Detecting visually significant cataract using retinal photograph-based deep learning

Age-related cataracts are the leading cause of visual impairment among older adults. Many significant cases remain undiagnosed or neglected in communities, due to limited availability or accessibility to cataract screening. In the present study, we report the development and validation of a retinal photograph-based, deep-learning algorithm for automated detection of visually significant cataracts, using more than 25,000 images from population-based studies. In the internal test set, the area under the receiver operating characteristic curve (AUROC) was 96.6%. External testing performed across three studies showed AUROCs of 91.6-96.5%. In a separate test set of 186 eyes, we further compared the algorithm's performance with 4 ophthalmologists' evaluations. The algorithm performed comparably, if not being slightly more superior (sensitivity of 93.3% versus 51.7-96.6% by ophthalmologists and specificity of 99.0% versus 90.7-97.9% by ophthalmologists). Our findings show the potential of a retinal photograph-based screening tool for visually significant cataracts among older adults, providing more appropriate referrals to tertiary eye centers.

Insights From Survival Analyses During 12 Years of Anti-Vascular Endothelial Growth Factor Therapy for Neovascular Age-Related Macular Degeneration

Importance

Although multiple imputation models for missing data and the use of mixed-effects models generally provide better outcome estimates than using only observed data or last observation carried forward in clinical trials, such approaches usually cannot be applied to visual outcomes from retrospective analyses of clinical practice settings, also called real-world outcomes.

Objective

To explore the potential usefulness of survival analysis techniques for retrospective clinical practice visual outcomes.

Design, Setting, and Participants

This retrospective cohort study covered a 12-year observation period at a tertiary eye center. Of 10 744 eyes with neovascular age-related macular degeneration receiving anti-vascular endothelial growth factor (VEGF) therapy between October 28, 2008, and February 1, 2020, 7802 eyes met study criteria (treatment-naive, first-treated eyes starting anti-VEGF therapy). Eyes were excluded from the analysis if they received photodynamic therapy or macular laser, any previous anti-VEGF therapy, treatment with anti-VEGF agents other than ranibizumab or aflibercept, or had an unknown date or visual acuity (VA) value at first injection.

Main Outcomes and Measures

Kaplan-Meier estimates and Cox proportional hazards modeling were used to consider VA reaching an Early Treatment Diabetic Retinopathy Study (ETDRS) letter score of 70 (Snellen equivalent, 20/40) or better, duration of VA sustained at or better than 70 (20/40), and VA declining to 35 (20/200) or worse.

Results

A total of 7802 patients (mean [SD] age, 78.7 [8.8] years; 4776 women [61.2%]; and 4785 White [61.3%]) were included in the study. The median time to attaining a VA letter score greater than or equal to 70 (20/40) was 2.0 years (95% CI, 1.87-2.32) after the first anti-VEGF injection. Predictive features were baseline VA (hazard ratio [HR], 1.43 per 5 ETDRS letter score or 1 line; 95% CI, 1.40-1.46), baseline age (HR, 0.88 per 5 years; 95% CI, 0.86-0.90), and injection number (HR, 1.12; 95% CI, 1.10-1.15). Of the 4439 of 7802 patients (57%) attaining this outcome, median time sustained at an ETDRS letter score of 70 (20/40) or better was 1.1 years (95% CI, 1.1-1.2).

Conclusions and Relevance

In this cohort study, patients with neovascular age-related macular degeneration beginning anti-VEGF therapy were more likely to experience positive visual outcomes within the first 2.0 years after treatment, typically maintaining this outcome for 1.1 years but then deteriorating to poor vision within 8.7 years. These findings demonstrate the potential usefulness of the proposed analyses. This data set, combined with the statistical approach for retrospective analyses, may provide long-term prognostic information for patients newly diagnosed with this condition.

Macular Thickness in Intermediate Age-Related Macular Degeneration Is Influenced by Disease Severity and Subretinal Drusenoid Deposit Presence

Purpose

To investigate how macular thickness varies with intermediate age-related macular degeneration (iAMD) severity and the presence of subretinal drusenoid deposits (SDDs).

