ORCID Profile
0000-0002-7818-1011
Current Organisations
The University of Edinburgh
,
Hallmarq Veterinary Imaging
,
NAVC
,
Vet Oracle Teleneurology
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Publications
Adiposity by Differing Measures and the Risk of Cataract in the UK Biobank: The Importance of Diabetes
Publisher: Association for Research in Vision and Ophthalmology (ARVO)
Date: 19-11-2021
Visual Impairment and Risk of Dementia: The UK Biobank Study
Publisher: Elsevier BV
Date: 03-2022
DOI: 10.1016/J.AJO.2021.08.010
Abstract: To investigate the relationship between visual impairment (VI) and dementia in the UK Biobank Study. Prospective cohort study. A total of 117,187 volunteers (aged 40-69 years) deemed free of dementia at baseline were included. Habitual distance visual acuity worse than 0.3 logMAR units in the better-seeing eye was used to define VI. The incident dementia was based on electronically linked hospital inpatient and death records. During a median follow-up of 5.96 years, the presence of VI was significantly associated with incident dementia (hazard ratio: 1.78 95% confidence interval: 1.18-2.68 P = .006). There was a clear trend between the severity of VI and risk of dementia (P for trend = .002). We found VI was associated with increased risk of dementia, with a progressively greater risk among those with worse visual acuity. Our findings suggested that VI might be a modifiable risk factor for dementia and highlighted the potential value of VI elimination to delay the manifestation of dementia.
Axonal Fiber Terminations Concentrate on Gyri
Publisher: Oxford University Press (OUP)
Date: 20-12-2011
Association of Retinal Age Gap With Arterial Stiffness and Incident Cardiovascular Disease
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 11-2022
DOI: 10.1161/STROKEAHA.122.038809
Abstract: Retinal parameters could reflect systemic vascular changes. With the advances of deep learning technology, we have recently developed an algorithm to predict retinal age based on fundus images, which could be a novel biomarker for aging and mortality. Therefore, we aim to investigate associations of retinal age gap with arterial stiffness index and incident cardiovascular disease (CVD). A deep learning model was trained based on 19 200 fundus images of 11 052 participants without any medical history at baseline to predict the retinal age. Retinal age gap (retinal age predicted minus chronological age) was generated for the remaining 35 917 participants. Regression models were used to assess the association between retinal age gap and arterial stiffness index. Cox proportional hazards regression models and restricted cubic splines were used to explore the association between retinal age gap and incident CVD. We found each 1-year increase in retinal age gap was associated with increased arterial stiffness index (β=0.002 [95% CI, 0.001–0.003] P .001). After a median follow-up of 5.83 years (interquartile range: 5.73–5.97), 675 (2.00%) developed CVD. In the fully adjusted model, each 1-year increase in retinal age gap was associated with a 3% increase in the risk of incident CVD (hazard ratio=1.03 [95% CI, 1.01–1.06] P =0.014). In the restricted cubic splines analysis, the risk of incident CVD increased significantly when retinal age gap reached 1.21 (hazard ratio=1.05 [95% CI, 1.00–1.10] P -overall .0001 P -nonlinear=0.0681). We found that retinal age gap was significantly associated with arterial stiffness index and incident CVD events, supporting the potential of this novel biomarker in identifying in iduals at high risk of future CVD events.
A Deep Learning–Based Fully Automated Program for Choroidal Structure Analysis Within the Region of Interest in Myopic Children
Publisher: Association for Research in Vision and Ophthalmology (ARVO)
Date: 22-03-2023
DOI: 10.1167/TVST.12.3.22
Retinal age gap as a predictive biomarker of stroke risk
Publisher: Springer Science and Business Media LLC
Date: 30-11-2022
DOI: 10.1186/S12916-022-02620-W
Abstract: The aim of this study is to investigate the association of retinal age gap with the risk of incident stroke and its predictive value for incident stroke. A total of 80,169 fundus images from 46,969 participants in the UK Biobank cohort met the image quality standard. A deep learning model was constructed based on 19,200 fundus images of 11,052 disease-free participants at baseline for age prediction. Retinal age gap (retinal age predicted based on the fundus image minus chronological age) was generated for the remaining 35,917 participants. Stroke events were determined by data linkage to hospital records on admissions and diagnoses, and national death registers, whichever occurred earliest. Cox proportional hazards regression models were used to estimate the effect of retinal age gap on risk of stroke. Logistic regression models were used to estimate the predictive value of retinal age and well-established risk factors in 10-year stroke risk. A total of 35,304 participants without history of stroke at baseline were included. During a median follow-up of 5.83 years, 282 (0.80%) participants had stroke events. In the fully adjusted model, each one-year increase in the retinal age gap was associated with a 4% increase in the risk of stroke (hazard ratio [HR] = 1.04, 95% confidence interval [CI]: 1.00–1.08, P = 0.029). Compared to participants with retinal age gap in the first quintile, participants with retinal age gap in the fifth quintile had significantly higher risks of stroke events (HR = 2.37, 95% CI: 1.37–4.10, P = 0.002). The predictive capability of retinal age alone was comparable to the well-established risk factor-based model (AUC=0.676 vs AUC=0.661, p =0.511). We found that retinal age gap was significantly associated with incident stroke, implying the potential of retinal age gap as a predictive biomarker of stroke risk.
