Association between deep learning measured retinal vessel calibre and incident myocardial infarction in a retrospective cohort from the UK Biobank.

BACKGROUND: Cardiovascular disease is a leading cause of global death. Prospective population-based studies have found that changes in retinal microvasculature are associated with the development of coronary artery disease. Recently, artificial intelligence deep learning (DL) algorithms have been developed for the fully automated assessment of retinal vessel calibres. METHODS: In this study, we validate the association between retinal vessel calibres measured by a DL system (Singapore I Vessel Assessment) and incident myocardial infarction (MI) and assess its incremental performance in discriminating patients with and without MI when added to risk prediction models, using a large UK Biobank cohort. RESULTS: Retinal arteriolar narrowing was significantly associated with incident MI in both the age, gender and fellow calibre-adjusted (HR=1.67 (95% CI: 1.19 to 2.36)) and multivariable models (HR=1.64 (95% CI: 1.16 to 2.32)) adjusted for age, gender and other cardiovascular risk factors such as blood pressure, diabetes mellitus (DM) and cholesterol status. The area under the receiver operating characteristic curve increased from 0.738 to 0.745 (p=0.018) in the age-gender-adjusted model and from 0.782 to 0.787 (p=0.010) in the multivariable model. The continuous net reclassification improvements (NRIs) were significant in the age and gender-adjusted (NRI=21.56 (95% CI: 3.33 to 33.42)) and the multivariable models (NRI=18.35 (95% CI: 6.27 to 32.61)). In the subgroup analysis, similar associations between retinal arteriolar narrowing and incident MI were observed, particularly for men (HR=1.62 (95% CI: 1.07 to 2.46)), non-smokers (HR=1.65 (95% CI: 1.13 to 2.42)), patients without DM (HR=1.73 (95% CI: 1.19 to 2.51)) and hypertensive patients (HR=1.95 (95% CI: 1.30 to 2.93)) in the multivariable models. CONCLUSION: Our results support DL-based retinal vessel measurements as markers of incident MI in a predominantly Caucasian population.

Influence of secondhand smoke exposure on the retinal vasculature of children in Hong Kong.

BACKGROUND: A recent prospective demonstrated that cardiovascular risk factors in early childhood were associated with later cardiovascular events. However, the impact of secondhand smoke (SHS) on children is unclear. The aims of this study is to determine the effects of SHS exposure on the retinal vasculature of children. METHODS: This is a population-based cross-sectional study of children aged 6 to 8 years. All participants received comprehensive ophthalmic examinations and retinal photography. Data on SHS exposure was derived from a validated questionnaire. A validated deep-learning system was used to automatically estimate retinal arteriolar and venular calibers from retinal photographs. Associations of quantitative retinal vessel caliber values with SHS exposure, number of smokers in the household, and total number of cigarettes smoked were determined by analyses of covariance (ANCOVA) after adjusting for potential confounders. Test of trend was determined by treating categorical risk factors as continuous ordinal variables. RESULTS: Here we show children exposed to SHS have wider retinal arteriolar (CRAE 152.1 µm vs. 151.3 µm, p < 0.001) and venular (CRVE 216.7 µm vs. 215.5 µm, p < 0.001) calibers compared to those in smoke-free homes, after adjustment for different factors. Wider arteriolar and venular calibers are also associated with increasing number of smokers in the family (p trend < 0.001) and more cigarettes smoked among family smokers (p trend<0.001). CONCLUSIONS: Exposure to SHS at home is associated with changes in retinal vasculature among children. This reinforces the adverse effect of secondhand smoking around children though further research incorporating comprehensive assessment of potential confounders is necessary.

