The remarkable recent advances in managing keratoconus, the most common corneal ectasia, encouraged researchers to conduct further studies on the disease. Despite the abundance of information about keratoconus, debates persist regarding the detection of mild cases. Early detection plays a crucial role in facilitating less invasive treatments. This review encompasses corneal data ranging from the basic sciences to the application of artificial intelligence in keratoconus patients. Diagnostic systems utilize automated decision trees, support vector machines, and various types of neural networks, incorporating input from various corneal imaging equipment. Although the integration of artificial intelligence techniques into corneal imaging devices may take time, their popularity in clinical practice is increasing. Most of the studies reviewed herein demonstrate a high discriminatory power between normal and keratoconus cases, with a relatively lower discriminatory power for subclinical keratoconus.

Objective: There are inconsistent findings on the association between obesity and age-related cataract (ARC). This systematic review was done to summarize available findings on the association between obesity [defined by body mass index (BMI)] and ARC by performing a dose–response meta-analysis on eligible prospective cohort studies.Methods: We performed a systematic search in PubMed, Scopus, ISI Web of Knowledge, and Google Scholar until June 2022 to identify eligible publications.Results: In total, 16 studies with a total sample size of 1,607,125 participants were included. Among all of these studies, there were 103,897 cases of ARC. In the follow-up periods ranging between 4 and 28 years, 4,870 cases of nuclear cataract, 1,611 cases of cortical cataract, and 1,603 cases of posterior subcapsular cataracts (PSC) were detected. By comparing the highest and lowest categories of BMI, we found that higher BMI was associated with an increased risk of ARC (RR: 1.18, 95% CI: 1.09–1.28) and PSC (RR: 1.44, 95% CI: 1.08–1.90). In the dose–response analysis, each 5 kg/m² increase in BMI was associated with a 6 and 27% increased risk of ARC (RR: 1.06, 95% CI: 1.01–1.12) and PSC (RR: 1.27, 95% CI: 1.14–1.41), respectively. In addition, we found a positive association for cortical cataract among high-quality studies, in which higher BMI was associated with a 20% increased risk of cortical cataract (RR: 1.20, 95% CI: 1.02–1.42). In terms of nuclear cataract, we found no significant association either in the comparison between the highest and lowest categories of BMI or in the dose–response meta-analysis.Conclusion: Obesity (defined by BMI) was associated with an increased risk of ARC, PSC, and cortical cataract in adults. However, such a positive association was not seen for nuclear cataract.PROSPERO registration: CRD42022357132.

Background: New developments in artificial intelligence, particularly with promising results in early detection and management of keratoconus, have favorably altered the natural history of the disease over the last few decades. Features of artificial intelligence in different machine such as anterior segment optical coherence tomography, and femtosecond laser technique have improved safety, precision, effectiveness, and predictability of treatment modalities of keratoconus (from contact lenses to keratoplasty techniques). These options ingrained in artificial intelligence are already underway and allow ophthalmologist to approach disease in the most non-invasive way.Objectives: This study comprehensively describes all of the treatment modalities of keratoconus considering machine learning strategies.Design: A multidimensional comprehensive systematic narrative review.Data sources and methods: A comprehensive search was done in the five main electronic databases (PubMed, Scopus, Web of Science, Embase, and Cochrane), without language and time or type of study restrictions. Afterward, eligible articles were selected by screening the titles and abstracts based on main mesh keywords. For potentially eligible articles, the full text was also reviewed.Results: Artificial intelligence demonstrates promise in keratoconus diagnosis and clinical management, spanning early detection (especially in subclinical cases), preoperative screening, postoperative ectasia prediction after keratorefractive surgery, and guiding surgical decisions. The majority of studies employed a solitary machine learning algorithm, whereas minor studies assessed multiple algorithms that evaluated the association of various keratoconus staging and management strategies. Last but not least, AI has proven effective in guiding the implantation of intracorneal ring segments in keratoconus corneas and predicting surgical outcomes.Conclusion: The efficient and widespread clinical translation of machine learning models in keratoconus management is a crucial goal of potential future approaches to better visual performance in keratoconus patients.Trial registration: The article has been registered through PROSPERO, an international database of prospectively registered systematic reviews, with the ID: CRD42022319338

: Age-related changes in the lower eyelid are noticed by patients as bags or circles under the eye, a tired look, and a flattened face. Lower eyelid blepharoplasty, in which the excess skin and/or orbital fat is excised and repositioned, is mainly performed for aesthetic reasons rather than the correction of functional abnormalities. Favorable outcomes for the combination of these approaches have been reported, but the most suitable surgical technique is still debated. This systematic narrative review deals with the indications, preoperative considerations, operative techniques, and complications of several different surgical approaches to lower eyelid blepharoplasty. Level of Evidence: 3:

To evaluate the clinical results of toric trifocal diffractive intraocular lens in eyes with cataract and mild keratoconus. Five keratoconus patients (10 eyes) that had bilateral AT LISA 939 implantation were selected and had followed in 3-time horizons of 1, 3, and 6 months. Patients were 46 to 65 years old age, corneal astigmatism of (2.00 D at 6.75 D) and cataract that all of them needed cataract surgery. The distance, intermediate and near visual acuities, defocus curve, ocular aberrations, contrast sensitivity, were measured as effectiveness criteria. Average of binocular uncorrected distance visual acuity (UDVA) improved from 0.72 log MAR ± 0.11 (SD) to 0.04 ± 0.04 (P < 0.05) log MAR, average of uncorrected binocular intermediate visual acuity (UIVA) (80 cm) improved from 0.52 ± 0.07 log MAR to 0.14 ± 0.04 (P < 0.05) log MAR, and average of binocular uncorrected near visual acuity (UNVA) improved from 0.48 ± 0.09 log MAR to 0.02 ± 0.07 (P < 0.05) log MAR at 6 months, respectively. Contrast sensitivity testing showed acceptable results, the binocular defocus curve corroborate were in appropriate good visual acuity even at the intermediate distances, by a gentle slope less than log MAR 0.2 at −1.5 D, with regard to the best distance visual acuity at the 0 D defocus. Trifocal AT LISA 939MP IOLs provided appropriate distances, near and intermediate of the visual results. Prediction of the refractive results and optical performances were good.