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Table 3 Methods, limitations and results of relevant studies

From: The relationship between carotid disease and retinopathy in diabetes: a systematic review

First authorMethodsResultsVariables included in multivariate modelLimitations
Studies which used carotid disease as the dependent variable:
 Cardoso [23]Tertiary-care university hospital outpatients were consecutively recruited
Required to have either any microvascular complication or macrovascular complication with at least 2 modifiable risk factors
Excluded if > 80 years old, BMI ≥ 40 kg/m2, serum creatinine ≥ 2 mg/dl or poor life expectancy
Participants followed up till first endpoint or end of study
Cox regression used
No measure of carotid disease was associated with new or worsening DR in most adjusted model
From personal communication from author, for highest versus lowest tertile of IMT, the HR (95% CI) was 0.99 (0.59–1.64) P = 0.95 for CCA, 1.23 (0.73–2.06) P = 0.44 for BIF and 1.17 (0.71–1.93) P = 0.53 for ICA
Carotid plaque score ≥ 3 points was also not significant; 1.69 (0.88–3.24) P = 0.12
Age, sex, diabetes duration, BMI, smoking, physical activity, clinic SBP, number of antihypertensive drugs, use of insulin and statins, presence of macrovascular diseases and baseline DR, mean HbA1c, HDL and LDL during first year of follow upSelection bias—recruited from tertiary hospital clinic so likely complex type 2 diabetes participants
Potential measurement bias as single ophthalmologist
Unclear risk of attrition bias
 Hjelmgren [32]Participants were recruited from the Western Region initiative to Gather Information of Atherosclerosis (WINGA) database
Participants who were referred for ultrasound after suffering first ischaemic stroke or TIA were consecutively included
Excluded if < 40 years old, no ultrasound within 6 months of event or if information on DR ambiguous
Logistic regression used
Any DR did not increase the odds of carotid stenosis (OR: 0.79 (0.48–1.30), P = 0.35)Age, CHD, HF, PAD and creatinineSelection bias—only included those who had experienced an ischaemic stroke or TIA
Potential detection bias as information from medical records may not be complete and detection may vary between hospitals/clinics
Used stenosis > 50% as outcome so would have missed lower rates of occlusion/CIMT increase
Potential measurement bias—unsure about who/how many conducted the carotid ultrasound
High proportion of males
Limited generalisability
 Carbonell [7]Recruited from two outpatient university hospital clinics belonging to the same health care organisation
Participants were identified from electronic clinical records and included if > 18 years old and diabetes duration ≥ 1 year
Excluded if history of CVD, diabetic foot disease, eGFR < 60 ml/min/1.73 m2 or uACR > 300 mg/g
Logistic and multinomial logistic regression used
Advanced DR (OR: 2.66 (1.03–6.95) P = 0.044) but not mild DR (1.35 (0.66–2.76) P = 0.41) was independently associated with carotid plaque
Advanced DR (OR 4.71 (1.48–15.04) P = 0.009) was also independently associated with increased odds of ≥ 2 carotid plaques
The presence of any DR was not statistically significantly associated with any plaque (1.64 (0.85–3.17) P = 0.14) or ≥ 2 plaques (1.93 (0.83–4.47) P = 0.129)
Age, sex, diabetes duration, smoking, diastolic BP, dyslipidaemia, uACR, BMI, pulse pressure and LDLSelection bias—only recruited from clinics
Excluded those with CVD and in doing so may have excluded some with carotid disease
Sample size was calculated on the presence of DR and not advanced DR
Potential measurement bias as single ophthalmologist and sonographer at each site
 Liu [34]Participants were from the Diabetes Health Management Program, a community-based system of electronic health records recruited via free health check-up annually for residents and household survey at Meilong Town
Excluded if < 40 years of age or history of CVD
Linear and logistic multiple regressions used
Any DR was associated with CCA IMT (mm) (coefficient 0.015, P = 0.010, Standard error: 0.080) in linear Regression
Any DR was associated with CCA IMT > 1 mm (OR:1.84 (1.02–3.31) P = 0.043), presence of plaque (1.87 (1.03–3.39) P = 0.039) and subclinical atherosclerosis (1.93 (1.03–3.60) P = 0.039) in most adjusted logistic regression models
Age, sex, alcohol use and LDL in all models. The logistic regressions also adjusted for smoking, hypertension, diabetes duration, HbA1c, use of antidiabetic drugs, insulin use, antihypertensive drugs, obesity, Triglycerides, total cholesterol, HDL, eGFR, uACR and GGTExcluded those with CVD and in doing so may have excluded some with carotid disease
Potential measurement bias as single ophthalmologist and sonographer
Unclear risk of selection bias