Methods

A longitudinal prospective study of 143 participants >50 years of age with no to intermediate AMD who were followed with multimodal imaging and functional testing. Participants were stratified by iAMD severity according to imaging features. Macular thicknesses measurements over the central circles with 1-mm, 3-mm, and 6-mm diameters obtained from ocular coherence tomography imaging were compared across severity categories using cross-sectional (143 eyes) and longitudinal (subset of 77 eyes followed for 4 years) multivariate analyses.

Results

Compared with control eyes without large drusen or SDDs (Group 0), central maculas of lower risk eyes with unilateral large drusen (Group 1) were thicker (P = 0.014), whereas higher risk eyes with SDDs (Group SDD) were thinner (P = 0.02) in cross-sectional multivariate analyses. In longitudinal analyses, maculas with SDDs thinned more rapidly over 4 years relative to control eyes (P = 0.0058), which did not show significant thinning. More rapid central macular thinning was associated with worse baseline best-corrected visual acuity (BCVA) (P = 0.016) and more rapid BCVA decline (P = 0.0059).

Conclusions

Macular thickness in iAMD varies with disease severity, showing small increases in eyes with large drusen and decreases in eyes with SDDs. Active processes possibly related to neuroinflammation and neurodegeneration may be contributory. Longitudinal central macular thickness evaluation is an accessible outcome measure relevant to functional measures and is potentially useful for iAMD interventional studies.

Predicting risk of late age-related macular degeneration using deep learning

By 2040, age-related macular degeneration (AMD) will affect ~288 million people worldwide. Identifying individuals at high risk of progression to late AMD, the sight-threatening stage, is critical for clinical actions, including medical interventions and timely monitoring. Although deep learning has shown promise in diagnosing/screening AMD using color fundus photographs, it remains difficult to predict individuals' risks of late AMD accurately. For both tasks, these initial deep learning attempts have remained largely unvalidated in independent cohorts. Here, we demonstrate how deep learning and survival analysis can predict the probability of progression to late AMD using 3298 participants (over 80,000 images) from the Age-Related Eye Disease Studies AREDS and AREDS2, the largest longitudinal clinical trials in AMD. When validated against an independent test data set of 601 participants, our model achieved high prognostic accuracy (5-year C-statistic 86.4 (95% confidence interval 86.2-86.6)) that substantially exceeded that of retinal specialists using two existing clinical standards (81.3 (81.1-81.5) and 82.0 (81.8-82.3), respectively). Interestingly, our approach offers additional strengths over the existing clinical standards in AMD prognosis (e.g., risk ascertainment above 50%) and is likely to be highly generalizable, given the breadth of training data from 82 US retinal specialty clinics. Indeed, during external validation through training on AREDS and testing on AREDS2 as an independent cohort, our model retained substantially higher prognostic accuracy than existing clinical standards. These results highlight the potential of deep learning systems to enhance clinical decision-making in AMD patients.

Incidence of Macular Atrophy after Untreated Neovascular Age-Related Macular Degeneration: Age-Related Eye Disease Study Report 40

PURPOSE

To report the natural history of untreated neovascular age-related macular degeneration (nAMD) regarding subsequent macular atrophy.

DESIGN

Prospective cohort within a randomized, controlled trial of oral micronutrient supplements.

PARTICIPANTS

Age-Related Eye Disease Study (AREDS) participants (55-80 years) who demonstrated nAMD during follow-up (1992-2005), prior to anti-vascular endothelial growth factor (VEGF) therapy.

METHODS

Color fundus photographs were collected at annual study visits and graded centrally for late age-related macular degeneration (AMD). Incident macular atrophy after nAMD was examined by Kaplan-Meier analysis and proportional hazards regression.

MAIN OUTCOME MEASURES

Incident macular atrophy after nAMD.

