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Ocular surface disease (OSD) is a complex condition that can cause a range of symptoms (e.g, dryness, irritation, and pain) and can significantly impact the quality of life of affected individuals. Iatrogenic OSD, a common finding in patients with glaucoma who receive chronic therapy with topical ocular antihypertensive drugs containing preservatives such as benzalkonium chloride (BAK), has been linked to damage to the ocular surface barrier, corneal epithelial cells, nerves, conjunctival goblet cells, and trabecular meshwork. Chronic BAK exposure activates inflammatory pathways and worsens symptoms, compromising the success of subsequent filtration surgery in an exposure-dependent manner. In eyes being treated for glaucoma, symptomatic treatment of OSD may provide some relief, but addressing the root cause of the OSD often necessitates reducing or, ideally, eliminating BAK toxicity. Strategies to decrease BAK exposure in patients with glaucoma encompass the use of preservative-free formulations or drugs with alternative and less toxic preservatives such as SofZia®, Polyquad, potassium sorbate, or Purite®. Though the benefits of these alternative preservatives are largely unproven, they might be considered when financial constraints prevent the use of preservative-free versions. For patients receiving multiple topical preserved drugs, the best practice is to switch to nonpreserved equivalents wherever feasible, regardless of OSD severity. Furthermore, nonpharmacological approaches, including laser or incisional procedures, should be considered. This review explores the effects of BAK on the ocular surface and reviews strategies for minimizing or eliminating BAK exposure in patients with glaucoma in order to significantly improve their quality of life and prevent complications associated with chronic exposure to BAK.
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Overview: This study evaluates the diagnostic accuracy of a multimodal large language model (LLM), ChatGPT-4, in recognizing glaucoma using color fundus photographs (CFPs) with a benchmark dataset and without prior training or fine tuning. Methods: The publicly accessible Retinal Fundus Glaucoma Challenge "REFUGE" dataset was utilized for analyses. The input data consisted of the entire 400 image testing set. The task involved classifying fundus images into either 'Likely Glaucomatous' or 'Likely Non-Glaucomatous'. We constructed a confusion matrix to visualize the results of predictions from ChatGPT-4, focusing on accuracy of binary classifications (glaucoma vs non-glaucoma). Results: ChatGPT-4 demonstrated an accuracy of 90% with a 95% confidence interval (CI) of 87.06%-92.94%. The sensitivity was found to be 50% (95% CI: 34.51%-65.49%), while the specificity was 94.44% (95% CI: 92.08%-96.81%). The precision was recorded at 50% (95% CI: 34.51%-65.49%), and the F1 Score was 0.50. Conclusion: ChatGPT-4 achieved relatively high diagnostic accuracy without prior fine tuning on CFPs. Considering the scarcity of data in specialized medical fields, including ophthalmology, the use of advanced AI techniques, such as LLMs, might require less data for training compared to other forms of AI with potential savings in time and financial resources. It may also pave the way for the development of innovative tools to support specialized medical care, particularly those dependent on multimodal data for diagnosis and follow-up, irrespective of resource constraints.
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PURPOSE: To investigate the capability of ChatGPT for forecasting the conversion from ocular hypertension (OHT) to glaucoma based on the Ocular Hypertension Treatment Study (OHTS). DESIGN: Retrospective case-control study. PARTICIPANTS: A total of 3008 eyes of 1504 subjects from the OHTS were included in the study. METHODS: We selected demographic, clinical, ocular, optic nerve head, and visual field (VF) parameters 1 year before glaucoma development from the OHTS participants. Subsequently, we developed queries by converting tabular parameters into textual format based on both eyes of all participants. We used the ChatGPT application program interface (API) to automatically perform ChatGPT prompting for all subjects. We then investigated whether ChatGPT can accurately forecast conversion from OHT to glaucoma based on various objective metrics. MAIN OUTCOME MEASURE: Accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and weighted F1 score. RESULTS: ChatGPT4.0 demonstrated an accuracy of 75%, AUC of 0.67, sensitivity of 56%, specificity of 78%, and weighted F1 score of 0.77 in predicting conversion to glaucoma 1 year before onset. ChatGPT3.5 provided an accuracy of 61%, AUC of 0.62, sensitivity of 64%, specificity of 59%, and weighted F1 score of 0.63 in predicting conversion to glaucoma 1 year before onset. CONCLUSIONS: The performance of ChatGPT4.0 in forecasting development of glaucoma 1 year before onset was reasonable. The overall performance of ChatGPT4.0 was consistently higher than ChatGPT3.5. Large language models (LLMs) hold great promise for augmenting glaucoma research capabilities and enhancing clinical care. Future efforts in creating ophthalmology-specific LLMs that leverage multimodal data in combination with active learning may lead to more useful integration with clinical practice and deserve further investigations.
