Introduction: Cataract is a prevalent eye condition that affects millions of individuals worldwide, leading to visual impairment and reduced quality of life. Cataract surgery is the most effective treatment, but post-surgical complications can arise, impacting the success of the intervention. Optical coherence tomography (OCT) has emerged as a valuable imaging technique for evaluating these complications, but the manual interpretation of OCT images is time-consuming and subjective.Objective: In this study, we aimed to assess the performance of a machine learning (ML) tool specifically developed for detecting post-surgical complications in cataract patients.Methods: We employed a support vector machine (SVM) algorithm to analyze a comprehensive dataset of OCT images. The dataset comprised 700 OCT images obtained post-surgery, including patients with cystoid macular oedema (CMO), retinal detachment (RD), and healthy individuals. The ML tool utilized pre-processed OCT images with annotations provided by expert ophthalmologists, undergoing retinal layer segmentation using intensity-based features.Results: The SVM algorithm demonstrated high sensitivity and specificity in detecting and classifying post-surgical complications. It achieved a sensitivity of 92.5% in detecting CMO and 90.9% in identifying RD. The specificity of the algorithm was 90.9% and 96.2% for these complications, respectively. The overall accuracy of the ML tool in correctly identifying and classifying post-surgical complications was 92%.Conclusions: The integration of ML algorithms in OCT imaging shows promise in enhancing the accuracy and efficiency of assessing post-surgical complications in cataract patients. The ML tool developed in this study provides reliable and objective assessments, reducing the subjectivity and variability associated with the manual interpretation of OCT images

Integrating optical coherence tomography (OCT) into the pre-surgical stage of cataract management holds significant clinical and economic potential, particularly in low-to-middle-income countries like Kazakhstan. This study aimed to evaluate these impacts by prospectively recruiting 124 patients, aged 70±8 years, from two ophthalmology surgical centers in Almaty, Kazakhstan. Patients undergoing phacoemulsification of cataracts with monofocal intraocular lens (IOL) implantation between January and December 2022 were divided into two groups: the OCT group (n=75) received pre-operative OCT, while the Control group (n=49) did not. Visual acuity (VA) was measured pre- and post-surgery, and the cost-effectiveness of the surgical strategies was analyzed. The OCT group experienced a significantly greater improvement in VA (-0.647±0.232 logMAR) compared to the Control group (-0.543±0.244 logMAR), with a notable interaction between time and group (F(df) = 217.2, p < 0.001). Additionally, pre-existing concomitant diseases were diagnosed in 25.3% of cases in the OCT group and 28.6% in the Control group. The economic analysis revealed that the integration of OCT facilitated multiple surgeries in one appointment, thereby reducing overall costs. These findings suggest that implementing OCT in the pre-surgical stage of cataract management can significantly enhance visual outcomes and decrease the cost of ophthalmology services in Kazakhstan.

Целью данной статьи является обзор литературы по оптимизации администрирования диагностики, лечения и профилактики пациентов с катарактой. Для подробного и полноценного обзора с разнообразными типами исследований и их методологиями была использована технология эволюционирующих стандартов синтеза реалистических и метанарративных доказательств, или иначе RAMSES. Были проанализированы более 2 000 публикации, из которых 52 манускриптов были добавлены для окончательного анализа в данной работе. Из-за растущей популяцией больных с катарактой в мире, растет и количественный, и качественный состав публикации по оптимизации организации оказания офтальмологической помощи пациентам с помутнением хрусталика. Практическое применение современных и эффективных методов оптимизации способствует усовершенствованию всех этапов медицинской помощи больным с катарактой. Бұл мақаланың мақсаты катаракта бар науқастарды диагностикалауды, емдеуді және алдын-алуды оңтайландыру мәселелері бойынша рецензияланған мәліметтер базасынан әдебиеттерді шолу болып табылады. Зерттеудің бірнеше түрлерімен және олардың әдіснамасымен толығырақ шолу мақсатында RAMSES, немесе нақты және метанаративті дәлелдерді синтездеу технологиясы қолданылды. 2000-нан астам мақалалар талданылып, олардың 52 қолжазбасы осы жұмыста түпкілікті талдау үшін қосылды. Әлемде катаракта бар науқастардың санының өсуіне байланысты линзаның бұлдырауы бар науқастарға офтальмологиялық көмек көрсетуді ұйымдастыруды оңтайландыру туралы жарияланымның сандық және сапалық құрамы өсуде. Оңтайландырудың заманауи және тиімді әдістерін практикалық қолдану катаракта бар науқастарға медициналық көмектің барлық кезеңдерін жетілдіруге көмектеседі. The purpose of this paper is to review the literature from peer-reviewed databases on optimizing the administration of diagnosis, treatment and prevention of patients with cataracts. For a detailed and complete review with a variety of types of studies and their methodologies, the technology of Realist And MEta-narrative Evidence Syntheses: Evolving Standards (RAMSES) was used. More than 2,000 publications were analyzed, of which 52 manuscripts were added for final analysis in this work. Due to the growing population of patients with cataracts in the world, both the quantitative and qualitative composition of the publication on optimizing the organization of the provision of ophthalmic care to patients with lens opacity is growing. The practical application of modern and effective optimization methods contributes to the improvement of all stages of medical care for patients with cataracts.

This retrospective study evaluates the efficacy of peritoneal dialysis (PD) in mitigating acute kidney injury (AKI) associated with cardiac surgery in newborns. We analyzed data from 120 neonates up to 28 days old who developed AKI post-cardiac surgery and required PD. Statistical analysis was performed using SPSS 26. Results indicated that PD patients were predominantly male (p = 0,007) with an average age of 12,87 days versus 9,32 days (p = 0,015), and an average weight of 3,06 kg compared to 2,76 kg (p = 0,040). Multivariate regression highlighted age (OR = 1,083, p = 0,032), cardiopulmonary bypass duration (OR = 1,081, p = 0,030), and RACHS-1 scores (OR = 4,785, p = 0,037) as significant predictors of PD initiation. Among PD patients, non-survivors had an average age of 10,31 days versus 18,00 days for survivors (p = 0,045), and an average weight of 2,94 kg versus 3,54 kg (p = 0,040). Non-survivors also had shorter cardiopulmonary bypass times (33,63 minutes versus 50,60 minutes, p = 0,036) and aortic cross-clamp times (22,77 minutes versus 26,50 minutes, p = 0,015). Multivariate analysis also showed that younger age (OR = 0,927, p = 0,009), lower weight (OR = 0,597, p = 0,006), higher RACHS-1 scores (OR = 0,432, p = 0,002), longer bypass (OR = 0,969, p = 0,001), and longer cross-clamp times (OR = 0,871, p = 0,007) predicted decreased survival. PD benefits include reduced AKI severity and enhanced survival, particularly in complex cases, despite an increased sepsis risk