RESULTS

Of the 4757 AREDS participants, 708 eyes (627 participants) demonstrated nAMD during follow-up and were eligible. The cumulative risks of incident macular atrophy after untreated nAMD were 9.6% (standard error, 1.2%), 31.4% (standard error, 2.2%), 43.1% (standard error, 2.6%), and 61.5% (standard error, 4.3%) at 2, 5, 7, and 10 years, respectively. This corresponded to a linear risk of 6.5% per year. The cumulative risk of central involvement was 30.4% (standard error, 3.2%), 43.4% (standard error, 3.8%), and 57.0% (standard error, 4.8%) at first appearance of atrophy, 2 years, and 5 years, respectively. Geographic atrophy (GA) in the fellow eye was associated with increased risk of macular atrophy (hazard ratio [HR], 1.70; 95% confidence interval [CI], 1.17-2.49; P = 0.006). However, higher 52-single nucleotide polymorphism AMD genetic risk score was not associated with increased risk of macular atrophy (HR, 1.03; 95% CI, 0.90-1.17; P = 0.67). Similarly, no significant differences were observed according to SNPs at CFH, ARMS2, or C3.

CONCLUSIONS

The rate of incident macular atrophy after untreated nAMD is relatively high, increasing linearly over time and affecting half of eyes by 8 years. Hence, factors other than anti-VEGF therapy are involved in atrophy development, including natural progression to GA. Comparison with studies of treated nAMD suggests it may not be necessary to invoke a large effect of anti-VEGF therapy on inciting macular atrophy, although a contribution remains possible. Central involvement is present in one third of eyes at the outset (similar to pure GA) and increases linearly to half at 3 years.

Prevalence, Risk, and Genetic Association of Reticular Pseudodrusen in Age-related Macular Degeneration: Age-Related Eye Disease Study 2 Report 21

PURPOSE

To determine the prevalence of reticular pseudodrusen (RPD) in eyes with age-related macular degeneration (AMD), assess the role of RPD as an independent risk factor for late AMD development, and evaluate genetic association with RPD.

DESIGN

Prospective cohort study.

PARTICIPANTS

Participants with intermediate AMD in 1 or both eyes enrolled in the Age-Related Eye Disease Study 2 (AREDS2), a 5-year multicenter study of nutritional supplement.

METHODS

Fundus autofluorescence (FAF) images from a subset of AREDS2 participants were evaluated at annual visits for presence of RPD. Six single nucleotide polymorphisms-rs10490924 (ARMS2), rs1061170 (CFH), rs2230199 (C3), rs116503776 and rs114254831 (C2/CFB), and rs943080 (VEGF-A)-and the genetic risk score (GRS) were assessed for association with RPD. Development of late AMD, defined as geographic atrophy (GA) or neovascular AMD (NVAMD), was identified.

MAIN OUTCOME MEASURES

Prevalence of RPD, odds ratio (OR) of late AMD development, and genetic associations of RPD.

RESULTS

The FAF images were evaluated for 5021 eyes (2516 participants). Reticular pseudodrusen were seen in 1186 eyes (24% of eyes, 29% of participants). Prevalence of RPD varied with baseline AREDS AMD severity level: 6% in early AMD (n = 458), 26% in intermediate AMD (n = 2606), 36% in GA (n = 682), and 19% in NVAMD (n = 1246). Mean age of participants with RPD was 79 years (standard deviation [SD], 7) and 75 years (SD, 8) in those without RPD (P < 0.0001). Reticular pseudodrusen were more frequent in female participants (65% RPD vs. 53% no RPD). Odds ratio adjusted for baseline age, gender, race, educational status, smoking, and AMD severity level for 1710 eyes at risk of developing late AMD at the next annual visit was 2.42 (95% confidence interval [CI], 1.80-3.24; P < 0.001) for GA and 1.21 (95% CI, 0.87-1.7; P = 0.26) for NVAMD. Presence of RPD was significantly associated with higher GRS (P < 0.0001) and ARMS2 risk alleles (P < 0.0001) and, at a nominal level, with C3 risk alleles (P = 0.04) and CFH risk alleles (P = 0.048 for homozygotes).

CONCLUSIONS

Participants with RPD have an increased risk of progression to GA but not NVAMD. ARMS2 risk alleles and higher GRS were associated with the presence of RPD. This study suggests that RPD are an important risk marker and should be included in classification systems used for patient prognosis.