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PURPOSE: To test an online training course for non-ophthalmic diabetic retinopathy (DR) graders for recognition of glaucomatous optic nerves in Vietnam. METHODS: This was an uncontrolled, experimental, before-and-after study in which 43 non-ophthalmic DR graders underwent baseline testing on a standard image set, completed a self-paced, online training course and were retested using the same photographs presented randomly. Twenty-nine local ophthalmologists completed the same test without the training course. DR graders then underwent additional one-to-one training by a glaucoma specialist and were retested. Test performance (% correct, compared with consensus grades from four fellowship-trained glaucoma experts), sensitivity, specificity, positive and negative predictive value, and area under the receiver operating (AUC) curve, were computed. RESULTS: Mean age of DR graders (32.6±5.5 years) did not differ from ophthalmologists (32.3±7.3 years, p=0.13). Online training required a mean of 297.9 (SD 144.6) minutes. Graders' mean baseline score (33.3%±14.3%) improved significantly after training (55.8%±12.6%, p<0.001), and post-training score did not differ from ophthalmologists (58.7±15.4%, p=0.384). Although grader sensitivity reduced before [85.5% (95% CI 83.5% to 87.3%)] versus after [80.4% (78.3% to 82.4%)] training, specificity improved significantly [47.8 (44.9 to 50.7) vs 79.8 (77.3 to 82.0), p<0.001]. Grader AUC also improved after training [66.6 (64.9 to 68.3)] to [80.1 (78.5 to 81.6), p<0.001]. Additional one-to-one grader training by a glaucoma specialist did not further improve grader scores. CONCLUSION: Non-ophthalmic DR graders can be trained to recognise glaucoma using a short online course in this setting, with no additional benefit from more expensive one-to-one training. After 5-hour online training in recognising glaucomatous optic nerve head, scores of non-ophthalmic DR graders doubled, and did not differ from local ophthalmologists. Intensive one-to-one training did not further improve performance.
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Diabetes Mellitus , Retinopatía Diabética , Glaucoma , Disco Óptico , Humanos , Adulto , Retinopatía Diabética/diagnóstico , Vietnam , Glaucoma/diagnóstico , Valor Predictivo de las Pruebas , FotograbarRESUMEN
Purpose: To evaluate the efficiency of large language models (LLMs) including ChatGPT to assist in diagnosing neuro-ophthalmic diseases based on case reports. Design: Prospective study. Subjects or Participants: We selected 22 different case reports of neuro-ophthalmic diseases from a publicly available online database. These cases included a wide range of chronic and acute diseases that are commonly seen by neuro-ophthalmic sub-specialists. Methods: We inserted the text from each case as a new prompt into both ChatGPT v3.5 and ChatGPT Plus v4.0 and asked for the most probable diagnosis. We then presented the exact information to two neuro-ophthalmologists and recorded their diagnoses followed by comparison to responses from both versions of ChatGPT. Main Outcome Measures: Diagnostic accuracy in terms of number of correctly diagnosed cases among diagnoses. Results: ChatGPT v3.5, ChatGPT Plus v4.0, and the two neuro-ophthalmologists were correct in 13 (59%), 18 (82%), 19 (86%), and 19 (86%) out of 22 cases, respectively. The agreement between the various diagnostic sources were as follows: ChatGPT v3.5 and ChatGPT Plus v4.0, 13 (59%); ChatGPT v3.5 and the first neuro-ophthalmologist, 12 (55%); ChatGPT v3.5 and the second neuro-ophthalmologist, 12 (55%); ChatGPT Plus v4.0 and the first neuro-ophthalmologist, 17 (77%); ChatGPT Plus v4.0 and the second neuro-ophthalmologist, 16 (73%); and first and second neuro-ophthalmologists 17 (17%). Conclusions: The accuracy of ChatGPT v3.5 and ChatGPT Plus v4.0 in diagnosing patients with neuro-ophthalmic diseases was 59% and 82%, respectively. With further development, ChatGPT Plus v4.0 may have potential to be used in clinical care settings to assist clinicians in providing quick, accurate diagnoses of patients in neuro-ophthalmology. The applicability of using LLMs like ChatGPT in clinical settings that lack access to subspeciality trained neuro-ophthalmologists deserves further research.
