patients with only visible haemorrhages.
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Affiliation(s)
| | | | - Rose Ann Goh
- SNEC Ocular Reading Centre, Singapore National Eye Centre, Singapore, Singapore
| | - Qian Xin Lee
- SNEC Ocular Reading Centre, Singapore National Eye Centre, Singapore, Singapore
| | - Haslina Hamzah
- SNEC Ocular Reading Centre, Singapore National Eye Centre, Singapore, Singapore
| | - Serene S C Sim
- SNEC Ocular Reading Centre, Singapore National Eye Centre, Singapore, Singapore
| | - Colin S Tan
- Duke-NUS Medical School, National University of Singapore, Ophthalmology and Visual Sciences Academic Clinical Programme, Singapore, Singapore
- Ophthalmology, Tan Tock Seng Hospital, National Healthcare Group Eye Institute, Singapore, Singapore
| | - Ngiap Chuan Tan
- Outram Polyclinic, SingHealth Polyclinics, Singapore, Singapore
| | - Tien Yin Wong
- Singapore National Eye Centre, Singapore, Singapore
- Singapore Eye Research Institute, Singapore, Singapore
- Duke-NUS Medical School, National University of Singapore, Ophthalmology and Visual Sciences Academic Clinical Programme, Singapore, Singapore
- Tsinghua Medicine, Tsinghua University, Beijing, People's Republic of China
- School of Clinical Medicine, Beijing Tsinghua Changgung Hospital, Beijing, People's Republic of China
| | - Gavin S W Tan
- Singapore National Eye Centre, Singapore, Singapore.
- Singapore Eye Research Institute, Singapore, Singapore.
- SNEC Ocular Reading Centre, Singapore National Eye Centre, Singapore, Singapore.
- Duke-NUS Medical School, National University of Singapore, Ophthalmology and Visual Sciences Academic Clinical Programme, Singapore, Singapore.
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Sikka R, Raina P, Soni R, Gupta H, Bhanwer AJS. Genomic profile of diabetic retinopathy in a north indian cohort. Mol Biol Rep 2023; 50:9769-9778. [PMID: 37700140 DOI: 10.1007/s11033-023-08772-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 08/18/2023] [Indexed: 09/14/2023]
Abstract
BACKGROUND Diabetic Retinopathy (DR) is one of the major microvascular complications of diabetes. Being a complex disease, it is important to delineate the genetic and environmental factors that influence the susceptibility to DR in a population. Therefore, the present study was designed to investigate the role of genetic and lifestyle risk factors associated with DR susceptibility in a North-Indian population. METHODS A total of 848 subjects were enrolled, comprising of DR cases (n = 414) and healthy controls (n = 434). The Sequenom MassARRAY technology was used to perform target genome analysis of 111 SNPs across 57 candidate genes and 14 intergenic region SNPs that are involved in the metabolic pathways associated with type 2 diabetes (T2D) and DR. Allele, genotype and haplotype frequencies were determined and compared among cases and controls. Logistic regression models were used to determine genotype-phenotype and phenotype-phenotype correlations. RESULTS The strongest association was observed with TCF7L2 rs12255372 T allele [p < 0.0001; odds ratio (OR) = 1.81 (1.44-2.27)] and rs11196205 C allele [p < 0.0008; OR = 1.62 (1.32-1.99)]. Genotype-phenotype and phenotype-phenotype correlations were found in the present study. CONCLUSION Our study provides strong evidence of association between the TCF7L2 variants and DR susceptibility.
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Affiliation(s)
- Ruhi Sikka
- Department of Human Genetics, Guru Nanak Dev University, Amritsar, Punjab, India.