Retinal age gap as a predictive biomarker for mortality risk
Publisher: BMJ
Date: 18-01-2022
DOI: 10.1136/BJOPHTHALMOL-2021-319807
Abstract: To develop a deep learning (DL) model that predicts age from fundus images (retinal age) and to investigate the association between retinal age gap (retinal age predicted by DL model minus chronological age) and mortality risk. A total of 80 169 fundus images taken from 46 969 participants in the UK Biobank with reasonable quality were included in this study. Of these, 19 200 fundus images from 11 052 participants without prior medical history at the baseline examination were used to train and validate the DL model for age prediction using fivefold cross-validation. A total of 35 913 of the remaining 35 917 participants had available mortality data and were used to investigate the association between retinal age gap and mortality. The DL model achieved a strong correlation of 0.81 (p ·001) between retinal age and chronological age, and an overall mean absolute error of 3.55 years. Cox regression models showed that each 1 year increase in the retinal age gap was associated with a 2% increase in risk of all-cause mortality (hazard ratio (HR)=1.02, 95% CI 1.00 to 1.03, p=0.020) and a 3% increase in risk of cause-specific mortality attributable to non-cardiovascular and non-cancer disease (HR=1.03, 95% CI 1.00 to 1.05, p=0.041) after multivariable adjustments. No significant association was identified between retinal age gap and cardiovascular- or cancer-related mortality. Our findings indicate that retinal age gap might be a potential biomarker of ageing that is closely related to risk of mortality, implying the potential of retinal image as a screening tool for risk stratification and delivery of tailored interventions.
Interthalamic adhesion size in aging dogs with presumptive spontaneous brain microhemorrhages: a comparative retrospective MRI study of dogs with and without evidence of canine cognitive dysfunction
Publisher: PeerJ
Date: 13-04-2020
DOI: 10.7717/PEERJ.9012
Abstract: Spontaneous brain microhemorrhages in elderly people are present to some degree in Alzheimer’s disease patients but have been linked to brain atrophy in the absence of obvious cognitive decline. Brain microhemorrhages have recently been described in older dogs, but it is unclear whether these are associated with brain atrophy. Diminution of interthalamic adhesion size-as measured on MRI or CT-has been shown to be a reliable indicator of brain atrophy in dogs with canine cognitive dysfunction (CCD) in comparison with successfully aging dogs. We hypothesized that aging dogs with brain microhemorrhages presenting for neurologic dysfunction but without obvious features of cognitive decline would have small interthalamic adhesion measurements, like dogs with CCD, compared with control dogs. The objective of this study was to compare interthalamic adhesion size between three groups of aging ( years) dogs: (1) neurologically impaired dogs with presumptive spontaneous brain microhemorrhages and no clinical evidence of cognitive dysfunction (2) dogs with CCD (3) dogs without clinical evidence of encephalopathy on neurologic examination (control dogs). MR images from 52 aging dogs were reviewed and measurements were obtained of interthalamic adhesion height (thickness) and mid-sagittal interthalamic adhesion area for all dogs, in addition to total brain volume. Interthalamic adhesion measurements, either absolute or normalized to total brain volume were compared between groups. Signalment (age, breed, sex), body weight, presence and number of SBMs, as well as other abnormal MRI findings were recorded for all dogs. All interthalamic adhesion measurement parameters were significantly ( P 0.05) different between control dogs and affected dogs. Both dogs with cognitive dysfunction (12/15 80%) and dogs with isolated brain microhemorrhages had more microhemorrhages than control dogs (3/25 12%). Affected dogs without cognitive dysfunction had significantly more microhemorrhages than dogs with cognitive dysfunction. In addition to signs of cognitive impairment for the CCD group, main clinical complaints for SBM and CCD dogs were referable to central vestibular dysfunction, recent-onset seizure activity, or both. Geriatric dogs with spontaneous brain microhemorrhages without cognitive dysfunction have similar MRI abnormalities as dogs with cognitive dysfunction but may represent a distinct disease category.