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INTRODUCTION: The purpose of this study was to evaluate the capabilities of large language models such as Chat Generative Pretrained Transformer (ChatGPT) to diagnose glaucoma based on specific clinical case descriptions with comparison to the performance of senior ophthalmology resident trainees. METHODS: We selected 11 cases with primary and secondary glaucoma from a publicly accessible online database of case reports. A total of four cases had primary glaucoma including open-angle, juvenile, normal-tension, and angle-closure glaucoma, while seven cases had secondary glaucoma including pseudo-exfoliation, pigment dispersion glaucoma, glaucomatocyclitic crisis, aphakic, neovascular, aqueous misdirection, and inflammatory glaucoma. We input the text of each case detail into ChatGPT and asked for provisional and differential diagnoses. We then presented the details of 11 cases to three senior ophthalmology residents and recorded their provisional and differential diagnoses. We finally evaluated the responses based on the correct diagnoses and evaluated agreements. RESULTS: The provisional diagnosis based on ChatGPT was correct in eight out of 11 (72.7%) cases and three ophthalmology residents were correct in six (54.5%), eight (72.7%), and eight (72.7%) cases, respectively. The agreement between ChatGPT and the first, second, and third ophthalmology residents were 9, 7, and 7, respectively. CONCLUSIONS: The accuracy of ChatGPT in diagnosing patients with primary and secondary glaucoma, using specific case examples, was similar or better than senior ophthalmology residents. With further development, ChatGPT may have the potential to be used in clinical care settings, such as primary care offices, for triaging and in eye care clinical practices to provide objective and quick diagnoses of patients with glaucoma.
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Purpose: To evaluate incisional or excisional tissue-level effects of ab interno goniotomy techniques on human trabecular meshwork (TM). Methods: The TM from human cadaveric corneal rim tissue was treated using three devices: (1) Kahook Dual Blade (KDB) GLIDE, (2) iAccess, and (3) SION. Two human corneal rims were used for each of the iAccess and SION devices and one with the KDB GLIDE, with 360 degrees of TM treated in each case. Sections were then prepared for analysis and comparison between devices. Tissue samples underwent standard histologic processing with H&E stain, followed by comparative analyses. Results: Areas treated with the KDB GLIDE device resulted in nearly complete excision of TM overlying the canal of Schlemm without injury to surrounding tissues. The iAccess device can be used as a focal trephine to create holes or dragged for TM disruption. When used to create holes, iAccess punched through the full thickness of the TM and also disrupted the anterior scleral tissue. It caused some incisional openings through the TM but with significant leaflets remaining and minimal true "hole-punch" effect. When the device tip was dragged, iAccess incised the TM and left debris behind with little, if any, excision of tissue. SION led to both incision and excision of TM with incision predominating over excision. Conclusion: The various methods evaluated to perform ab interno goniotomy resulted in varying degrees of TM incision or excision. Only the KDB GLIDE device resulted in reliable excision of TM, while the other devices produced incision or minimal excision of tissue with residual leaflets and debris. Use of iAccess resulted in focal disruption of the anterior scleral wall. Because incisional approaches that leave longer residual leaflets may be more prone to fibrosis and closure compared to excisional treatments, clinical correlation will be necessary to better understand the significance of these findings with respect to relative effectiveness of intraocular pressure lowering in eyes with glaucoma.