- Department of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, UP, India.
| | - Priyanka Raina
- Department of Human Genetics, Guru Nanak Dev University, Amritsar, Punjab, India
- Mosaic Therapeutics, Wellcome Genome Campus, Cambridge, UK
| | | | - Himanshu Gupta
- Department of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, UP, India
| | - A J S Bhanwer
- Department of Human Genetics, Guru Nanak Dev University, Amritsar, Punjab, India
- Department of Genetics, Guru Ram Das University of Health Sciences, Amritsar, Punjab, India
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Wiebe N, Lloyd A, Crumley ET, Tonelli M. Associations between body mass index and all-cause mortality: A systematic review and meta-analysis. Obes Rev 2023; 24:e13588. [PMID: 37309266 DOI: 10.1111/obr.13588] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 04/12/2023] [Accepted: 05/22/2023] [Indexed: 06/14/2023]
Abstract
Fasting insulin and c-reactive protein confound the association between mortality and body mass index. An increase in fat mass may mediate the associations between hyperinsulinemia, hyperinflammation, and mortality. The objective of this study was to describe the "average" associations between body mass index and the risk of mortality and to explore how adjusting for fasting insulin and markers of inflammation might modify the association of BMI with mortality. MEDLINE and EMBASE were searched for studies published in 2020. Studies with adult participants where BMI and vital status was assessed were included. BMI was required to be categorized into groups or parametrized as non-first order polynomials or splines. All-cause mortality was regressed against mean BMI squared within seven broad clinical populations. Study was modeled as a random intercept. β coefficients and 95% confidence intervals are reported along with estimates of mortality risk by BMIs of 20, 30, and 40 kg/m2 . Bubble plots with regression lines are drawn, showing the associations between mortality and BMI. Splines results were summarized. There were 154 included studies with 6,685,979 participants. Only five (3.2%) studies adjusted for a marker of inflammation, and no studies adjusted for fasting insulin. There were significant associations between higher BMIs and lower mortality risk in cardiovascular (unadjusted β -0.829 [95% CI -1.313, -0.345] and adjusted β -0.746 [95% CI -1.471, -0.021]), Covid-19 (unadjusted β -0.333 [95% CI -0.650, -0.015]), critically ill (adjusted β -0.550 [95% CI -1.091, -0.010]), and surgical (unadjusted β -0.415 [95% CI -0.824, -0.006]) populations. The associations for general, cancer, and non-communicable disease populations were not significant. Heterogeneity was very large (I2 ≥ 97%). The role of obesity as a driver of excess mortality should be critically re-examined, in parallel with increased efforts to determine the harms of hyperinsulinemia and chronic inflammation.
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Affiliation(s)
- Natasha Wiebe
- Department of Medicine, University of Alberta, Edmonton, Canada
| | - Anita Lloyd
- Department of Medicine, University of Alberta, Edmonton, Canada
| | - Ellen T Crumley
- Rowe School of Business, Dalhousie University, Halifax, Nova Scotia, Canada
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4
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Levitsky LL, Drews KL, Haymond M, Glubitosi-Klug RA, Levitt Katz LE, Mititelu M, Tamborlane W, Tryggestad JB, Weinstock RS. The obesity paradox: Retinopathy, obesity, and circulating risk markers in youth with type 2 diabetes in the TODAY Study. J Diabetes Complications 2022; 36:108259. [PMID: 36150365 DOI: 10.1016/j.jdiacomp.2022.108259] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 06/24/2022] [Accepted: 07/04/2022] [Indexed: 10/31/2022]
Abstract
AIM To understand the relationship of obesity and 27 circulating inflammatory biomarkers to the prevalence of non-proliferative diabetic retinopathy (NPDR) in youth with type 2 diabetes. METHODS Youth with type 2 diabetes who participated in the TODAY (Treatment Options for Type 2 Diabetes in Adolescents and Youth) study were followed for 2-6.5 years. Digital fundus photographs were obtained in the last year of the study. Blood samples during the study were processed for inflammatory biomarkers, and these were correlated with obesity tertiles and presence of retinopathy. RESULTS Higher BMI was associated with an increase in circulating levels of metabolic biomarkers including high sensitivity C-reactive protein (hsCRP), plasminogen activator inhibitor 1 (PAI-1), fibrinogen, LDL-cholesterol (LDL-C) and Apolipoprotein B (ApoB), tumor necrosis factor receptors 1 and 2 (TNFR-1 and -2), interleukin 6 (IL-6), E-selectin, and homocysteine, as well as a decrease in the metabolic risk markers HDL-cholesterol (HDLC), and insulin-like growth factor binding protein 1 (IGFBP-1). Although NPDR risk decreased with increasing obesity, it was not associated with any of the measured biomarkers. CONCLUSIONS Circulating levels of measured biomarkers did not elucidate the "obesity paradox" of decreased NPDR in the most obese participants in the TODAY study. TRIAL REGISTRATION clinicaltrials.govNCT00081328.
