PRéCIS:: Noninferiority of efficacy was demonstrated for a preservative-free latanoprost-timolol fixed combination compared with a BAK-containing formulation at 84 days after treatment in patients with open-angle glaucoma or ocular hypertension.The purpose of this study was to compare the effect on intraocular pressure and safety of preservative-free latanoprost-timolol fixed combination (T2347) to benzalkonium chloride-preserved latanoprost-timolol fixed combination in patients with open-angle glaucoma or ocular hypertension.Phase III, randomized, parallel-group, investigator-masked study in 10 countries. A total of 242 patients aged 18 years or older with open-angle glaucoma or ocular hypertension in both eyes controlled with a preserved latanoprost-timolol fixed combination (15.7±2.4 mm Hg overall before inclusion) were randomized at day 0 with no washout period to receive the preservative-free alternative T2347 (N=127) or remain on the preserved comparator (N=115) for 84 days. Intraocular pressure changes from day 0 were measured at 9:00 am (±1 hour) on day 42 and day 84, and noninferiority of T2347 to the preserved comparator was analyzed statistically at day 84. Safety parameters were also reported.The mean change in intraocular pressure from baseline to day 84 was -0.49±1.80 mm Hg for preservative-free T2347 and -0.49±2.25 mm Hg for the preserved comparator. These results met the noninferiority limits. Similar results were observed at day 42. There was no difference between groups in the incidence of adverse events or ocular signs. The total ocular symptoms score was better for T2347 than BPLT upon instillation at day 84 (45.9%/44.3%/9.8% of patients with improvement/no change/worsening vs. 33.6%/47.3%/19.1%; P=0.021), reflecting improvements in individual symptoms such as irritation/burning/stinging (P<0.001), and itching (P<0.01) on day 84.Preservative-free latanoprost-timolol fixed combination T2347 showed noninferior efficacy compared with the preserved comparator and was well tolerated.
Aims/Purpose: To evaluate the association between Glaucoma referral and Diabetes in participants in a population‐based glaucoma screening using artificial intelligence (AI). Methods: Analysis of cohort characteristics at baseline contact (screening visit). Glaucoma referral was defined by intraocular pressure (IOP) ≥ 24mmHg or AI score ≥ 0.73. Diabetes information, including HbA1C, was collected from electronic medical records. Our analysis used descriptive and bivariate statistics, including chi‐square tests. Significance was p < 0.05 with 95% confidence intervals (CI). Results: Data from 837 participants were analyzed, comprising 54% males, with an average age of 62±4 years, across 11 functional units of Santa Maria Local Health Unit. A significant portion of participants had diabetes (69%), of which 8.3% were referred. AI scores were lower in diabetic patients compared to the non‐diabetic sub‐cohort (0.57 vs 0.61; p = 0,009). Intrigingly, while no correlation in the overall range of HbA1C with the AI score was detected, there was a detectable trend towards higher AI scores in decompensated diabetic patients (HbA1C > 9%; n = 10): (ρ = 0.591; CI‐0.083‐0.894; p = 0.072) Conclusions: Overall, diabetes diagnosis may influence glaucoma referral programs. AI threshold for referral may be adapted to the setting (particularly if a dual diabetic retinopathy and glaucoma screening is considered). Interestingly, AI appears to detect retinal/disc abnormalities in metabolic decompensated patients.
Aims/Purpose: To evaluate the association between Glaucoma referral and Diabetes in participants in a population‐based glaucoma screening using artificial intelligence (AI). Methods: Analysis of cohort characteristics at baseline contact (screening visit). Glaucoma referral was defined by intraocular pressure (IOP) ≥ 24mmHg or AI score ≥ 0.73. Diabetes information, including HbA1C, was collected from electronic medical records. Our analysis used descriptive and bivariate statistics, including chi‐square tests. Significance was p < 0.05 with 95% confidence intervals (CI). Results: Data from 837 participants were analyzed, comprising 54% males, with an average age of 62±4 years, across 11 functional units of Santa Maria Local Health Unit. A significant portion of participants had diabetes (69%), of which 8.3% were referred. AI scores were lower in diabetic patients compared to the non‐diabetic sub‐cohort (0.57 vs 0.61; p = 0,009). Intrigingly, while no correlation in the overall range of HbA1C with the AI score was detected, there was a detectable trend towards higher AI scores in decompensated diabetic patients (HbA1C > 9%; n = 10): (ρ = 0.591; CI‐0.083‐0.894; p = 0.072) Conclusions: Overall, diabetes diagnosis may influence glaucoma referral programs. AI threshold for referral may be adapted to the setting (particularly if a dual diabetic retinopathy and glaucoma screening is considered). Interestingly, AI appears to detect retinal/disc abnormalities in metabolic decompensated patients.
