Construction of databases:advances and significance in clinical research

Widely used in clinical research, the database is a new type of data management automation technology and the most efficient tool for data management. In this article, we first explain some basic concepts, such as the definition, classification, and establishment of databases. Afterward, the workflow for establishing databases, inputting data, verifying data, and managing databases is presented. Meanwhile, by discussing the application of databases in clinical research, we illuminate the important role of databases in clinical research practice. Lastly, we introduce the reanalysis of randomized controlled trials(RCTs) and cloud computing techniques, showing the most recent advancements of databases in clinical research.

预测儿童Ⅱ期人工晶状体植入术后青光眼相关不良事件的风险:一项为期3年的研究

目的:建立并评估儿童Ⅱ期人工晶状体(intraocular lens,IOL)植入术后青光眼相关不良事件(glaucomarelated adverse events,GRAEs)的预测模型。方法:选取于中山大学中山眼科中心行Ⅱ期IOL植入术的无晶状体眼患儿205例(356眼),并在术后对其随访3年。采用Cox比例风险模型确定GRAEs的预测因子,并建立列线图预测模型。采用随时间变化的受试者工作特征(receiver operating characteristic,ROC)曲线、决策曲线分析、Kaplan-Meier曲线评估模型性能,并通过Bootstrapping的C指数和校准图进行内部验证。结果:行Ⅱ期IOL植入术时年龄较大(HR=1.50,95%CI:1.03~2.19)、术后一过性高眼压(HR=9.06,95%CI:2.97~27.67)和IOL睫状沟植入术(HR=14.55,95%CI:2.11~100.57)是GRAEs的危险因素(均P<0.05),并据此建立了两个列线图预测模型。在术后1、2、3年,模型1的ROC曲线下面积(area under curve,AUC)分别为0.747(95%CI:0.776~0.935)、0.765(95%CI:0.804~0.936)和0.748(95%CI:0.736~0.918),模型2的AUC分别为0.881(95%CI:0.836~0.926)、0.895(95%CI:0.852~0.938)和0.848(95%CI:0.752~0.945)。在内部验证和评价中,两种模型均表现出良好的性能和临床净效益。Kaplan-Meier曲线显示两个不同的风险组在两个模型中都能被显著且稳健地区分。此外,本研究也构建了在线风险计算器。结论:两种列线图均能灵敏、准确地识别Ⅱ期IOL植入术后GRAEs的高危患儿,有助对其进行早期识别和及时干预。

Significance of Axial Length Monitoring in Children with Congenital Cataract and Update of Measurement Methods

Congenital cataract is the main cause of blindness in children, with significantly varying treatment effects. The development of axial length is an important factor that affects the prognosis of these children.However,when compared with the eyes of normal children,the mechanism of growth of the axial length is so complicated that the reported findings differ significantly in terms of the measuring apparatus,assessment methods,and statistical outcome,making the rule of axial length development still unclear. In this paper, we first review the process of axial length development in normal healthy children and compare different hypotheses about certain factors that could affect the development of axial length. The results of some current research about the characteristics of axial length development in congenital cataract children are then reviewed. Lastly, the advantages and disadvantages of current axial length measurements methods are compared and analyzed.The purpose of this review is to improve our understanding of the complexity and importance of axial length development and to suggest better use of axial length monitoring measurements in congenital cataract children for pediatric ophthalmologists,with the hope of offering assistance that will enhance long-term therapeutic effects for these children.

Progress of Application of Sedation Technique in Pediatric Ocular Examination

Pediatric ophthalmic test requires meticulous observation and precise measurement..However, children are unable to actively cooperate with the test...If they were forced to receive the examinations,.it is difficult to deliver accurate diagnosis and treatment, and cause negative influence upon physical and mental health. Consequently, sedation technique plays an extremely vital role in pediatric eye examinations..This study was designed to summarize the application of chloral hydrate in pediatric eye examination and propose different methods of medicine administration for children of varying ages, aiming to improve the effect of sedation. In addition, the feasibility of use of dexmedetomidine,.which had been proven to be effective in pediatric sedation examination,.into pediatric ophthalmic sedation examination was evaluated,.thereby offering more options for the development of pediatric ocular sedation test.

