Eye最新文献

Background/objectives: Qualitative research can be laborious and time consuming, presenting a challenge for practitioners and policymakers seeking rapid, actionable results. Data collection, transcription and analysis are the main contributors to the resource-intensive nature. OpenAI's Chat Generative Pre-trained Transformer (ChatGPT), have demonstrated potential to aid in data analysis. Our study aimed to compare themes generated by ChatGPT (3.5 and 4.0) with traditional human analysis from in-depth interviews.

Methods: Three transcripts from an evaluation study to understand patients' experiences at a community eye clinic were used. Transcripts were first analysed by an independent researcher. Next, specific aims, instructions and de-identified transcripts were uploaded to ChatGPT 3.5 and ChatGPT 4.0. Concordance in the themes was calculated as the number of themes generated by ChatGPT divided by the number of themes generated by the researcher. The number of unrelated subthemes and time taken by both ChatGPT were also described.

Results: The average time taken per transcript was 11.5 min, 11.9 min and 240 min for ChatGPT 3.5, ChatGPT 4.0 and researcher respectively. Six themes were identified by the researcher: (i) clinic's accessibility, (ii) patients' awareness, (iii) trust and satisfaction, (iv) patients' expectations, (v) willingness to return and (vi) explanation of the clinic by referral source. Concordance for ChatGPT 3.5 and 4.0 ranged from 66 to 100%.

Conclusion: Preliminary results showed that ChatGPT significantly reduced analysis time with moderate to good concordance compared with current practice. This highlighted the potential adoption of ChatGPT to facilitate rapid preliminary analysis. However, regrouping of subthemes will still need to be conducted by a researcher.

Importance: Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection is paramount yet challenging, particularly in resource-limited settings. A novel, computer vision-based model for glaucoma screening using fundus images could enhance early and accurate disease detection.

Objective: To develop and validate a generalised deep-learning-based algorithm for screening glaucoma using fundus image.

Design, setting and participants: The glaucomatous fundus data were collected from 20 publicly accessible databases worldwide, resulting in 18,468 images from multiple clinical settings, of which 10,900 were classified as healthy and 7568 as glaucoma. All the data were evaluated and downsized to fit the model's input requirements. The potential model was selected from 20 pre-trained models and trained on the whole dataset except Drishti-GS. The best-performing model was further trained to classify healthy and glaucomatous fundus images using Fastai and PyTorch libraries.

Main outcomes and measures: The model's performance was compared against the actual class using the area under the receiver operating characteristic (AUROC), sensitivity, specificity, accuracy, precision and the F1-score.

Results: The high discriminative ability of the best-performing model was evaluated on a dataset comprising 1364 glaucomatous discs and 2047 healthy discs. The model reflected robust performance metrics, with an AUROC of 0.9920 (95% CI: 0.9920-0.9921) for both the glaucoma and healthy classes. The sensitivity, specificity, accuracy, precision, recall and F1-scores were consistently higher than 0.9530 for both classes. The model performed well on an external validation set of the Drishti-GS dataset, with an AUROC of 0.8751 and an accuracy of 0.8713.

Conclusions and relevance: This study demonstrated the high efficacy of our classification model in distinguishing between glaucomatous and healthy discs. However, the model's accuracy slightly dropped when evaluated on unseen data, indicating potential inconsistencies among the datasets-the model needs to be refined and validated on larger, more diverse datasets to ensure reliability and generalisability. Despite this, our model can be utilised for screening glaucoma at the population level.