Exposure to secondhand smoke can be harmful, particularly for our heart and lung health as adults. However, the impact of secondhand smoke on children is less clear. Here, we looked at the effects of secondhand smoke exposure on vessels within children's eyes. The health of these vessels is a potential indicator of overall eye health and is also associated with cardiovascular disease. Pictures were taken of children's eyes and analyzed using a computer program. We looked at the association between vessel measurements in the eye and how much secondhand smoke the children are exposed to. We observed differences in the vessels in children exposed to secondhand smoke, compared to those from smoke-free homes. These findings indicate that secondhand smoke may affect the health of children's eyes and highlight the need to promote smoke-free home environments.

Risk of Normal Tension Glaucoma Progression From Automated Baseline Retinal-Vessel Caliber Analysis: A Prospective Cohort Study.

PURPOSE: To determine the relationship between baseline retinal-vessel calibers computed by a deep-learning system and the risk of normal tension glaucoma (NTG) progression. DESIGN: Prospective cohort study. METHODS: Three hundred and ninety eyes from 197 patients with NTG were followed up for at least 24 months. Retinal-vessel calibers (central retinal arteriolar equivalent [CRAE] and central retinal venular equivalent [CRVE]) were computed from fundus photographs at baseline using a previously validated deep-learning system. Retinal nerve fiber layer (RNFL) thickness and visual field (VF) were evaluated semiannually. The Cox proportional-hazards model was used to evaluate the relationship of baseline retinal-vessel calibers to the risk of glaucoma progression. RESULTS: Over a mean follow-up period of 34.36 ± 5.88 months, 69 NTG eyes (17.69%) developed progressive RNFL thinning and 22 eyes (5.64%) developed VF deterioration. In the multivariable Cox regression analysis adjusting for age, gender, intraocular pressure, mean ocular perfusion pressure, systolic blood pressure, axial length, standard automated perimetry mean deviation, and RNFL thickness, narrower baseline CRAE (hazard ratio per SD decrease [95% confidence interval], 1.36 [1.01-1.82]) and CRVE (1.35 [1.01-1.80]) were associated with progressive RNFL thinning and narrower baseline CRAE (1.98 [1.17-3.35]) was associated with VF deterioration. CONCLUSION: In this study, each SD decrease in the baseline CRAE or CRVE was associated with a more than 30% increase in the risk of progressive RNFL thinning and a more than 90% increase in the risk of VF deterioration during the follow-up period. Baseline attenuation of retinal vasculature in NTG eyes was associated with subsequent glaucoma progression. High-throughput deep-learning-based retinal vasculature analysis demonstrated its clinical utility for NTG risk assessment.

Deep-learning retinal vessel calibre measurements and risk of cognitive decline and dementia.

Previous studies have explored the associations of retinal vessel calibre, measured from retinal photographs or fundus images using semi-automated computer programs, with cognitive impairment and dementia, supporting the concept that retinal blood vessels reflect microvascular changes in the brain. Recently, artificial intelligence deep-learning algorithms have been developed for the fully automated assessment of retinal vessel calibres. Therefore, we aimed to determine whether deep-learning-based retinal vessel calibre measurements are predictive of risk of cognitive decline and dementia. We conducted a prospective study recruiting participants from memory clinics at the National University Hospital and St. Luke's Hospital in Singapore; all participants had comprehensive clinical and neuropsychological examinations at baseline and annually for up to 5 years. Fully automated measurements of retinal arteriolar and venular calibres from retinal fundus images were estimated using a deep-learning system. Cox regression models were then used to assess the relationship between baseline retinal vessel calibre and the risk of cognitive decline and developing dementia, adjusting for age, gender, ethnicity, education, cerebrovascular disease status, hypertension, hyperlipidemia, diabetes, and smoking. A total of 491 participants were included in this study, of whom 254 developed cognitive decline over 5 years. In multivariable models, narrower retinal arteriolar calibre (hazard ratio per standard deviation decrease = 1.258, P = 0.008) and wider retinal venular calibre (hazard ratio per standard deviation increase = 1.204, P = 0.037) were associated with increased risk of cognitive decline. Among participants with cognitive impairment but no dementia at baseline (n = 212), 44 progressed to have incident dementia; narrower retinal arteriolar calibre was also associated with incident dementia (hazard ratio per standard deviation decrease = 1.624, P = 0.021). In summary, deep-learning-based measurement of retinal vessel calibre was associated with risk of cognitive decline and dementia.