The Association of Aspirin Use with Age-Related Macular Degeneration Progression in the Age-Related Eye Disease Studies: Age-Related Eye Disease Study 2 Report No. 20

PURPOSE

To analyze the potential association between aspirin use and progression of age-related macular degeneration (AMD).

DESIGN

Two prospective cohort studies within 2 controlled clinical trials of oral supplementation for age-related eye disease.

PARTICIPANTS

Age-Related Eye Disease Study (AREDS) participants 55 to 80 years of age and AREDS2 participants 50 to 85 years of age.

METHODS

Propensity scores for aspirin use were calculated for AREDS and AREDS2 participants separately by logistic regression. Of the participants without late AMD (geographic atrophy [GA] or neovascular AMD) in either eye at study baseline, aspirin users were matched 1:1 with nonusers by propensity score (separately for AREDS and AREDS2). Proportional hazards regression was performed, adjusting for age, on the matched participants to evaluate associations between aspirin propensity score and progression to late AMD (and its subtypes).

MAIN OUTCOME MEASURES

Progression to late AMD on color fundus photographs, graded centrally.

RESULTS

Of the 3734 eligible AREDS participants, 1049 (28.1%) were taking aspirin, and of the 2403 eligible AREDS2 participants, 1198 (49.9%) were taking aspirin. After matching by propensity score, the characteristics of the users and nonusers were similar in both studies. Of the 1950 matched AREDS participants and 1694 matched AREDS2 participants, over a median follow-up of 10.1 years and 5.0 years, respectively, the numbers who progressed to late AMD, GA, or neovascular AMD were 454 (23.3%), 345 (17.7%), and 278 (14.3%), respectively, in AREDS and 643 (38.0%), 402 (24.6%), and 341 (20.1%) in AREDS2. The hazard ratios of progression in quintile 5 (highest propensity for aspirin use) versus 1 (reference) were 1.17 (P = 0.35), 1.24 (0.25), and 0.95 (0.81), respectively, in AREDS and 1.26 (0.09), 1.46 (0.03), and 1.12 (0.58) in AREDS2. No significant association with progression to late AMD was observed for quintiles 2 through 5 for any of the 3 outcomes in either study.

CONCLUSIONS

Aspirin use was not associated significantly with progression to late AMD or its subtypes in either the AREDS or AREDS2. Patients with AMD need not avoid aspirin for this reason when its use is medically indicated.

A Deep Learning Approach for Automated Detection of Geographic Atrophy from Color Fundus Photographs

PURPOSE

To assess the utility of deep learning in the detection of geographic atrophy (GA) from color fundus photographs and to explore potential utility in detecting central GA (CGA).

DESIGN

A deep learning model was developed to detect the presence of GA in color fundus photographs, and 2 additional models were developed to detect CGA in different scenarios.

PARTICIPANTS

A total of 59 812 color fundus photographs from longitudinal follow-up of 4582 participants in the Age-Related Eye Disease Study (AREDS) dataset. Gold standard labels were from human expert reading center graders using a standardized protocol.

METHODS

A deep learning model was trained to use color fundus photographs to predict GA presence from a population of eyes with no AMD to advanced AMD. A second model was trained to predict CGA presence from the same population. A third model was trained to predict CGA presence from the subset of eyes with GA. For training and testing, 5-fold cross-validation was used. For comparison with human clinician performance, model performance was compared with that of 88 retinal specialists.

MAIN OUTCOME MEASURES

Area under the curve (AUC), accuracy, sensitivity, specificity, and precision.