Aims/Purpose: Report results of a novel AI‐powered population‐level glaucoma screening protocol. Methods: Individuals aged 55‐65 were invited for glaucoma screening in a primary‐care setting. Screening involved disc‐centered fundus photography and intraocular pressure (IOP) measurement. Glaucoma risk was assessed by an AI tool, MONA G‐Risk, using the images. A positive result was defined by either a risk score higher than 0.73 (range 0‐1) or an IOP of ≥24mmHg. Participants with a positive result were referred to a glaucoma clinic for further tests, including OCT (Heidelberg Spectralis®️) for peripapillary retinal nerve fiber layer (ppRNFL) and Bruch's membrane opening (BMO) evaluation, along with visual field (VF) testing using Humphrey 24‐2 perimetry. VF analysis followed the ocular hypertension treatment study protocol, glaucoma diagnosis followed Thessaloniki eye study criteria. Clinicaltrial.gov:NCT05875090. Results: 1038 patients were contacted, 830 accepted, 671 attended. Of these, 112 subjects performed opportunistic screening and had not been contacted previously. Most screened patients were diabetic (567/671). Mean IOP and risk scores were 14.3 mmHg (±3.9) and 0.54 (±0.12), respectively. 82 (12.2%) of subjects (diabetics: 65/567; non‐diabetics: 17/107) met referral criteria: 66 for high AI risk (9.8%), 16 (2.3%) for high IOP‐only criteria. 72 subjects underwent glaucoma clinic evaluation (AI: n = 54; IOP: n = 14; AI+IOP: n = 4). 34 met glaucoma criteria (5.1% prevalence). In glaucoma criteria eyes ( n = 46), mean IOP was 15.9mmHg (±5.5), MD was ‐6.0dB (±6.1) and ppRNFL was 90.4μm (±13.5). 10 patients presented at least moderate glaucoma (MD < ‐6dB). Mean circuit time of screening was 48.7 days (±24.3). Conclusions: Our AI‐powered glaucoma screening protocol appears effective in detecting referrable patients. IOP cutoffs‐only appear insufficient for glaucoma screening. Glaucoma prevalence detected matches published data. Our protocol's circuit time shows that glaucoma healthcare was provided in a timely manner.
Aims/Purpose: To evaluate the association between glaucoma referral and systemic hypertension (SH) in participants in a population‐based glaucoma screening using artificial intelligence (AI). Methods: compare the odds of glaucoma referral between participants with and without SH. Glaucoma referral was defined by intraocular pressure (IOP) ≥ 24mmHg or AI index ≥ 0.73. Clinical data was extracted from electronical medical records. Statistical analyses included descriptive and bivariate statistics. Results: Data from 837 participants were analyzed, comprising 54% males, with an average age of 62±4 years, across 11 functional units of Santa Maria Local Health Unit. 63,4% ( n = 530) of this cohort had SH, of which 81.1% were on angiotensin‐converting enzyme (ACE) inhibitors. SH was not a risk factor for positive Glaucoma referral (SH = 8.5% vs non‐SH = 6,86%; OR 1.663; 95% CI 0.827‐3.345). Interestingly, there appears to be a potential association between SH and a higher IOP ( p = 0.024). Furthermore, there also appears to be a higher AI mean between hypertensive patients who are medicated with ACE inhibitors and those who are not (0.58 vs 0.52, p = 0.003). Conclusions: Our findings suggest a potential association between SH and a higher IOP but not with the AI index. Type of anti‐SH medication may influence optic disc damage assessment and thus may need to be considered in the management of glaucoma patients.