Effect of wrist dorsiflexion on ultrasound-guided radial artery catheterisation using dynamic needle tip positioning technique in adult patients: a randomised controlled clinical trial.

BACKGROUND: It is generally recommended to keep the wrist joint mildly dorsiflexed during radial artery catheterisation. However, wrist dorsiflexion might decrease the success rate of radial artery catheterisation with dynamic needle tip positioning technique. Therefore, we assessed the success rates of two groups with or without wrist dorsiflexion by 5 cm wrist elevation in adult patients. METHODS: This randomised controlled clinical trial was performed between March and December 2018 in the First Affiliated Hospital of Shantou University Medical College, China. We recruited 120 adult patients undergoing major surgical procedures and randomly allocated them into two groups: dorsiflexion group (group D) and neutral group (group N). The primary outcome was first-attempt success rates of two groups. Secondary outcomes were overall success rates within 5 min; numbers of insertion and cannulation attempts; overall catheterisation time; duration of localisation, insertion and cannulation; and complication rates of catheterisation. RESULTS: First-attempt success rate was 88.3% in group D and 81.7% in group N (p=0.444). The overall success rate within 5 min was 93.3% in group D compared with 90.0% in group N (p=0.743). Numbers of insertion and cannulation attempts, overall catheterisation time, duration of localisation and insertion, and complication rates did not show a significant difference between the two groups. Cannulation time was longer in group N (35.68 s) than that in group D (26.19 s; p<0.05). CONCLUSION: Wrist dorsiflexion may not be a necessity for ultrasound-guided radial artery catheterisation using dynamic needle tip positioning technique in adult patients. TRIAL REGISTRATION NUMBER: ChiCTR1800015262.

A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre.

Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models for the automated measurement of retinal-vessel calibre in retinal photographs, using diverse multiethnic multicountry datasets that comprise more than 70,000 images. Retinal-vessel calibre measured by the models and by expert human graders showed high agreement, with overall intraclass correlation coefficients of between 0.82 and 0.95. The models performed comparably to or better than expert graders in associations between measurements of retinal-vessel calibre and CVD risk factors, including blood pressure, body-mass index, total cholesterol and glycated-haemoglobin levels. In retrospectively measured prospective datasets from a population-based study, baseline measurements performed by the deep-learning system were associated with incident CVD. Our findings motivate the development of clinically applicable explainable end-to-end deep-learning systems for the prediction of CVD on the basis of the features of retinal vessels in retinal photographs.

A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations.

BACKGROUND: Screening for chronic kidney disease is a challenge in community and primary care settings, even in high-income countries. We developed an artificial intelligence deep learning algorithm (DLA) to detect chronic kidney disease from retinal images, which could add to existing chronic kidney disease screening strategies. METHODS: We used data from three population-based, multiethnic, cross-sectional studies in Singapore and China. The Singapore Epidemiology of Eye Diseases study (SEED, patients aged ≥40 years) was used to develop (5188 patients) and validate (1297 patients) the DLA. External testing was done on two independent datasets: the Singapore Prospective Study Program (SP2, 3735 patients aged ≥25 years) and the Beijing Eye Study (BES, 1538 patients aged ≥40 years). Chronic kidney disease was defined as estimated glomerular filtration rate less than 60 mL/min per 1·73m2. Three models were trained: 1) image DLA; 2) risk factors (RF) including age, sex, ethnicity, diabetes, and hypertension; and 3) hybrid DLA combining image and RF. Model performances were evaluated using the area under the receiver operating characteristic curve (AUC). FINDINGS: In the SEED validation dataset, the AUC was 0·911 for image DLA (95% CI 0·886 -0·936), 0·916 for RF (0·891-0·941), and 0·938 for hybrid DLA (0·917-0·959). Corresponding estimates in the SP2 testing dataset were 0·733 for image DLA (95% CI 0·696-0·770), 0·829 for RF (0·797-0·861), and 0·810 for hybrid DLA (0·776-0·844); and in the BES testing dataset estimates were 0·835 for image DLA (0·767-0·903), 0·887 for RF (0·828-0·946), and 0·858 for hybrid DLA (0·794-0·922). AUC estimates were similar in subgroups of people with diabetes (image DLA 0·889 [95% CI 0·850-0·928], RF 0·899 [0·862-0·936], hybrid 0·925 [0·893-0·957]) and hypertension (image DLA 0·889 [95% CI 0·860-0·918], RF 0·889 [0·860-0·918], hybrid 0·918 [0·893-0·943]). INTERPRETATION: A retinal image DLA shows good performance for estimating chronic kidney disease, underlying the feasibility of using retinal photography as an adjunctive or opportunistic screening tool for chronic kidney disease in community populations. FUNDING: National Medical Research Council, Singapore.