RESULTS

The deep learning models (GA detection, CGA detection from all eyes, and centrality detection from GA eyes) had AUCs of 0.933-0.976, 0.939-0.976, and 0.827-0.888, respectively. The GA detection model had accuracy, sensitivity, specificity, and precision of 0.965 (95% confidence interval [CI], 0.959-0.971), 0.692 (0.560-0.825), 0.978 (0.970-0.985), and 0.584 (0.491-0.676), respectively, compared with 0.975 (0.971-0.980), 0.588 (0.468-0.707), 0.982 (0.978-0.985), and 0.368 (0.230-0.505) for the retinal specialists. The CGA detection model had values of 0.966 (0.957-0.975), 0.763 (0.641-0.885), 0.971 (0.960-0.982), and 0.394 (0.341-0.448). The centrality detection model had values of 0.762 (0.725-0.799), 0.782 (0.618-0.945), 0.729 (0.543-0.916), and 0.799 (0.710-0.888).

CONCLUSIONS

A deep learning model demonstrated high accuracy for the automated detection of GA. The AUC was noninferior to that of human retinal specialists. Deep learning approaches may also be applied to the identification of CGA. The code and pretrained models are publicly available at https://github.com/ncbi-nlp/DeepSeeNet.

DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs

PURPOSE

In assessing the severity of age-related macular degeneration (AMD), the Age-Related Eye Disease Study (AREDS) Simplified Severity Scale predicts the risk of progression to late AMD. However, its manual use requires the time-consuming participation of expert practitioners. Although several automated deep learning systems have been developed for classifying color fundus photographs (CFP) of individual eyes by AREDS severity score, none to date has used a patient-based scoring system that uses images from both eyes to assign a severity score.

DESIGN

DeepSeeNet, a deep learning model, was developed to classify patients automatically by the AREDS Simplified Severity Scale (score 0-5) using bilateral CFP.

PARTICIPANTS

DeepSeeNet was trained on 58 402 and tested on 900 images from the longitudinal follow-up of 4549 participants from AREDS. Gold standard labels were obtained using reading center grades.

METHODS

DeepSeeNet simulates the human grading process by first detecting individual AMD risk factors (drusen size, pigmentary abnormalities) for each eye and then calculating a patient-based AMD severity score using the AREDS Simplified Severity Scale.

MAIN OUTCOME MEASURES

Overall accuracy, specificity, sensitivity, Cohen's kappa, and area under the curve (AUC). The performance of DeepSeeNet was compared with that of retinal specialists.

RESULTS

DeepSeeNet performed better on patient-based classification (accuracy = 0.671; kappa = 0.558) than retinal specialists (accuracy = 0.599; kappa = 0.467) with high AUC in the detection of large drusen (0.94), pigmentary abnormalities (0.93), and late AMD (0.97). DeepSeeNet also outperformed retinal specialists in the detection of large drusen (accuracy 0.742 vs. 0.696; kappa 0.601 vs. 0.517) and pigmentary abnormalities (accuracy 0.890 vs. 0.813; kappa 0.723 vs. 0.535) but showed lower performance in the detection of late AMD (accuracy 0.967 vs. 0.973; kappa 0.663 vs. 0.754).

CONCLUSIONS

By simulating the human grading process, DeepSeeNet demonstrated high accuracy with increased transparency in the automated assignment of individual patients to AMD risk categories based on the AREDS Simplified Severity Scale. These results highlight the potential of deep learning to assist and enhance clinical decision-making in patients with AMD, such as early AMD detection and risk prediction for developing late AMD. DeepSeeNet is publicly available on https://github.com/ncbi-nlp/DeepSeeNet.

Longitudinal Study of Dark Adaptation as a Functional Outcome Measure for Age-Related Macular Degeneration

PURPOSE

To investigate the natural history of dark adaptation (DA) function as measured by the change in rod intercept time (RIT) over 4 years and to correlate RIT change with age-related macular degeneration (AMD) severity.

DESIGN

Longitudinal, single-center, observational study.

PARTICIPANTS

A total of 77 participants aged ≥50 years with a range of AMD severities.

METHODS

Participants each contributing a single study eye to the analysis were assigned into person-based AMD severity groups based on fundus characteristics (drusen, pigmentary changes, late AMD, and subretinal drusenoid deposits [SDDs]). The DA function was assessed in study eyes at baseline and 3, 6, 12, 18, 24, 36, and 48 months. Mean change in DA function over time was calculated using the slope of linear regression fits of longitudinal RIT data. Patient-reported responses on a Low Luminance Questionnaire (LLQ) were obtained at baseline and yearly. Nonparametric statistical testing was performed on all comparisons.

