Blood Pressure and Glaucomatous Progression in a Large Clinical Population.

PURPOSE: To investigate the effect of systemic arterial blood pressure (BP) on rates of progressive structural damage over time in glaucoma. DESIGN: Retrospective cohort study. PARTICIPANTS: A total of 7501 eyes of 3976 subjects with glaucoma or suspected of glaucoma followed over time from the Duke Glaucoma Registry. METHODS: Linear mixed models were used to investigate the effects of BP on the rates of retinal nerve fiber layer (RNFL) loss from spectral-domain OCT (SD-OCT) over time. Models were adjusted for intraocular pressure (IOP), gender, race, diagnosis, central corneal thickness (CCT), follow-up time, and baseline disease severity. MAIN OUTCOME MEASURE: Effect of mean arterial pressure (MAP), systolic arterial pressure (SAP), and diastolic arterial pressure (DAP) on rates of RNFL loss over time. RESULTS: A total of 157 291 BP visits, 45 408 IOP visits, and 30 238 SD-OCT visits were included. Mean rate of RNFL change was -0.70 µm/year (95% confidence interval, -0.72 to -0.67 µm/year). In univariable models, MAP, SAP, and DAP during follow-up were not significantly associated with rates of RNFL loss. However, when adjusted for mean IOP during follow-up, each 10 mmHg reduction in mean MAP (-0.06 µm/year; P = 0.007) and mean DAP (-0.08 µm/year; P < 0.001) but not SAP (-0.01 µm/year; P = 0.355) was associated with significantly faster rates of RNFL thickness change over time. The effect of the arterial pressure metrics remained significant after additional adjustment for baseline age, diagnosis, sex, race, follow-up time, disease severity, and corneal thickness. CONCLUSIONS: When adjusted for IOP, lower MAP and DAP during follow-up were significantly associated with faster rates of RNFL loss, suggesting that levels of systemic BP may be a significant factor in glaucoma progression.

Impact of Intraocular Pressure Control on Rates of Retinal Nerve Fiber Layer Loss in a Large Clinical Population.

PURPOSE: To investigate the impact of intraocular pressure (IOP) control on rates of change of spectral-domain OCT (SD-OCT) retinal nerve fiber layer (RNFL) thickness in a large clinical population. DESIGN: Retrospective cohort study. PARTICIPANTS: A total of 85 835 IOP measurements and 60 223 SD-OCT tests from 14 790 eyes of 7844 patients. METHODS: Data were extracted from the Duke Glaucoma Registry, a large database of electronic medical records of patients with glaucoma and suspected disease followed over time at the Duke Eye Center and satellite clinics. All records from patients with a minimum of 6 months of follow-up and at least 2 good-quality SD-OCT scans and 2 clinical visits with Goldmann applanation tonometry were included. Eyes were categorized according to the frequency of visits with IOP below cutoffs of 21 mmHg, 18 mmHg, and 15 mmHg over time. Rates of change for global RNFL thickness were obtained using linear mixed models and classified as slow if change was slower than -1.0 µm/year; moderate if between -1.0 and -2.0 µm/year; and fast if faster than -2.0 µm/year. Multivariable models were adjusted for age, gender, race, diagnosis, central corneal thickness, follow-up time, and baseline disease severity. MAIN OUTCOME MEASURES: Rates of change in SD-OCT RNFL thickness according to levels of IOP control. RESULTS: Eyes had a mean follow-up of 3.5±1.9 years. Average rate of change in RNFL thickness was -0.68±0.59 µm/year. Each 1 mmHg higher mean IOP was associated with 0.05 µm/year faster RNFL loss (P < 0.001) after adjustment for potentially confounding variables. For eyes that had fast progression, 41% of them had IOP <21 mmHg in all visits during follow-up, whereas 20% of them had all visits with IOP <18 mmHg, but only 9% of them had all visits with IOP <15 mmHg. CONCLUSIONS: Intraocular pressure was significantly associated with rates of progressive RNFL loss in a large clinical population. Eyes with stricter IOP control over follow-up visits had a smaller chance of exhibiting fast deterioration. Our findings may assist clinicians in establishing target pressures in clinical practice.

Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs.

PURPOSE: To compare the diagnostic performance of human gradings vs predictions provided by a machine-to-machine (M2M) deep learning (DL) algorithm trained to quantify retinal nerve fiber layer (RNFL) damage on fundus photographs. DESIGN: Evaluation of a machine learning algorithm. METHODS: An M2M DL algorithm trained with RNFL thickness parameters from spectral-domain optical coherence tomography was applied to a subset of 490 fundus photos of 490 eyes of 370 subjects graded by 2 glaucoma specialists for the probability of glaucomatous optical neuropathy (GON), and estimates of cup-to-disc (C/D) ratios. Spearman correlations with standard automated perimetry (SAP) global indices were compared between the human gradings vs the M2M DL-predicted RNFL thickness values. The area under the receiver operating characteristic curves (AUC) and partial AUC for the region of clinically meaningful specificity (85%-100%) were used to compare the ability of each output to discriminate eyes with repeatable glaucomatous SAP defects vs eyes with normal fields. RESULTS: The M2M DL-predicted RNFL thickness had a significantly stronger absolute correlation with SAP mean deviation (rho=0.54) than the probability of GON given by human graders (rho=0.48; P < .001). The partial AUC for the M2M DL algorithm was significantly higher than that for the probability of GON by human graders (partial AUC = 0.529 vs 0.411, respectively; P = .016). CONCLUSION: An M2M DL algorithm performed as well as, if not better than, human graders at detecting eyes with repeatable glaucomatous visual field loss. This DL algorithm could potentially replace human graders in population screening efforts for glaucoma.