Progress in Screening and Treatment of Common Congenital Eye Diseases

Congenital eye illnesses are caused by congenital ocular malformations and are a primary cause of poor visual acuity and blindness in infants. Early diagnosis and treatment of congenital eye illnesses are of great significance for affected infants, their families, and even society as a whole. This study describes the current situation for prenatal and infant screening for congenital eye diseases and briefly summarizes novel progress in the treatment of the five most common eye diseases(congenital dacryocystitis, congenital cataract, retinopathy of prematurity, congenital glaucoma and retinoblastoma).Current programs are now aimed at improvements in the prevention and treatment of congenital eye diseases in China.

Pattern of Refractive Correction and Timing of Stage Ⅱ IOL Implantation after Congenital Cataract Extraction

Congenital cataract occurs during infancy when the axial length and corneal and visual function are in the sensitive stages of rapid development..Inappropriate surgical intervention not only fails to restore visual function,.but also causes irreversible serious influences upon eyeball development in children diagnosed with congenital cataract. At present, the uncertainty of selection of intraocular lens(IOL) degrees during the eyeball development period is averted by using a main treatment of congenital cataract that includes two-stage surgery:.stage I cataract extraction and stage II IOL implantation. However, the accurate selection of a refractive correction method and the timing of IOL implantation during stage II surgery for aphakic eyes remains controversial following stage I cataract extraction..This review retrospectively summarizes the current progress and existing problems indicated by related recent studies focusing on refractive correction pattern and IOL implantation timing.

Exploration of Management Workflow of Cataract Surgery in an Impoverished Population in Urban China

Purpose:.To explore and establish a rational management workflow for a free cataract surgery program for the poor population in urban China, aiming to improve surgical efficiency.Methods:.Establishment of a management workflow mainly includes system design and an auxiliary facility. System design procedures consist of outpatient screening, outpatient physical examination,.surgical procedures,.and postoperative clinic visits. After establishing the management workflow of cataract surgery, a free cataract surgery program was conducted for 15 months.Results: Based upon the established management mode, 9003 patients received preoperative screening and 2358 underwent cataract surgery..During the 15-month investigation,.each procedure was successfully conducted,.the efficiency of screening and operation attained the highest standards in China,.and no surgical malpractice occurred intraoperatively.Conclusion:.In this study,.a management workflow for cataract surgery was designed for a poverty relief project in urban China. During the 15-month project, the degree of patient satisfaction was enhanced without disrupting the normal practice and safety of the sponsor hospital.

Application of visual electrophysiology for the diagnosis and treatment of cataracts

Visual electrophysiology is widely used in clinical ophthalmology. It is also of significant value in the objective assessment of visual function in adult and pediatric cataract patients and for the diagnosis of and research on retinal and visual pathway diseases. This article systematically reviews visual electrophysiology techniques, their applications in the diagnosis and treatment of adult and pediatric cataracts, and factors influencing the application of visual electrophysiology during surgical treatment for cataracts.

Handwashing quality assessment via deep learning:a modelling study for monitoring compliance and standards in hospitals and communities