Associations of ophthalmic and systemic conditions with incident dementia in the UK Biobank
Publisher: BMJ
Date: 13-09-2021
DOI: 10.1136/BJOPHTHALMOL-2021-319508
Abstract: To examine independent and interactive associations of ophthalmic and systemic conditions with incident dementia. Our analysis included 12 364 adults aged 55–73 years from the UK Biobank cohort. Participants were assessed between 2006 and 2010 at baseline and were followed up until the early of 2021. Incident dementia was ascertained using hospital inpatient, death records and self-reported data. Over 1 263 513 person-years of follow-up, 2304 cases of incident dementia were documented. The multivariable-adjusted HRs (95% CI) for dementia associated with age-related macular degeneration (AMD), cataract, diabetes-related eye disease (DRED) and glaucoma at baseline were 1.26 (1.05 to 1.52), 1.11 (1.00 to 1.24), 1.61 (1.30 to 2.00) and (1.07 (0.92 to 1.25), respectively. Diabetes, heart disease, stroke and depression at baseline were all associated with an increased risk of dementia. Of the combination of AMD and a systemic condition, AMD-diabetes was associated with the highest risk for incident dementia (HR (95% CI): 2.73 (1.79 to 4.17)). In iduals with cataract and a systemic condition were 1.19–2.29 times more likely to develop dementia compared with those without cataract and systemic conditions. The corresponding number for DRED and a systemic condition was 1.50–3.24. Diabetes, hypertension, heart disease, depression and stroke newly identified during follow-up mediated the association between cataract and incident dementia as well as the association between DRED and incident dementia. AMD, cataract and DRED but not glaucoma are associated with an increased risk of dementia. In iduals with both ophthalmic and systemic conditions are at higher risk of dementia compared with those with an ophthalmic or systemic condition only.
Contrastive pre-training and linear interaction attention-based transformer for universal medical reports generation
Publisher: Elsevier BV
Date: 02-2023
Camera Adaptation for Fundus-Image-Based CVD Risk Estimation
Publisher: Springer Nature Switzerland
Date: 2022
Self-reported cataract surgery and 10-year all-cause and cause-specific mortality: findings from the National Health and Nutrition Examination Survey
Publisher: BMJ
Date: 25-10-2021
DOI: 10.1136/BJOPHTHALMOL-2021-319678
Abstract: To investigate the association of self-reported cataract surgery with all-cause and cause-specific mortality using a large-scale population-based s le. Data from the 1999–2008 cycles of the National Health and Nutrition Examination Survey were used. A self-reported history of cataract surgery was considered a surrogate for the presence of clinically significant cataract surgery. Mortality data were ascertained from National Death Index records. Hazard ratios (HRs) and 95% confidence intervals (CIs) for survival were estimated using Cox proportional hazards regression models. A total of 14 918 participants were included in the analysis. During a median follow-up of 10.8 (Interquartile range, IQR, 8.25–13.7) years, 3966 (19.1%) participants died. Participants with self-reported cataract surgery were more likely to die from all causes and specific causes (vascular disease, cancer, accident, Alzheimer’s disease, respiratory disease, renal disease and others) compared with those without (all Ps .05). The association between self-reported cataract surgery and all-cause mortality remained significant after multiple adjustments (HR=1.13 95% CI 1.01 to 1.26). For cause-specific mortality, multivariable Cox models showed that self-reported cataract surgery predicted a 36% higher risk of vascular-related mortality (HR=1.36 95% CI 1.01 to 1.82). The association with other specific causes of mortality did not reach statistical significance after multiple adjustments. This study found significant associations of self-reported cataract surgery with all-cause and vascular mortalities. Our findings provide potential insights into the pathogenic pathways underlying cataract.
Related Organisations
The University Of Edinburgh
Location: United Kingdom of Great Britain and Northern Ireland
Hallmarq Veterinary Imaging
Location: United Kingdom of Great Britain and Northern Ireland
Vet Oracle Teleneurology
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
No related grants have been discovered for Simon Platt.