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Purpose: To characterize clinical outcomes of transluminal dilation of the canal of Schlemm using the STREAMLINE Surgical System combined with phacoemulsification in eyes of Hispanic patients diagnosed with mild to moderate primary open-angle glaucoma. Methods: This was a prospective analysis of all cases performed and followed up to 12 months. All eyes underwent medication washout preoperatively. Reduction in intraocular pressure (IOP) from unmedicated baseline, as well as medications from pre-washout baseline, were analyzed at postoperative Day 1, Week 1, and Months 1, 3, 6, 9, and 12. Results: All 37 patients were Hispanic, 83.8% were female, and mean (standard deviation) age was 66.0 (10.5) years. Mean medicated preoperative IOP was 16.9 (3.2) mmHg using a mean of 2.1 (0.9) medications, unmedicated baseline IOP (after washout) was 23.2 (2.3) mmHg, and mean IOP at every postoperative study visit was significantly lower (p<0.0002). Mean IOP from month 1 through the first postoperative year ranged from 14.7-16.2 mmHg, representing a reduction of 7.0-8.5 mmHg (30.7-36.5%). At month 12, 80% of all eyes (28/35) and 77.8% of medication-free eyes (14/18) had IOP reduction ≥20% from unmedicated baseline, and 51.4% of eyes (18/35) were medication-free. Mean medication use was significantly reduced (by 59.9-74.6%, p<0.0001) at every postoperative study visit. The only adverse event occurring in >1 eye was high IOP (n=4) which was responsive to topical medical therapy; no adverse events were attributed to the transluminal dilation procedure. Conclusion: Transluminal dilation of the canal of Schlemm using the STREAMLINE Surgical System combined with phacoemulsification safely and effectively reduced both IOP and dependence on IOP-lowering medications in a Hispanic population diagnosed with POAG and should be considered at the time of phacoemulsification in Hispanic patients who have a need for IOP reduction, medication reduction, or both.
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There has been a recent surge in the number of publications centered on the use of artificial intelligence (AI) to diagnose various systemic diseases. The Food and Drug Administration has approved several algorithms for use in clinical practice. In ophthalmology, most advances in AI relate to diabetic retinopathy, which is a disease process with agreed upon diagnostic and classification criteria. However, this is not the case for glaucoma, which is a relatively complex disease without agreed-upon diagnostic criteria. Moreover, currently available public datasets that focus on glaucoma have inconstant label quality, further complicating attempts at training AI algorithms efficiently. In this perspective paper, we discuss specific details related to developing AI models for glaucoma and suggest potential steps to overcome current limitations.
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Purpose: To determine the drop volume and total number of dispensed drops using the Nanodropper eyedrop bottle adaptor (Nanodropper, Inc.) compared to drops dispensed from stock bottles to potentially limit ocular toxicity of these eyedrops and prolong bottle use. Patients and Methods: Six topical ocular hypotensive medications (5 solutions, 1 suspension), one steroid (suspension) and two artificial tears emulsions were selected for this study. An analytical balance was used to determine the mass per 10 drops with and without the volume-reducing adaptor and repeated until the bottles were completely emptied. The density of each product was determined using the calculated density. The average drop volume and number of drops per bottle for the nine medications were compared with and without the adaptor with paired t-testing. Results: When all medications were assessed, the drops delivered with the adaptor were 62.1% smaller than eyedrops administered from standard bottles. Compared to stock bottle eyedrops, which had a mean volume of 39.8 ± 2.1 µL, the adaptor resulted in drops with a mean volume of 15.1 ± 1.0 µL, p<0.0001. The adaptor delivered 2.6x the number of drops dispensed from a standard 2.5 mL bottle (184.1 ± 15.1 drops with adaptor and 69.8 ± 4.9 drops from stock bottle, p<0.0001). Conclusion: The Nanodropper eyedrop bottle adaptor can significantly reduce drop volume and increase the overall number of drops dispensed compared with stock eyedrop bottles. Further studies are needed to elucidate the clinical impact of utilizing decreased drop volume with direct comparison to current standards of care.