Background Hand hygiene can be a simple,inexpensive,and effective method for preventing the spread of infectious diseases.However,a reliable and consistent method for monitoring adherence to the guidelines within and outside healthcare settings is challenging.The aim of this study was to provide an approach for monitoring handwashing compliance and quality in hospitals and communities.Methods We proposed a deep learning algorithm comprising three-dimensional convolutional neural networks(3D CNNs)and used 230 standard handwashing videos recorded by healthcare professionals in the hospital or at home for training and internal validation.An assessment scheme with a probability smoothing method was also proposed to optimize the neural network’s output to identify the handwashing steps,measure the exact duration,and grade the standard level of recognized steps.Twenty-two videos by healthcare professionals in another hospital and 28 videos recorded by civilians in the community were used for external validation.Results Using a deep learning algorithm and an assessment scheme,combined with a probability smoothing method,each handwashing step was recognized(ACC ranged from 90.64%to 98.87%in the hospital and from 87.39%to 96.71%in the community).An assessment scheme measured each step’s exact duration,and the intraclass correlation coefficients were 0.98(95%CI:0.97-0.98)and 0.91(95%CI:0.88-0.93)for the total video duration in the hospital and community,respectively.Furthermore,the system assessed the quality of handwashing,similar to the expert panel(kappa=0.79 in the hospital;kappa=0.65 in the community).Conclusions This work developed an algorithm to directly assess handwashing compliance and quality from videos,which is promising for application in healthcare settings and communities to reduce pathogen transmis-sion.

Application of artifcial intelligence in cataract management:current and future directions

The rise of artifcial intelligence(AI)has brought breakthroughs in many areas of medicine.In ophthalmology,AI has delivered robust results in the screening and detection of diabetic retinopathy,age-related macular degeneration,glaucoma,and retinopathy of prematurity.Cataract management is another feld that can beneft from greater AI application.Cataract is the leading cause of reversible visual impairment with a rising global clinical burden.Improved diagnosis,monitoring,and surgical management are necessary to address this challenge.In addition,patients in large developing countries often sufer from limited access to tertiary care,a problem further exacerbated by the ongoing COVID-19 pandemic.AI on the other hand,can help transform cataract management by improving automation,efcacy and overcoming geographical barriers.First,AI can be applied as a telediagnostic platform to screen and diagnose patients with cataract using slit-lamp and fundus photographs.This utilizes a deep-learning,convolutional neural network(CNN)to detect and classify referable cataracts appropriately.Second,some of the latest intraocular lens formulas have used AI to enhance prediction accuracy,achieving superior postoperative refractive results compared to traditional formulas.Third,AI can be used to augment cataract surgical skill training by identifying diferent phases of cataract surgery on video and to optimize operating theater workfows by accurately predicting the duration of surgical procedures.Fourth,some AI CNN models are able to efectively predict the progression of posterior capsule opacifcation and eventual need for YAG laser capsulotomy.These advances in AI could transform cataract management and enable delivery of efcient ophthalmic services.The key challenges include ethical management of data,ensuring data security and privacy,demonstrating clinically acceptable performance,improving the generalizability of AI models across heterogeneous populations,and improving the trust of end-users.

Machine learning methods for biological age estimation

Age stands as a primary risk factor for diseases and disabilities among the elderly.To effectively assess the underlying aging processes,accurate measures of biological age and rates of aging across multiple levels of aging features are essential.Biological age derives from physiological assessments of systems and organs.It has emerged as a superior predictor of age-related diseases and mortality compared to chronological age.Recent advancements in machine learning have catalyzed the development of sophisticated models capable of quantitatively characterizing biological aging with different types of data.This review explores the machine learning models in advancing our understanding of biological aging,highlighting the potential of these innovative approaches to facilitate aging research and personalized healthcare strategies.

Genus Tetrastigma:A review of its folk uses,phytochemistry and pharmacology

The genus Tetrastigma belongs to the Vitaceae family and contains over 100 species.This paper reviewed folk uses,chemical constituents,pharmacological activities,and clinical applications of the medicinal plants in the genus Tetrastigma.In addition,the paper also discussed the current problems for the further studies.Up to now,more than 240 compounds were reported from the genus Tetrastigma,covering 74 flavonoids,14 terpenoids,19 steroids,21 phenylpropanoids,14 alkaloids and others constituents.Among them,flavonoids are the major and the characteristic chemical constituents in this genus.Modern pharmacological studies and clinical practice showed that the extracts and chemical constituents of Tetrastigma species possessed wide pharmacological activities including antitumor,antioxidative,hepatoprotective,antiviral,anti-inflammatory,and analgesic activities.The information summarized in this paper provides valuable clues for new drug discovery and an incentive to expand the research of genus Tetrastigma.