 Alonso [28]Recruited based on medical records from an outpatient clinic and diabetic eye disease program
Tried to match those with DR and those without on age and sex
Excluded those with CVD or impaired renal function
General linear models used for IMT and logistic regression for plaque presence
Any DR was associated with mean ICA IMT (P = 0.0176) but not CCA IMT or bifurcation IMT
Any DR increased odds of any plaque (OR: 1.71 (1.03–2.85) P = 0.0366) and the odds of ≥ 2 plaques (3.17 (1.75–5.75)) P < 0.0001)
All models adjusted for age. Also, in general linear models CCA IMT adjusted for smoking; bifurcation IMT for hypertension; and ICA IMT for sex. In logistic regression for any plaque adjusted for hypertension and smoking; and for ≥ 2 plaques for sex and dyslipidaemiaSelection bias—only recruited from clinics
Excluded those with CVD and in doing so may have excluded some with carotid disease
Potential measurement bias as single ophthalmologist and sonographer
 Jung [27]Hospital patients’ notes were retrospectively reviewed
Excluded if malignancy, hepatic failure, acute infection, acute metabolic complications, fatal arrhythmia or CVD
Logistic regression used
Any DR was independently associated with CCA IMT > 1 mm (OR: 3.8 (1.4–10.2)) but not > 2 carotid plaques (OR: 5.7 (0.6–51.3))Age, diabetes duration, smoking, hypertension, HbA1c, cardiac autonomic neuropathy, brachial-ankle pulse wave velocity, statin use, ACE-I/ARB use and eGFRPotential detection bias -retrospectively analysed medical notes which relies on all data being available/recorded appropriately
All tests would have been done as part of usual diabetes care so may reflect a higher risk population
Excluded those with CVD and in doing so may have excluded some with carotid disease
Potential measurement bias—single ophthalmologist and limited detail on who/how many performed ultrasounds
Relatively small, young sample
Limited generalisability
 Cardoso [29]Tertiary -care university hospital outpatients were consecutively recruited
Required to have either any microvascular complication or macrovascular complication with at least 2 modifiable risk factors
Excluded if > 80 years old, BMI ≥ 40 kg/m2, serum creatinine ≥ 2 mg/dl or poor life expectancy
Generalised linear models were used with DR as a fixed factor to assess relationship with IMT
Logistic regression used to assess relationship between DR and plaque score
Any DR was associated with increased odds of a plaque score > 2 (OR: 1.70 (1.02–2.84) P = 0.043)
Any DR was not independently associated with IMT at ICA, BIF or CCA in either logistic or linear regression but effect size and P-values not given
The logistic regression for plaque score adjusted for age, sex, smoking, antihypertensive use and aortic pulse wave velocity. All IMT linear and logistic regressions adjusted for age and night-time pulse pressure. Additionally, CCA IMT adjusted for sex, smoking and antihypertensive use; bifurcation IMT for LDL and smoking; and ICA IMT for sex and C-reactive protein in logistic regression as well as smoking in linear regression.Potential selection bias—recruited from tertiary hospital clinic so likely complex type 2 diabetes participants
Potential measurement bias as single ophthalmologist
 Son [10]Consecutive patients of an outpatient diabetes centre diagnosed with diabetes during the study period were recruited
Excluded those with longer duration of diabetes, CVD or cerebrovascular events
Logistic regression used
Any DR increased the odds of plaque or increased CCA IMT > 0.9 mm (OR: 6.57 (1.68–25.71) P = 0.007) compared to those with CCA IMT < 0.9 mm and no plaqueAge, sex, smoking, hypertension, BMI, diabetic nephropathy, HbA1c, fasting glucose, HDL and LDLHigh proportion of males
Only comprised participants with newly diagnosed diabetes
Small sample size
Excluded those with CVD and in doing so may have excluded some with carotid disease
Potential measurement bias – single ophthalmologist and limited detail on who/how many performed ultrasounds
 Lacroix [33]Patients with diabetes referred to a vascular laboratory were consecutively recruited
Excluded those with life expectancy > 12 months, a recent (< 6 weeks) stroke or TIA, carotid surgery, cervical radiotherapy or symptoms of carotid disease
Multiple logistic regression used
Any DR increased odds of any carotid stenosis (2.38 (1.06–5.33) P = 0.03)
Any DR increased odds of carotid stenosis ≥ 60% (3.62 (1.12–11.73), P < 0.0001) compared to no or < 60% stenosis
Age > 70 years, hypertension, BMI, history of CHD and family history of diabetes in model for any stenosis. Sex, ABI and history of ischemic neurological disorder or cervical bruit in model for stenosis ≥ 60%Selection bias—recruited from referrals to a specialist clinic and excluded those with symptoms of carotid disease
Study was focussed on screening for carotid disease