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PRCIS: Glaucoma patients exhibit worse indices of sleep function by both objective and subjective metrics compared with controls. PURPOSE: The purpose of this study is to characterize the sleep parameters and physical activity levels of glaucoma patients compared with controls. PATIENTS AND METHODS: A total of 102 patients with a diagnosis of glaucoma in at least 1 eye and 31 control subjects were enrolled in the study. Participants completed the Pittsburgh Sleep Quality Index (PSQI) during enrollment and then wore wrist actigraphs for 7 consecutive days to characterize circadian rhythm, sleep quality, and physical activity. The primary outcomes of the study were subjective and objective metrics of sleep quality using the PSQI and actigraphy devices, respectively. The secondary outcome was physical activity, measured by the actigraphy device. RESULTS: From the PSQI survey, glaucoma patients had higher (worse) scores compared with controls for sleep latency, sleep duration, and subjective sleep quality, whereas scores for sleep efficiency were lower (better), suggesting more time spent in bed asleep. By actigraphy, time in bed was significantly higher in glaucoma patients as was time awake after sleep onset. Interdaily stability, quantifying the synchronization to the 24-hour light-dark cycle, was lower in glaucoma patients. There were no other significant differences between glaucoma and control patients with regard to rest-activity rhythms or physical activity metrics. In contrast to the survey data, findings from the actigraphy demonstrated that there were no significant associations between the study group and controls regarding sleep efficiency, onset latency, or total sleep time. CONCLUSIONS: In this study, patients with glaucoma demonstrated several subjective and objective differences in sleep function when compared with controls, whereas physical activity metrics were similar.
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Glaucoma , Calidad del Sueño , Humanos , Presión Intraocular , Sueño , Ritmo Circadiano , Glaucoma/complicaciones , Glaucoma/diagnósticoRESUMEN
INTRODUCTION: To compare outcomes of phacoemulsification combined with endoscopic cyclophotocoagulation (phaco/ECP), first generation iStent implantation (phaco/iStent), or both (phaco/iStent/ECP) in patients with open-angle glaucoma. METHODS: A retrospective chart review was performed on patients at the University of Colorado Department of Ophthalmology. Outcomes included intraocular pressure (IOP), medication use, best corrected visual acuity (BCVA), and surgical complications were analyzed. Success was defined as IOP reduction of ≥ 20% and/or reduction by at least one glaucoma medication. RESULTS: A total of 394 eyes were included in the study. There were 170 eyes (43.1%) in the phaco/ECP group, 175 eyes (44.4%) in the phaco/iStent group, and 49 eyes (12.4%) in the phaco/iStent/ECP group. The mean pre-operative IOP was 15.9 mmHg for phaco/ECP, 15.8 mmHg for phaco/iStent, and 15.2 mmHg for phaco/iStent/ECP. At 24 months, the mean IOP was 13.7 mmHg (p < 0.0001), 14.2 mmHg (p = 0.0001), and 13.0 mmHg (p = 0.0007), respectively. The mean pre-operative number of glaucoma medications was 2.0 for phaco/ECP, 1.4 for phaco/iStent, and 2.2 for phaco/iStent/ECP and at 24 months post-surgery decreased to, 1.8 (p = 0.011), 0.9 (p < 0.0001), and 1.7 (p = 0.01), respectively. The success rate at 24 months was 54.4% for phaco/ECP, 75.3% for phaco/iStent, and 55.6% for phaco/iStent/ECP. CONCLUSION: Phacoemulsification when combined with ECP, iStent, or both, lowered IOP and glaucoma medication reliance at 24 months. The success rate for phaco/iStent was significantly higher than phaco/ECP. When iStent was added to phaco/ECP, the success rate was higher at earlier postoperative visits compared to the phaco/ECP alone.
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Glaucoma de Ángulo Abierto , Glaucoma , Facoemulsificación , Humanos , Glaucoma de Ángulo Abierto/complicaciones , Glaucoma de Ángulo Abierto/cirugía , Estudios Retrospectivos , Glaucoma/cirugía , Presión Intraocular , Coagulación con LáserRESUMEN
Climate change has important implications on human health, affecting almost every system in the body. Multiple studies have raised the possibility of climate change impacting eye health. In this review, we aimed to summarize current literature on the impact of air pollution and climate change on eye health. We performed a search in four different databases, including Medline, Scopus, Cochrane, and Web of Sciences databases. The search strategy combined terms regarding eye health and environmental/climate changes. The outcome of interest included all eye conditions. The search yielded 2,051 unique articles. After applying inclusion and exclusion criteria, 61 articles were included in this systematic review with data covering 2,620,030 participants. Most studies originated from China, India, South Korea, and USA. Climate change adversely affected different eye conditions, with ocular surface diseases (e.g., conjunctivitis and dry eye) being most affected. Moreover, higher particulate matter (PM) was the most widely assessed pollutant and was adversely associated with the majority of eye conditions, increasing the burden on patients and healthcare providers. We found a low frequency of publications related to the delivery of eye care and its impact on climate change in countries with high air pollution and climate change burden.