The national multi-center artificial intelligent myopia prevention and control project

In recent years,the incidence of myopia has increased at an alarming rate among children and adolescents in China.The exploration of an effective prevention and control method for myopia is in urgent need.With the development of information technology in the past decade,artificial intelligence with the Internet of Things technology(AIoT)is characterized by strong computing power,advanced algorithm,continuous monitoring,and accurate prediction of long-term progression.Therefore,big data and artificial intelligence technology have the potential to be applied to data mining of myopia etiology and prediction of myopia occurrence and development.More recently,there has been a growing recognition that myopia study involving AIoT needs to undergo a rigorous evaluation to demonstrate robust results.

The critical need to establish standards for data quality in intelligent medicine

Medical artificial intelligence(AI)is an important technical asset to support medical supply-side reforms and national development in the big data era.Clinical data from multiple disciplines represent building blocks for the development and application of AI-aided diagnostic and treatment systems based on medical big data.However,the inconsistent quality of these data resources in AI research leads to waste and inefficiencies.Therefore,it is crucial that the field formulatesthe requirements and content related to data processing as part of the development of intelligent medicine.To promote medical AI research worldwide,the“Belt and Road”International Ophthalmic Artificial Intelligence Research and Development Alliance will establish a series of expert recommendations for data quality in intelligent medicine.

Expert recommendation on collection,storage,annotation,and management of data related to medical artificial intelligence

Medical artificial intelligence(AI)and big data technology have rapidly advanced in recent years,and they are now routinely used for image-based diagnosis.China has a massive amount of medical data.However,a uniform criteria for medical data quality have yet to be established.Therefore,this review aimed to develop a standardized and detailed set of quality criteria for medical data collection,storage,annotation,and management related to medical AI.This would greatly improve the process of medical data resource sharing and the use of AI in clinical medicine.

Recommendation on data collection and annotation of ocular appearance images in ptosis

Ptosis is a common ophthalmologic condition,and the diagnosis is primarily based on ocular appearance.Thediagnosis of such conditions can be improved using emerging technology such as artificial intelligence-basedmethods.However,unified data collection and labeling standards have not yet been established.This directlyimpacts the accuracy of ptosis diagnosis based on appearance alone.Therefore,in the present study,we aimedto establish a procedure to obtain and label images to devise a recommendation system for optimal recognitionof ptosis based on ocular appearances.This would help to standardize and facilitate data sharing and serve as aguideline for the development and improvisation of algorithms in artificial intelligence for ptosis.

Expert recommendations on collection and annotation of otoscopy images for intelligent medicine

Middle and outer ear diseases are common otological diseases worldwide.Otoscopy and otoendoscopy exami-nations are essential first steps in the evaluation of patients with otological diseases.Misdiagnosis often occurs when the doctor lacks experience in interpreting the results of otoscopy or otoendoscopy,leading to delays in treatment or complications.Using deep learning to process otoscopy images and developing otoscopic artificial-intelligence-based decision-making systems will become a significant trend in the future.However,the uneven quality of otoscopy images is among the major obstacles to development of such artificial intelligence systems,and no standardized process for data acquisition,and annotation of otoscopy images in intelligent medicine has yet been fully established.The standards for data storage and data management are unified with those of other specialties and are introduced in detail here.This expert recommendation criterion improved and standardized the collection and annotation procedures for otoscopy images and fills the current gap in otologic intelligent medicine;it would thus lay a solid foundation for the standardized collection,storage,and annotation of oto-scopy images and the application of training algorithms,and promote the development of automatic diagnosis and treatment for otological diseases.The full text introduced image collection(including patient preparation,equipment standards,and image storage),image annotation standards,and quality control.