MAIN OUTCOME MEASURE

The RIT, defined as the time taken after a photobleach for visual sensitivity to recover detection of a 5×10^-3 cd/m² stimulus (a decrease of 3 log units), was monitored in study eyes over 4 years, and the mean rate of change was computed.

RESULTS

Longitudinal analysis of 65 study eyes followed on the standard testing protocol (mean age, 71±9.3 years; 49% were female) revealed that higher rates of RIT prolongation were correlated with AMD severity group assignment at baseline (P = 0.026) and with severity group assignments at year 4 (P = 0.0011). Study eyes that developed SDD during follow-up demonstrated higher rates of RIT prolongation relative to those that did not (P < 0.0001). Overall, higher rates of RIT prolongation were significantly correlated with greater 4-year decreases in LLQ scores (total mean score, P = 0.0032).

CONCLUSIONS

Longitudinal decline in DA function, which correlated with patient-reported functional deficits, was accelerated in eyes with greater AMD severity and especially in eyes with SDD both at baseline and at 4 years. The RIT prolongation as a measure of changing DA function may be a functional outcome measure in AMD clinical studies.

Progression of Geographic Atrophy in Age-related Macular Degeneration: AREDS2 Report Number 16

PURPOSE

To analyze the prevalence, incidence, and clinical characteristics of eyes with geographic atrophy (GA) in age-related macular degeneration (AMD), including clinical and genetic factors affecting enlargement.

DESIGN

Prospective cohort study within a controlled clinical trial.

PARTICIPANTS

Age-Related Eye Disease Study 2 (AREDS2) participants, aged 50-85 years.

METHODS

Baseline and annual stereoscopic color fundus photographs were evaluated for GA presence and area. Analyses included GA prevalence and incidence rates, Kaplan-Meier rates, mixed-model regression, and multivariable analysis of the square root of GA, area adjusted for covariates, including clinical/imaging characteristics and genotype.

MAIN OUTCOME MEASURES

(1) Presence or development of GA; (2) change in the square root of GA area over time.

RESULTS

At baseline, 517 eyes (6.2%) of 411 participants (9.8%) had pre-existing GA (without neovascular AMD), with the following characteristics: 33% central, 67% noncentral; and the following configurations: 36% small, 26% solid/unifocal, 24% multifocal, 9% horseshoe/ring, and 6% indeterminate. Of the remaining 6530 eyes at risk, 1099 eyes (17.3%) of 883 participants developed incident GA without prior neovascular disease during mean follow-up of 4.4 years. The Kaplan-Meier rate of incident GA was 19% of eyes at 5 years. In eyes with incident GA, 4-year risk of subsequent neovascular AMD was 29%. In eyes with incident noncentral GA, 4-year risk of central involvement was 57%. GA enlargement rate (following square root transformation) was similar in eyes with pre-existing GA (0.29 mm/year; 95% confidence interval 0.27-0.30) and incident GA (0.28 mm/year; 0.27-0.30). In the combined group, GA enlargement was significantly faster with noncentrality, multifocality, intermediate baseline size, and bilateral GA (P < 0.0001 for interaction in each case) but not with AREDS2 treatment assignment (P = 0.33) or smoking status (P = 0.05). Enlargement was significantly faster with ARMS2 risk (P < 0.0001), C3 non-risk (P = 0.0002), and APOE non-risk (P = 0.001) genotypes.

CONCLUSIONS

Analyses of AREDS2 data on natural history of GA provide representative data on GA evolution and enlargement. GA enlargement, which was influenced by lesion features, was relentless, resulting in rapid central vision loss. The genetic variants associated with faster enlargement were partially distinct from those associated with risk of incident GA. These findings are relevant to further investigations of GA pathogenesis and clinical trial planning.