eview question / Objective To summarize the current literature on retinal vascular imaging parameters in HF, with particular f o c u s o n p a t h o p h y s i o l o g y, t h e r a p e u t i c implications, and their potential use as markers of HF risk, severity and prognosis.Rationale Despite significant progress in pharmacological and device therapy of heart failure (HF), its long-term prognosis remains poor, a n d i t s p a t h o p h y s i o l o g y i s i n c o m p l e t e l y understood.Microvascular function is impaired early in the development and progression of many pathological processes like HF. Retinal imaging provides a unique opportunity for easy, noninvasive and early detection of systemic microvascular disease. Condition being studiedHeart failure is a chronic condition where the heart is unable to pump blood efficiently to meet the body's needs.This can result from various underlying conditions that damage or overwork the heart muscle, such as cardiovascular comorbidities (like high blood pressure or obesity), coronary artery disease, cardiomyopathies, arrhythmias, heart valve disease… Key characteristics of heart failure include: * Symptoms: Common symptoms include shortness of breath, fatigue, swollen legs, and rapid heartbeat.* Types: Heart failure is often classified into two main types: heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF) INPLASY
Abstract A growing number of studies have reported a link between vascular damage and glaucoma based on optical coherence tomography angiography (OCTA) imaging. This multitude of studies focused on different regions of interest (ROIs) which offers the possibility to draw conclusions on the most discriminative locations to diagnose glaucoma. The objective of this work was to review and analyse the discriminative capacity of vascular density, retrieved from different ROIs, on differentiating healthy subjects from glaucoma patients. PubMed was used to perform a systematic review on the analysis of glaucomatous vascular damage using OCTA. All studies up to 21 April 2019 were considered. The ROIs were analysed by region (macula, optic disc and peripapillary region), layer (superficial and deep capillary plexus, avascular, whole retina, choriocapillaris and choroid) and sector (according to the Garway–Heath map). The area under receiver operator characteristic curve (AUROC) and the statistical difference (p‐value) were used to report the importance of each ROI for diagnosing glaucoma. From 96 screened studies, 43 were eligible for this review. Overall, the peripapillary region showed to be the most discriminative region with the highest mean AUROC (0.80 ± 0.09). An improvement of the AUROC from this region is observed when a sectorial analysis is performed, with the highest AUROCs obtained at the inferior and superior sectors of the superficial capillary plexus in the peripapillary region (0.86 ± 0.03 and 0.87 ± 0.10, respectively). The presented work shows that glaucomatous vascular damage can be assessed using OCTA, and its added value as a complementary feature for glaucoma diagnosis depends on the region of interest. A sectorial analysis of the superficial layer at the peripapillary region is preferable for assessing glaucomatous vascular damage.
Abstract Purpose To assess the 3‐year effectiveness and safety of the XEN gel stent implanted ab interno in open‐angle glaucoma (OAG). Methods This study was a multicentre, retrospective chart review of consecutive patients with OAG who underwent ab‐interno gel stent placement alone or combined with phacoemulsification between 1 January 2014 and 1 October 2015. Outcome measures included mean changes in intraocular pressure (IOP) and IOP‐lowering medication count from medicated baseline at 1, 2, 3 (primary outcome) and 4 years (if available) postimplantation. Intraoperative complications, adverse events of special interest (AESIs) and secondary surgical interventions (SSIs) were recorded. Results The safety and effectiveness populations included 212 eyes (primary and secondary) and 174 eyes (primary), respectively. Mean IOP and medication decreased from 20.7 mmHg and 2.5 at baseline ( n = 163 primary/first implanted eyes) to 13.9 mmHg and 1.1 medications ( n = 76) at 3 years postimplantation, respectively. Mean changes from baseline in IOP (−5.6, −6.2 and −6.6 mmHg) and IOP‐lowering medication count (−1.8, −1.6 and −1.4) were statistically significant at 1, 2 and 3 years postimplantation, respectively. Results appeared comparable when implantation was performed with ( n = 76) or without ( n = 98) phacoemulsification. In primary eyes with 4‐year IOP and medication count data ( n = 27), mean IOP was 14.0 mmHg on 1.3 medications at 4 years postimplantation. Fifteen (7.1%) eyes had intraoperative complications, 31 (14.6%) experienced 46 postoperative AESIs, and 26 (12.3%) required SSI. Conclusion The gel stent effectively lowered IOP and IOP‐lowering medication count over 3 years, with a predictable and acceptable safety profile, when implanted via the traditional ab‐interno technique.
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