Care pathways for the management of acute ophthalmic conditions have developed and transformed significantly over recent years, owing to a combination of legislative changes, policy implementation and the pressing requirement to redistribute increased demand away from traditional secondary care providers through collaboration with primary care. Following UK healthcare devolution in 1999, each nation has developed and implemented their own strategies for managing the growing demands on acute ophthalmology services. Local commissioning across England has seen Enhanced Service Pathways develop to provide acute eye care by primary care optometrists, with provision and access dependent upon locality. Northern Ireland has seen the implementation of a nationwide Primary Eyecare Acute Referral Service, whilst in Scotland and Wales, the respective Governments have redesigned primary care optometry General Ophthalmic Service contracts to incorporate provision of extended investigations and management of acute conditions by optometrists across the nation, recognising the added benefit of optometrists with higher qualifications. This narrative review summarises both peer reviewed and appropriate grey literature articles reporting on acute eye care pathways in primary care. Despite significant progress, particularly during the global COVID-19 pandemic, there is arguably still a great deal of further research and evaluation required relating to pathway innovation, the role of professionals with higher qualifications, including independent prescribing, the role of telemedicine, reassurance around clinical safety, and how digital interconnectivity could potentially add value to collaborative schemes to meet the growing demand on acute eyecare.

The pathophysiology of optic disc drusen (ODD) has long been discussed. According to one leading theory, they develop from calcified mitochondria extruded from axons compressed by an unusually small scleral canal. To examine this hypothesis, we conducted a systematic review and meta-analysis evaluating the scleral canal size in patients with ODD (PO) in comparison to healthy subjects (HS). We searched MEDLINE, Cochrane Central, EMBASE and gray literature to identify relevant articles. A subgroup analysis compared patients with buried ODD (PO_b) and patients with visible ODD (PO_v). The study was registered with the International Prospective Register of Systematic Reviews on December 9th, 2022 (Registration: CRD42022375110). We included fifteen articles in the review and fourteen in the meta-analysis. The mean diameter of the scleral canal computed using both fundus photography (D_F) and spectral-domain with enhanced depth imaging optical coherence tomography (D_O-EDI) was significantly smaller in PO compared to HS (standardized mean difference -1.21 [-1.85 to -0.56] and -0.66 [-0.94 to -0.37] respectively). D_O-EDI, but not D_F, was higher in PO_v as compared to PO_b. When including all-generation OCT in the analysis, the difference between PO_v and PO_b, but not between PO and HS, remained. Several intertwined hypotheses can explain these subgroup and sensitivity results: an enlargement of the canal as the ODD grow, an enlargement with time, or a measurement bias (artefactual enlargement of the canal due to a posterior shadow on OCT). In conclusion, this review and meta-analysis further supports the role of a small scleral canal in the development of ODD.

Background: The vitreous evolves from birth over lifetime. Little is known about the appearance of the healthy vitreous during childhood. We aimed to characterise posterior vitreous features in healthy children using spectral domain optical coherence tomography (SD-OCT).

Methods: Retrospective cohort study including healthy eyes of 78 children aged 2-12 years and 39 healthy adults. Patients diagnosed with intraocular inflammation or vitreoretinal pathology were excluded.

Main outcome: Proportion of eyes with presence of punctate hyperreflective vitreous opacities (PHVO). Percentage of B-scans demonstrating PHVO within an OCT volume scan, correlation between presence of PHVO and patients' age group, retinal measurements, and presence of premacular bursa were analysed.

Results: 154 paediatric eyes (median age 9.08 (IQR 5.17-9.75) years) and 76 adult eyes (30.75 (IQR 26.42-38.08) years) were included; 12244 OCT images were reviewed. All eyes (100%) in the paediatric group and 73% in the adult group presented PHVO. The median percentage of OCT images showing PHVO was 77.05% (IQR 51.23-88.52) in children and 8.0% (IQR 0-16.03) in adults (p < 0.001). Separate analysis of right and left eyes confirmed the results (p < 0001). Premacular bursa appeared in 20.5% of paediatric and 31.6% of adult eyes (p = 0.103). Mean central subfield thickness was significantly lower in children (257 ± 21 µm vs. 276 ± 18 µm, p < 0.001), while median total macular volume was similar (8.59 (IQR 8.25-8.86) mm³ vs. 8.62 (IQR 8.39-8.96) mm³, p = 0.145).

Conclusions: This study demonstrates that PHVO are ubiquitous physiologic vitreous findings in healthy children beyond infancy. These findings enhance the understanding of the development of the posterior segment of the eye and might improve paediatric OCT interpretation, potentially avoiding misdiagnoses and unnecessary interventions in children.