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Purpose: The purpose of this study was to evaluate the long-term efficacy of phototherapeutic keratectomy (PTK) in treating epithelial basement membrane dystrophy (EBMD). Methods: Preoperative and postoperative records were reviewed for 58 eyes of 51 patients with <3 months follow-up (range 3-170 months) treated for EBMD with PTK after failure of conservative medical treatment at Byers Eye Institute of Stanford University. Symptoms, clinical findings, and corrected distance visual acuity (CDVA) were assessed. The primary outcome measure was symptomatic recurrence as measured by erosions or visual complaints <3 months after successful PTK. Results: For eyes with visual disturbances (n=30), preoperative CDVA was ∼20/32 (0.24 Log-MAR, SD 0.21) and postoperative CDVA was ∼20/25 (0.07 LogMAR, SD 0.12; P<0.0001). Twenty-six eyes (86.7%) responded to treatment, with symptomatic recurrence in 6 eyes (23.1%) at an average of 37.7 months (SD 42.8). For eyes with painful erosions (n=29), preoperative CDVA was ∼20/25 (0.12, SD 0.19) and postoperative CDVA was ∼20/20 (0.05. SD 0.16; P=0.0785). Twenty-three eyes (79.3%) responded to treatment, with symptomatic recurrence in 3 eyes (13.0%) at an average of 9.7 months (SD 1.5). The probability of being recurrence free after a successful treatment for visual disturbances and erosions at 5 years postoperatively was estimated at 83.0% (95% confidence interval 68.7%-97.0%) and 88.0% (95% confidence interval 65.3%-96.6%), respectively. Conclusion: The majority of visual disturbances and painful erosions associated with EBMD respond to PTK. For those with a treatment response, symptomatic relief is maintained over long-term follow-up. [ABSTRACT FROM AUTHOR]

Cerebral microvascular occlusion is a common phenomenon throughout life that might require greater recognition as a mechanism of brain pathology. Failure to recanalize microvessels promptly may lead to the disruption of brain circuits and significant functional deficits. Haemodynamic forces and the fibrinolytic system are considered to be the principal mechanisms responsible for recanalization of occluded cerebral capillaries and terminal arterioles. Here we identify a previously unrecognized cellular mechanism that may also be critical for this recanalization. By using high-resolution fixed-tissue microscopy and two-photon imaging in living mice we observed that a large fraction of microemboli infused through the internal carotid artery failed to be lysed or washed out within 48 h. Instead, emboli were found to translocate outside the vessel lumen within 2–7 days, leading to complete re-establishment of blood flow and sparing of the vessel. Recanalization occurred by a previously unknown mechanism of microvascular plasticity involving the rapid envelopment of emboli by endothelial membrane projections that subsequently form a new vessel wall. This was followed by the formation of an endothelial opening through which emboli translocated into the perivascular parenchyma. The rate of embolus extravasation was significantly decreased by pharmacological inhibition of matrix metalloproteinase 2/9 activity. In aged mice, extravasation was markedly delayed, resulting in persistent tissue hypoxia, synaptic damage and cell death. Alterations in the efficiency of the protective mechanism that we have identified may have important implications in microvascular pathology, stroke recovery and age-related cognitive decline. [ABSTRACT FROM AUTHOR]

With the progression of diabetic retinopathy (DR) from the non-proliferative (NPDR) to proliferative (PDR) stage, the possibility of vision impairment increases significantly. Therefore, it is clinically important to detect the progression to PDR stage for proper intervention. We propose a segmentation-assisted DR classification methodology, that builds on (and improves) current methods by using a fully convolutional network (FCN) to segment retinal neovascularizations (NV) in retinal images prior to image classification. This study utilizes the Kaggle EyePacs dataset, containing retinal photographs from patients with varying degrees of DR (mild, moderate, severe NPDR and PDR. Two graders annotated the NV (a board-certified ophthalmologist and a trained medical student). Segmentation was performed by training an FCN to locate neovascularization on 669 retinal fundus photographs labeled with PDR status according to NV presence. The trained segmentation model was used to locate probable NV in images from the classification dataset. Finally, a CNN was trained to classify the combined images and probability maps into categories of PDR. The mean accuracy of segmentation-assisted classification was 87.71% on the test set (SD = 7.71%). Segmentation-assisted classification of PDR achieved accuracy that was 7.74% better than classification alone. Our study shows that segmentation assistance improves identification of the most severe stage of diabetic retinopathy and has the potential to improve deep learning performance in other imaging problems with limited data availability. [ABSTRACT FROM AUTHOR]

Therapeutic agents for the novel coronavirus disease 2019 (COVID-19) have been proposed, but evidence supporting their use is limited. A machine learning algorithm was developed in order to identify a subpopulation of COVID-19 patients for whom hydroxychloroquine was associated with improved survival; this population might be relevant for study in a clinical trial. A pragmatic trial was conducted at six United States hospitals. We enrolled COVID-19 patients that were admitted between 10 March and 4 June 2020. Treatment was not randomized. The study endpoint was mortality; discharge was a competing event. Hazard ratios were obtained on the entire population, and on the subpopulation indicated by the algorithm as suitable for treatment. A total of 290 patients were enrolled. In the subpopulation that was identified by the algorithm, hydroxychloroquine was associated with a statistically significant (p = 0.011) increase in survival (adjusted hazard ratio 0.29, 95% confidence interval (CI) 0.11–0.75). Adjusted survival among the algorithm indicated patients was 82.6% in the treated arm and 51.2% in the arm not treated. No association between treatment and mortality was observed in the general population. A 31% increase in survival at the end of the study was observed in a population of COVID-19 patients that were identified by a machine learning algorithm as having a better outcome with hydroxychloroquine treatment. Precision medicine approaches may be useful in identifying a subpopulation of COVID-19 patients more likely to be proven to benefit from hydroxychloroquine treatment in a clinical trial. [ABSTRACT FROM AUTHOR]

Purpose: To assess the accuracy of best-corrected visual acuity (BCVA) measured by non-ophthalmic emergency department (ED) staff with a standard Snellen chart versus an automated application (app) on a handheld smartphone (Paxos Checkup, San Francisco, CA, USA). Methods: The study included 128 subjects who presented to the Stanford Hospital ED for whom the ED requested an ophthalmology consultation. We conducted the study in two phases. During phase 1 of the study, ED staff tested patient BCVA using a standard Snellen test at 20 feet. During phase 2 of the study, ED staff tested patient near BCVA using the app. During both phases, ophthalmologists measured BCVA with a Rosenbaum near chart, which was treated as the gold standard. ED BCVA measurements were benchmarked prospectively against ophthalmologists' measurements and converted to logMAR. Results: ED logMAR BCVA was 0.21 ± 0.35 (approximately 2 Snellen lines difference ± 3 Snellen lines) higher than that of ophthalmologists when ED staff used a Snellen chart ( p = .0.00003). ED BCVA was 0.06 ± 0.40 (less than 1 Snellen line ± 4 Snellen lines) higher when ED staff used the app ( p = 0.246). Inter-observer difference was therefore smaller by more than 1 line (0.15 logMAR) with the app ( p = 0.046). Conclusions: BCVA measured by non-ophthalmic ED staff with an app was more accurate than with a Snellen chart. Automated apps may provide a means to standardize and improve the efficiency of ED ophthalmologic care. [ABSTRACT FROM AUTHOR]