Potential measurement bias—limited detail on who/how many people performed ophthalmic exams or ultrasounds
 Distiller [31]Patients with diabetes were recruited from the Centre for Diabetes and Endocrinology
Included those with at least 10 measurements of Hba1c in last 5 years, normal renal function, no proteinuria
Those on statins > 5 years, with an underlying autoimmune disease, nephropathy, on steroids or those with hypothyroidism with inadequate replacement were excluded
Multiple logistic regression, linear regression and ordinal logistic regression used
Any DR increased the odds of plaque; OR: 3.65 (1.11–12.02) P = 0.033, but not IMT or IMT risk (effect for these not given)In multiple regression for IMT adjusted for age, diabetes duration, BMI, hypertension and HDL. In ordinal regression for IMT risk adjusted for age, triglyceride:HDL ratio and HbA1c. In logistic regression for plaque adjusted for age, hypertension and smokingSome selection bias as recruited from a diabetes centre and only Caucasians with long diabetes duration
Potential measurement bias—limited information given on ascertainment of DR status
First authorMethodsResultsResults adjusted forLimitations
Studies which used diabetic retinopathy as the dependent variable:
 Ichinohasama [8]Unclear how participants recruited, but underwent assessment at hospital
Excluded those with HbA1c < 6.5 and if not on ongoing diabetes therapy, those on haemodialysis, or who had malignancy, inflammatory disease, chronic respiratory disease, macular degeneration, or glaucoma or other retinal disease
Logistic regression analysis used
CCA IMT increased the odds of mild NPDR (OR: 8.65 (1.95–38.4) P = 0.005, per 1 mm increase)Age, sex, duration of diabetes, HbA1c diastolic blood pressure, heart rate, creatinine, central macular thickness and mean blur rate in the overall optic nerve headPotential selection bias—participant recruitment was not clear
Only right sided IMT and DR assessed
Participants had no or mild DR, none with more severe DR
Excluded those with T2D with HbA1c < 6.5 and diet controlled
Potential measurement bias as single ophthalmologist and sonographer
 Yun [10]Participants registered at a public health centre who had participated in another survey were recruited
Excluded those with missing data including blood, urine, HbA1c, diabetes duration, CCA-IMT, carotid plaque, baPWV, DR outcome
Logistic regression analysis used
CCA IMT was not associated with DR in most adjusted model (OR for tertile 2: 1.16 (0.67–2.02) and tertile 3: 1.06 (0.59–1.90) when compared to tertile 1, P = 0.844)
Carotid plaque was not associated with DR (OR: 1.20 (0.75–1.91))
Age, sex, duration of diabetes, HbA1c, total cholesterol, triglycerides, HDL, eGFR, BMI and history of hypertensionHigh proportion of females
Potential measurement bias—unclear about who graded DR and the reliability and validity of the ultrasounds
 Araszkiewicz [30]Hospital patients admitted for diabetes management recruited consecutively
Excluded those > 50 years old, liver dysfunction, chronic kidney disease ≥ stage 3, anaemia, acute inflammation, CVD, CHD, PVD, DKA on admission or carotid stenosis > 50%
Logistic regression analysis performed
CCA IMT not associated with DR in multivariate analysis (OR: 1.00 (0.99–1.01) P = 0.169 per 1 μm increase)Age, sex, diabetes duration, albuminuria, BP, postprandial glucose, HbA1c, central augmentation index and peripheral augmentation indexPotential selection bias—recruited from a hospital
Only right sided IMT measured
Likely excluded those with higher IMT as excluded if stenosis > 50% and CVD
Small numbers
Potential measurement bias as single ophthalmologist and unclear who performed ultrasounds
 Rema [9]A random sample of 450 participants with known and 150 participants with newly diagnosed diabetes from a population-based study were assessed
Multivariate regression models were used
Mean IMT increased the odds of DR (OR: 2.9 (1.17–7.33), P = 0.024 per 1 mm increase)Age, HbA1c, duration of diabetes and microalbuminuriaUnclear selection bias risk
Only used the right carotid ultrasound
  1. DR diabetic retinopathy, VTDR vision threatening diabetic retinopathy, IMT intima-media thickness, CCA common carotid artery, ICA internal carotid artery, BIF bifurcation, CVD cardiovascular disease, uACR urinary albumin:creatinine ratio, CHD coronary heart disease, PVD peripheral vascular disease, DKA diabetic ketoacidosis, TIA transient ischaemic attack, HF heart failure, PAD peripheral arterial disease, BP blood pressure, BMI body mass index, LDL low density lipoprotein, HDL high density lipoprotein, eGFR estimated glomerular filtration rate, GGT gamma-glutamyl transferase, ACE-I angiotensin converting enzyme inhibitors, ARB angiotensin receptor blockers, ABIs ankle-brachial index