A Deep Phenotype Association Study Reveals Specific Phenotype Associations with Genetic Variants in Age-related Macular Degeneration: Age-Related Eye Disease Study 2 (AREDS2) Report No. 14

PURPOSE

Age-related macular degeneration (AMD), a multifactorial disease with variable phenotypic presentation, was associated with 52 single nucleotide polymorphisms (SNPs) at 34 loci in a genome-wide association study (GWAS). These genetic variants could modulate different biological pathways involved in AMD, contributing to phenotypic variability. To better understand the effects of these SNPs, we performed a deep phenotype association study (DeePAS) in the Age-Related Eye Disease Study 2 (AREDS2), followed by replication using AREDS participants, to identify genotype associations with AMD and non-AMD ocular and systemic phenotypes.

DESIGN

Cohort study.

PARTICIPANTS

AREDS and AREDS2 participants.

METHODS

AREDS2 participants (discovery cohort) had detailed phenotyping for AMD; other eye conditions; cardiovascular, neurologic, gastrointestinal, and endocrine disease; cognitive function; serum nutrient levels; and others (total of 139 AMD and non-AMD phenotypes). Genotypes of the 52 GWAS SNPs were obtained. The DeePAS was performed by correlating the 52 SNPs to all phenotypes using logistic and linear regression models. Associations that reached Bonferroni-corrected statistical significance were replicated in AREDS.

MAIN OUTCOME MEASURES

Genotype-phenotype associations.

RESULTS

A total of 1776 AREDS2 participants had 5 years follow-up; 1435 AREDS participants had 10 years. The DeePAS revealed a significant association of the rs3750846 SNP at the ARMS2/HTRA1 locus with subretinal/sub-retinal pigment epithelial (RPE) hemorrhage related to neovascular AMD (odds ratio 1.55 [95% confidence interval 1.31-1.84], P = 2.67 × 10-7). This novel association remained significant after conditioning on participants with neovascular AMD (P = 2.42 × 10-4). Carriers of rs3750846 had poorer visual acuity during follow-up (P = 6.82 × 10-7) and were more likely to have a first-degree relative with AMD (P = 5.38 × 10-6). Two SNPs at the CFH locus, rs10922109 and rs570618, were associated with the drusen area in the Early Treatment Diabetic Retinopathy Study Report (ETDRS) grid (P = 2.29 × 10-11 and P = 3.20 × 10-9, respectively) and the center subfield (P = 1.24 × 10-9 and P = 6.68 × 10-8, respectively). SNP rs570618 was additionally associated with the presence of calcified drusen (P = 5.38 × 10-6). Except for positive family history of AMD with rs3750846, all genotype-phenotype associations were significantly replicated in AREDS. No pleiotropic associations were identified.

CONCLUSIONS

The association of the SNP at the ARMS2/HTRA1 locus with subretinal/sub-RPE hemorrhage and poorer visual acuity and of SNPs at the CFH locus with drusen area may provide new insights in pathophysiological pathways underlying different stages of AMD.

Treatment of bacterial cystitis with a single dose of trimethoprim, co-trimoxazole or amoxycillin compared with a course of trimethoprim

A single dose of trimethoprim, co-trimoxazole or amoxycillin was compared with a five-day course of trimethoprim for the treatment of bacterial cystitis in general practice. The respective cure rates were 80%, 80%, 65% and 86%. These differences were not statistically significant. Side effects were minimal. Single dose therapy is recommended as the treatment of choice for bacterial cystitis in domiciliary practice.

Comparison of trimethoprim alone with co-trimoxazole and sulphamethizole for treatment of urinary tract infections

This study was undertaken to compare the effectiveness of trimethoprim alone (300 mg daily) with both cotrimoxazole (0.96 g 12-hourly) and sulphamethizole (1 g eight-hourly) for the treatment of uncomplicated urinary tract infections in general practice. Treatment was continued for five days in all patients. Twenty patients were included in each group. The cure rates (sterile urine one week after finishing treatment) for trimethoprim, co-trimoxazole and sulphamethizole were 90, 95 and 90% respectively. Side effects were minimal. It is recommended that trimethoprim alone replace co-trimoxazole for the treatment of uncomplicated urinary tract infections.