DSIM: a DisSIMilarity-based image clutter metric for targeting performance.

Previous image clutter metrics were proposed on the thought that clutter was just a perceptual effect, while we identify clutter as both perceptual and cognitive effects. Under this identification, we give a new definition of image clutter metric by analyzing the research results in the fields of visual psychology and psychophysics. According to the definition, we further put forward a DisSIMilarity (DSIM) based image clutter metric, which can also be taken as a kind of HVS-based signal-to-clutter ratio. The earlier image clutter metrics produced limited success in predicting targeting performance mainly since they did not consider brain cognitive characteristics. We develop a brain cognitive dissimilarity measure (BCDM) as a quantitative estimate of the selection weights which are allocated by brain attentional mechanism to affect visual selection processes. A human vision perceptual dissimilarity measure (VPDM), fully embodying vision perceptual properties, is first established between the target and clutter images, and then we utilize the BCDM between the two images as selection weights to pool the VPDM to be a clutter metric, which can be called DSIM metric. The metric is tested in Search_2 dataset provided by TNO Human Factors Research Institute of Netherlands. Error analysis and correlation tests demonstrate that the DSIM metric makes a more significant improvement than previously proposed metrics in predicting 62 observers' targeting performances including detection probability, false alarm probability and search time.

[Effect of propofol and inhalation anesthesia on postoperative cognitive dysfunction in the elderly: a meta-analysis].

OBJECTIVE: To compare the effects of propofol and inhalation anesthesia on the incidence of early postoperative cognitive dysfunction (POCD) in elderly patients undergoing noncardiac surgeries. METHODS: PubMed, Cochrane Library, CBM, CNKI, Wanfang data and VIP Database (by October 2012) were searched for randomized controlled trials (RCTs) comparing propofol and inhalation anesthesia for their impact on the incidence of early POCD in elderly patients undergoing noncardiac surgeries. After data extraction and quality evaluation, Stata 12.0 software was used for statistical data analysis. RESULTS: Thirteen RCTs, including 2 comparing propofol with xenon, 7 comparing propofol with sevoflurane, and 4 comparing propofol with isoflurane were obtained, involving a total of 753 patients. The odds ratio of early POCD incidence between patients with propofol anesthesia and those with xenon anesthesia, sevoflurane anesthesia, and isoflurane anesthesia were 1.62 (95% CI 0.81-3.23, P=0.533), 0.67 (95% CI 0.39-1.14, P=0.830), and 0.20 (95% CI 0.08-0.50, P=0.925), respectively. Overall, the odds ratio of early POCD incidence between propofol anesthesia and inhalation anesthesia was 0.68 (95% CI 0.47-0.98, P=0.189). Egger's test showed a publication bias of the RCTs retrieved (P=0.011). CONCLUSION: Compared with inhalation anesthesia, propofol anesthesia is associated with a lower incidence of early POCD in elderly patients, but this conclusion needs to be further verified by more well-designed large-scale RCTs.