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Purpose: This trial was designed to determine if artificial intelligence (AI)-supported diabetic retinopathy (DR) screening improved referral uptake in Rwanda. Design: The Rwanda Artificial Intelligence for Diabetic Retinopathy Screening (RAIDERS) study was an investigator-masked, parallel-group randomized controlled trial. Participants: Patients ≥ 18 years of age with known diabetes who required referral for DR based on AI interpretation. Methods: The RAIDERS study screened for DR using retinal imaging with AI interpretation implemented at 4 facilities from March 2021 through July 2021. Eligible participants were assigned randomly (1:1) to immediate feedback of AI grading (intervention) or communication of referral advice after human grading was completed 3 to 5 days after the initial screening (control). Main Outcome Measures: Difference between study groups in the rate of presentation for referral services within 30 days of being informed of the need for a referral visit. Results: Of the 823 clinic patients who met inclusion criteria, 275 participants (33.4%) showed positive findings for referable DR based on AI screening and were randomized for inclusion in the trial. Study participants (mean age, 50.7 years; 58.2% women) were randomized to the intervention (n = 136 [49.5%]) or control (n = 139 [50.5%]) groups. No significant intergroup differences were found at baseline, and main outcome data were available for analyses for 100% of participants. Referral adherence was statistically significantly higher in the intervention group (70/136 [51.5%]) versus the control group (55/139 [39.6%]; P = 0.048), a 30.1% increase. Older age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.02-1.05; P < 0.0001), male sex (OR, 2.07; 95% CI, 1.22-3.51; P = 0.007), rural residence (OR, 1.79; 95% CI, 1.07-3.01; P = 0.027), and intervention group (OR, 1.74; 95% CI, 1.05-2.88; P = 0.031) were statistically significantly associated with acceptance of referral in multivariate analyses. Conclusions: Immediate feedback on referral status based on AI-supported screening was associated with statistically significantly higher referral adherence compared with delayed communications of results from human graders. These results provide evidence for an important benefit of AI screening in promoting adherence to prescribed treatment for diabetic eye care in sub-Saharan Africa.
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AIM: To compare intraocular pressure (IOP) readings obtained with Perkins tonometry, iCare Home, iCare 200, and Tonopen to IOP readings obtained with the manometer of a perfusion system to assess the accuracy and reproducibility of each method of tonometry at set pressures. METHODS: The IOP of human cadaveric eyes (n=2) was measured using a manometer inserted into the eye through the optic nerve. IOP measurements were obtained using a Perkins tonometer, iCare Home, iCare 200, and Tonopen. These measurements were compared to set point IOP measurements of a manometer to determine accuracy and reproducibility of each device. RESULTS: Mean IOP readings obtained with the Perkins tonometer compared to manometer readings demonstrated a difference of -1.0±5.0 mm Hg (P=0.45), indicating a lower reading on average than manometery although not significant. Mean IOP difference between iCare 200 and manometer was 5.3±2.2 mm Hg (P<0.0001). Mean difference in IOP between iCare Home and manometer was 3.5±2.4 mm Hg (P=0.0004). Mean IOP difference compared to manometer was 4.6±4.0 mm Hg for the Tonopen (P<0.0001). IOP measurements obtained with the Perkins tonometer demonstrated a standard deviation of 5.0 mm Hg while the Tonopen measurements demonstrated a 4.0 mm Hg standard deviation. In comparison, iCare 200 and iCare Home demonstrated 2.2 and 2.4 mm Hg standard deviation, respectively. CONCLUSION: Applanation tonometry produces more accurate IOP readings than rebound tonometry or Tonopen, however it demonstrates greater variability than the other forms of tonometry. Rebound tonometry is more reproducible but tends to over-estimate IOP.