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Affiliation(s)
- Lynne L Levitsky
- Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, United States of America
| | - Kimberly L Drews
- George Washington University Biostatistics Center, 6110 Executive Blvd., Rockville, MD 20852, United States of America.
| | - Morey Haymond
- Baylor College of Medicine, 6701 Fannin St, Houston, TX 77030, United States of America
| | - Rose A Glubitosi-Klug
- Rainbow Babies and Children's Hospital and Case Western Reserve University School of Medicine, 1100 Euclid Ave, Cleveland, OH 44106, United States of America
| | - Lorraine E Levitt Katz
- Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19107, United States of America
| | - Mihai Mititelu
- University of Wisconsin, Department of Ophthalmology and Visual Sciences, 2870 University Avenue, Suite 206, Madison, WI 53705, United States of America
| | - William Tamborlane
- Yale University, 1 Long Wharf Drive, New Haven, CT 06511, United States of America
| | - Jeanie B Tryggestad
- Univeristy of Oklahoma Health Sciences Center, 1200 Children's Ave, Oklahoma, OK 73104, United States of America
| | - Ruth S Weinstock
- SUNY Upstate Medical University, 3229 E Genesee St, Syracuse, NY 13214, United States of America
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Li W, Gong X, Wang W, Xiong K, Meng J, Li Y, Wang L, Liang X, Jin L, Huang W. Association of different kinds of obesity with diabetic retinopathy in patients with type 2 diabetes. BMJ Open 2022; 12:e056332. [PMID: 35589355 PMCID: PMC9121435 DOI: 10.1136/bmjopen-2021-056332] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
INTRODUCTION Although obesity is one of the established risk factors of diabetes mellitus, the relationship between obesity and diabetic retinopathy (DR) remains unclear in different studies. This study aimed to investigate the association of DR with four obesity-related indexes, including body mass index (BMI), waist to hip ratio (WHR), waist to height ratio (WHtR) and body adiposity index (BAI) in patients with diabetes. RESEARCH DESIGN AND METHODS We prospectively enrolled 2305 patients with diabetes (2305 eyes) in the Guangzhou Diabetic Eye Study between November 2017 and December 2019 to investigate the prevalence and the association of different types of obesity with DR using BMI, WHR, WHtR and BAI. DR, diabetic macular oedema (DME) and vision-threatening DR (VTDR) were selected as primary outcomes. BMI was categorised as normal (18.5-22.9 kg/m2), overweight (23.0-25.0 kg/m2) and obese (>25.0 kg/m2); WHR, WHtR and BAI were categorised into quarters. RESULTS A total of 336 (14.58%), 93 (4.03%) and 98 (4.25%) developed DR, DME and VTDR, respectively. The prevalence of DR, DME and VTDR was higher in patients with higher BMI/WHR or lower WHtR/BAI. In the univariate regression model, WHR correlated positively with DR, while WHtR and BAI correlated negatively with DR, DME and VTDR. The association remained independent of age, sex and lipid metabolism parameters. In the multivariate model, obese presented as a protective factor for DME and VTDR, while the second quarter of WHtR(Q2-WHtR) presented as a risk factor. CONCLUSIONS As high as 67.8% of patients with diabetes were overweight or obese. Obese presented as a significant protective factor of VTDR, while Q2-WHtR presented as a significant risk factor. Therefore, more attention should be paid to centripetal obesity as well as general obesity. Further research is also needed to focus on the improvement of sex-specific weight management in patients with diabetes.