Expert recommendations on data collection and annotation of two dimensional ultrasound images in azoospermic males for evaluation of testicular spermatogenic function in intelligent medicine

Testicular two-dimensional ultrasound is a testing modality that is often used to evaluate azoospermia and other related diseases.With the continuous development of deep learning in recent years,the combination of deep learning and testicular ultrasound appears unstoppable despite a lack of relevant standards.One of the major problems associated with the digitization of ultrasound images is the uneven quality of data however,and a standardized data source and acquisition process has not yet been developed.Such a standard could fill the current gap,and establish acquisition criteria for ultrasound images of testes during the male reproductive period,including grayscale ultrasound,shear wave elastography,and contrast-enhanced ultrasound.By following these guidelines the quality of testicular ultrasound images would be improved and standardized,which would lay a solid foundation for the standardization of testicular ultrasound images,and assist automated evaluation of testicular spermatogenic function of whole testis in azoospermic males.

Inheritance and innovation

In 2024,we celebrate the 125th anniversary of the birth of Professor Eugene Chan,one of the founders of Chinese modern ophthalmology.As a pioneer ophthalmic endeavors in China,he dedicated his entire life to the research,education,and clinical practice of ophthalmology,laying a solid foundation for its global development.His outstanding contributions and profound influence continue to inspire countless ophthalmic professionals.Zhongshan Ophthalmic Center founded by Professors Eugene Chan and Winifred Mao in 1983,organized the First International Ophthalmological Conference in China(IOCC)and published the selected distinguished speeches in the inaugurated issue of Eye Science in 1985.To honor this milestone,Zhongshan Ophthalmic Center invited ophthalmic experts worldwide to contribute their latest work in Eye Science in 2024,as a testament to our utmost deepest respect for this medical giant.

Retinal neurovascular characteristics for the diagnosis and staging of nondiabetic chronic kidney disease:a diagnostic study

Aims:To identify the characteristic retinal neurovascular changes in patients in different stages of nondiabetic chronic kidney disease(CKD)and to develop a model for the accurate diagnosis of nondiabetic CKD.Methods:Peripapillary retinal nerve fiber layer(pRNFL)thickness and average macular ganglion cell-inner plexiform layer(GC-IPL)thickness of nondiabetic CKD patients and healthy controls(HC)were evaluated by spectral-domain optical coherence tomography(OCT).The vessel density(VD)and perfusion density(PD)of the macula were obtained from optical coherence tomography angiography(OCTA).The estimated glomerular filtration rate(eGFR)was obtained to access the kidney function of CKD patients.Multiple linear regression models were used to adjust for confounding factors in statistical analyzes.The diagnostic capabilities of the parameters were evaluated by logistic regression models.Results:131 nondiabetic CKD patients and 62 HC entered the study.eGFR was found significantly associated with parafoveal VD and PD(average PD:β=0.0004,P_(adjusted)<0.001)in various sectors.Thinning of pRNFL(β=−6.725,P_(adjusted)<0.001)and GC-IPL(β=−4.542,P_(adjusted)<0.001),as well as decreased VD(β=−2.107,P_(adjusted)<0.001)and PD(β=−0.057,P_(adjusted)=0.0328)were found in CKD patients.Thinning of pRNFL and deteriorated perifoveal vasculature were found in early CKD,and the parafoveal and foveal VD significantly declined in advanced CKD.Logistic regression models were employed,and selected neurovascular parameters showed an AUC of 0.853(95%CI:0.795 to 0.910)in distinguishing CKD patients from HC.Conclusions:Distinctive retinal neurovascular characteristics could be observed in nondiabetic CKD patients of different severities.Our results suggest that retinal manifestations could be valuable in the screening,diagnosis,and follow-up evaluation of patients with CKD.