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AIM: To report the long-term outcomes of combined excisional goniotomy and manual small incision cataract surgery (MSICS). METHODS: This is a retrospective case series of patients with open angle glaucoma and visually significant cataracts that underwent combined excisional goniotomy and MSICS with one-year follow-up. The medical history, demographic information, and clinical characteristics of each case were recorded. Data regarding changes in vision, intraocular pressure (IOP), the number of glaucoma medications, and the evolution of the disease after surgery were reported. RESULTS: Three patients, with open angle glaucoma and cataracts underwent combined excisional goniotomy and MSICS without adverse events. All patients had improvement in vision compared to baseline measurements. The range of IOP at baseline was from 14 to 18 mm Hg and decrease to a range of 10 to 14 mm Hg after one year of follow-up. Additionally, two patients also decreased their dependence on IOP-lowering medications at the last follow up visit with one patient maintaining baseline level of medication use. CONCLUSION: A combination of excisional goniotomy and MSICS illustrates both the safety and efficacy to treat patients with visually significant cataract and glaucoma. This procedure allows for a more cost-effective surgical approach that matches the needs of resource strained territories around the globe.
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PRCIS: Kahook Dual Blade (KDB) goniotomy can successfully lower intraocular pressure in some patients with uveitis-associated ocular hypertension or glaucoma. PURPOSE: The purpose of this study was to report a case series of patients that underwent KDB goniotomy at a single institution for uveitis-associated ocular hypertension or glaucoma with an open angle. METHODS: We performed a retrospective chart review of all patients with uveitis-associated ocular hypertension or glaucoma who underwent KDB goniotomy with trabecular meshwork excision alone or in combination with phacoemulsification cataract surgery at a single center between August 2017 and February 2020. The case series included 45 eyes of 37 patients. All eyes developed ocular hypertension refractory to maximum-tolerated medical therapy and required surgical intervention. Two eyes were excluded as they were lost to follow-up before 5 months postoperatively. Surgical success was defined as reaching the goal intraocular pressure or lower for each patient, including ongoing medical therapy. RESULTS: At most recent follow-up, 25 (55.6%) of 45 eyes had an intraocular pressure that was at goal. Mean follow-up time was 15.2±12.1 months ranging from 0.5 to 36 months postoperatively, considering that patients were eliminated from the data analysis once they required a second surgery. The mean number of preoperative medications, including oral carbonic anhydrase inhibitors was 3.7±1.2 medications. The mean number of postoperative medications through the last clinic visit was 2.5±1.9 medications for a mean reduction of 1.2±1.6 medications ( P -value <0.0001*). CONCLUSIONS: This larger case series shows that some patients with uveitis-associated ocular hypertension or glaucoma with an open angle may have success with KDB goniotomy.
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Glaucoma de Ángulo Abierto , Glaucoma , Hipertensión Ocular , Trabeculectomía , Uveítis , Humanos , Glaucoma de Ángulo Abierto/complicaciones , Glaucoma de Ángulo Abierto/cirugía , Presión Intraocular , Estudios Retrospectivos , Resultado del Tratamiento , Glaucoma/cirugía , Hipertensión Ocular/etiología , Hipertensión Ocular/cirugía , Uveítis/complicaciones , Uveítis/diagnóstico , Uveítis/cirugíaRESUMEN
INTRODUCTION: To investigate the relationship between intraocular pressure (IOP)-lowering success of selective laser trabeculoplasty (SLT) and combined phacoemulsification/Kahook Dual Blade (phaco/KDB) goniotomy in eyes with mild to severe open angle glaucoma (OAG). METHODS: Eyes undergoing combined phaco/KDB goniotomy and that had previously undergone SLT were analyzed. Data collected included demographics, glaucoma type and severity, IOP, and topical IOP-lowering medications before and after both procedures. Eyes were divided into two groups based on success of SLT, defined as IOP reduction of at least 20% maintained on at least two consecutive follow-up visits without any subsequent medication additions or interventions. Phaco/KDB goniotomy success was defined as IOP reduction of at least 20% and/or reduction in the number of IOP-lowering medications of at least one up to 12 months of follow-up. RESULTS: Overall, SLT was successful in 20 of 43 eyes (46.5%), of which 63.6% (7/11) had successful phaco/KDB goniotomy at 12 months follow-up. Among eyes with unsuccessful SLT, 60.0% (9/15) had successful phaco/KDB at 12 months follow-up. Phaco/KDB success rate was similar in patients regardless of their previous response to SLT at all postoperative time points up to 12 months follow-up (p = 0.87). CONCLUSIONS: The presence or lack of IOP-lowering response to SLT did not influence the success rate of subsequent phaco/KDB goniotomy in eyes with mild to severe OAG. Patients who did not respond to SLT still benefited from phaco/KDB goniotomy at a later date.