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Affiliation(s)
- Wangting Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Xia Gong
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Wei Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Kun Xiong
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Jie Meng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Yuting Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Lanhua Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Xiaoling Liang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Ling Jin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Wenyong Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
- Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, People's Republic of China
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Shang X, Zhu Z, Zhang X, Huang Y, Tan Z, Wang W, Tang S, Ge Z, Shi D, Jiang Y, Yang X, He M. Adiposity by Differing Measures and the Risk of Cataract in the UK Biobank: The Importance of Diabetes. Invest Ophthalmol Vis Sci 2021; 62:19. [PMID: 34797907 PMCID: PMC8606797 DOI: 10.1167/iovs.62.14.19] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Purpose To examine the association between adiposity by differing measures and incident cataract and identify important factors contributing to the association. Methods Our analysis included 153,139 adults from the UK Biobank, aged 40 to 70 years at baseline (2006-2010). Cataract was ascertained using hospital inpatient, and self-reported data until the early of 2021. Anthropometric measures, body fat percentage, and glycosylated hemoglobin (HbA1c) were measured at baseline. Results During a median follow-up of 10.9 years, 15,255 cases of incident cataract were documented. HbA1c was an important contributor to the association between obesity and incident cataract. Obesity; defined by body mass index was associated with an increased risk of cataract (hazard ratio [HR], 1.21 95% confidence interval [CI], 1.16-1.26), and this association was attenuated but remained significant after additional adjustment for HbA1c (HR, 1.05; 95% CI, 1.00-1.10). Similar results were observed for obesity defined by waist circumference or waist-to-hip ratio. Obesity defined by fat percentage was associated with an increased risk of cataract before but not after adjustment for covariates. The association between obesity defined by body mass index and incident cataract was positively significant in individuals with normal HbA1c (HR, 1.07; 95% CI, 1.02-1.13), but inversely significant in those with prediabetes (HR, 0.80; 95% CI, 0.67-0.96) or diabetes (HR, 0.74; 95% CI, 0.61-0.89). Conclusions Anthropometric measurements are more predictive of cataract than bioelectrical impedance measures. Diabetes plays an important role in the association between obesity and incident cataract.
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Affiliation(s)
- Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,Guangdong Cardiovascular Institute, Guangzhou, China
| | - Zhuoting Zhu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,Guangdong Cardiovascular Institute, Guangzhou, China
| | - Xueli Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yu Huang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,Guangdong Cardiovascular Institute, Guangzhou, China
| | - Zachary Tan
- Centre for Eye Research Australia, Victoria, Australia
| | - Wei Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Shulin Tang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zongyuan Ge
- Monash e-Research Center, Faculty of Engineering, Airdoc Research, Nvidia AI Technology Research Center, Monash University, Melbourne, Victoria, Australia
| | - Danli Shi
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Yu Jiang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Xiaohong Yang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,Centre for Eye Research Australia, Victoria, Australia.,State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
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7
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Xiao L, Zou K, Zhou D, Ouyang G, Liu S, Luo J. Changes of Blink Reflex in Type 2 Diabetes Mellitus. J Diabetes Res 2021; 2021:2473193. [PMID: 33791387 PMCID: PMC7984919 DOI: 10.1155/2021/2473193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 11/15/2020] [Accepted: 02/20/2021] [Indexed: 12/22/2022] Open
Abstract
Blink reflex provides an objective assessment of the cranial and central nervous systems. However, the relationships between body mass index, dizziness, and BR have not been explored in patients with type 2 diabetes mellitus (T2DM). Moreover, R2 duration, one of the parameters of the blink reflex, has not been studied to date. In the present study, we aimed to investigate the characteristics and influencing factors of blink reflex in patients with T2DM. We included 45 healthy subjects and 105 hospitalized patients with T2DM. The relationships between these parameters and sex, age, body mass index, duration of T2DM, hemoglobin A1c, distal symmetrical polyneuropathy (DSPN), and dizziness symptoms were analyzed. The results showed that blink reflex latencies (including R1, ipsilateral R2, and contralateral R2 latency) were negatively associated with body mass index but were positively correlated with the duration of T2DM. There were no correlations between blink reflex parameters and sex, age, and hemoglobin A1c. Patients with DSPN had longer blink reflex latencies and shorter R2 durations than those without DSPN. Patients with dizziness had longer latencies (including R1, ipsilateral R2, and contralateral R2 latencies) and shorter R2 durations (including ipsilateral R2 and contralateral R2 durations) than those without dizziness. R2 duration was also a predictive factor for blink reflex abnormality. R2 latency was the most sensitive factor and the optimal predictor of dizziness. These results demonstrate that patients with T2DM with low body mass index, longer duration of T2DM, DSPN, and dizziness-related symptoms had more abnormal blink reflex parameters, indicating more serious injuries to the cranial nerves or the central nervous system.
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Affiliation(s)
- Li Xiao
- Department of Rehabilitation, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, China
- Department of Neuroelectrophysiology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province, China
| | - Kang Zou
- Intensive Care Unit, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province, China
| | - Duoyan Zhou
- Department of Neuroelectrophysiology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province, China
| | - Guilan Ouyang
- Department of Neuroelectrophysiology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province, China
| | - Shuixiang Liu
- Department of Neuroelectrophysiology, The First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province, China
| | - Jun Luo
- Department of Rehabilitation, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, China
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8
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Yang MC, Zhu XB, Wang YX, Wu SL, Wang Q, Yan YN, Yang X, Yang JY, Chen MX, Lei YH, Wei WB. Influencing factors for peripheral and posterior lesions in mild non-proliferative diabetic retinopathy-the Kailuan Eye Study. Int J Ophthalmol 2020; 13:1467-1476. [PMID: 32953588 DOI: 10.18240/ijo.2020.09.20] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 06/18/2020] [Indexed: 02/08/2023] Open
Abstract
AIM To explore the influencing factors of diabetes type 2 patients with mild non-proliferative diabetic retinopathy (NPDR) in the Kailuan area of Tangshan, Hebei Province, China. METHODS In this non-interventional, retrospective study, 683 patients with type 2 diabetes were included in the Kailuan Diabetic Retinopathy Study involving participants with diabetes in the community-based longitudinal Kailuan Study. Based on the undilated ultra-wide field (200°; UWF) images and partial dilated digital fundus images, the diabetic retinopathy (DR) of the surveyed population was graded. Interobserver agreement was estimated by using Cohen's Kappa statistics. The main outcome indicators included gender, age, weight, height, body mass index, blood pressure, circumferences of neck, waist and hip, current smoking, levels of fasting plasma glucose (FPG), hypersensitive C-reactive protein, creatinine, and cholesterol, etc. According to different lesions' locations of patients with mild NPDR, logistic regression models were used to estimate the odds ratios (ORs) and their 95%CIs of each risk factor. RESULTS The study group of 683 patients included 570 males and 113 females. The mean age of the patients was 62.18±9.41y. Compared with dilated fundus examinations, there was fair agreement with the level of DR identified on UWF images in 63.91% of eyes (k=0.369, 95%CI, 0.00-0.00). Detected by UWF images, there were 98 patients with mild NPDR having peripheral retinal lesions, 35 patients with mild NPDR having posterior lesions, 44 patients with mild NPDR whose lesions were detected both in and out the standard two fields area, and 336 patients with non obvious DR. Parameters that conferred a statistically significant increased risks for mild NPDR with having peripheral retinal lesions were neck circumstance (OR, 1.124; 95%CI, 1.044-1.211), and with posterior lesions were FPG (OR, 1.052; 95%CI, 1.007-1.099). CONCLUSION UWF is an effectiveness means of DR screening. Moreover, it is necessary to evaluate peripheral diabetic retinal lesions which can help to estimate the severity of DR. The phenomenon that nonuniform and inhomogeneous distribution of DR lesions has been found. And the influencing factors in mild NPDR are differing by different lesions' locations.
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Affiliation(s)
- Mo-Chi Yang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China.,Department of Ophthalmology, General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, China
| | - Xiao-Bo Zhu
- Dongfang Hospital Beijing University of Chinese Medicine, Beijing 100078, China
| | - Ya-Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Shou-Ling Wu
- Department of Cardiology, Kailuan General Hospital, Tangshan 063000, Hebei Province, China
| | - Qian Wang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Yan-Ni Yan
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Xuan Yang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Jing-Yan Yang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Meng-Xi Chen
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Ya-Hui Lei
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Wen-Bin Wei
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
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