Displaying publications 1 - 20 of 23 in total

Abstract:
Sort:
  1. Localization of optic disc and fovea in retinal images using intensity based line scanning analysis
    Kamble R, Kokare M, Deshmukh G, Hussin FA, Mériaudeau F
    Comput Biol Med, 2017 08 01;87:382-396.
    PMID: 28595892 DOI: 10.1016/j.compbiomed.2017.04.016
    Accurate detection of diabetic retinopathy (DR) mainly depends on identification of retinal landmarks such as optic disc and fovea. Present methods suffer from challenges like less accuracy and high computational complexity. To address this issue, this paper presents a novel approach for fast and accurate localization of optic disc (OD) and fovea using one-dimensional scanned intensity profile analysis. The proposed method utilizes both time and frequency domain information effectively for localization of OD. The final OD center is located using signal peak-valley detection in time domain and discontinuity detection in frequency domain analysis. However, with the help of detected OD location, the fovea center is located using signal valley analysis. Experiments were conducted on MESSIDOR dataset, where OD was successfully located in 1197 out of 1200 images (99.75%) and fovea in 1196 out of 1200 images (99.66%) with an average computation time of 0.52s. The large scale evaluation has been carried out extensively on nine publicly available databases. The proposed method is highly efficient in terms of quickly and accurately localizing OD and fovea structure together compared with the other state-of-the-art methods.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  2. Vascular intersection detection in retina fundus images using a new hybrid approach
    Aibinu AM, Iqbal MI, Shafie AA, Salami MJ, Nilsson M
    Comput Biol Med, 2010 Jan;40(1):81-9.
    PMID: 20022595 DOI: 10.1016/j.compbiomed.2009.11.004
    The use of vascular intersection aberration as one of the signs when monitoring and diagnosing diabetic retinopathy from retina fundus images (FIs) has been widely reported in the literature. In this paper, a new hybrid approach called the combined cross-point number (CCN) method able to detect the vascular bifurcation and intersection points in FIs is proposed. The CCN method makes use of two vascular intersection detection techniques, namely the modified cross-point number (MCN) method and the simple cross-point number (SCN) method. Our proposed approach was tested on images obtained from two different and publicly available fundus image databases. The results show a very high precision, accuracy, sensitivity and low false rate in detecting both bifurcation and crossover points compared with both the MCN and the SCN methods.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  3. Fulltext Accelerated diabetic retinopathy in pregnancy--a real and present danger
    Bastion MLC, Barkeh HJ, Muhaya M
    Med J Malaysia, 2005 Oct;60(4):502-4.
    PMID: 16570717
    A 36 year-old Malay lady with diabetes mellitus in pregnancy and poorly controlled hypertension developed rapid progression of diabetic retinopathy from no retinopathy to florid proliferative retinopathy over three months in her right eye. She had subsequent loss of vision due to vitreous haemorrhage in the peri-partum period. She had good final visual acuity with quiescent retinopathy following pars planar vitrectomy. A similar course was avoided in the left eye by timely pan retinal photocoagulation.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  4. Analysis of retinal fundus images for grading of diabetic retinopathy severity
    Ahmad Fadzil MH, Izhar LI, Nugroho H, Nugroho HA
    Med Biol Eng Comput, 2011 Jun;49(6):693-700.
    PMID: 21271293 DOI: 10.1007/s11517-011-0734-2
    Diabetic retinopathy (DR) is a sight threatening complication due to diabetes mellitus that affects the retina. In this article, a computerised DR grading system, which digitally analyses retinal fundus image, is used to measure foveal avascular zone. A v-fold cross-validation method is applied to the FINDeRS database to evaluate the performance of the DR system. It is shown that the system achieved sensitivity of >84%, specificity of >97% and accuracy of >95% for all DR stages. At high values of sensitivity (>95%), specificity (>97%) and accuracy (>98%) obtained for No DR and severe NPDR/PDR stages, the computerised DR grading system is suitable for early detection of DR and for effective treatment of severe cases.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis*
  5. Determination of foveal avascular zone in diabetic retinopathy digital fundus images
    Ahmad Fadzil MH, Izhar LI, Nugroho HA
    Comput Biol Med, 2010 Jul;40(7):657-64.
    PMID: 20573343 DOI: 10.1016/j.compbiomed.2010.05.004
    Monitoring FAZ area enlargement enables physicians to monitor progression of the DR. At present, it is difficult to discern the FAZ area and to measure its enlargement in an objective manner using digital fundus images. A semi-automated approach for determination of FAZ using color images has been developed. Here, a binary map of retinal blood vessels is computer generated from the digital fundus image to determine vessel ends and pathologies surrounding FAZ for area analysis. The proposed method is found to achieve accuracies from 66.67% to 98.69% compared to accuracies of 18.13-95.07% obtained by manual segmentation of FAZ regions from digital fundus images.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis*
  6. Fulltext An automated blood vessel segmentation algorithm using histogram equalization and automatic threshold selection
    Saleh MD, Eswaran C, Mueen A
    J Digit Imaging, 2011 Aug;24(4):564-72.
    PMID: 20524139 DOI: 10.1007/s10278-010-9302-9
    This paper focuses on the detection of retinal blood vessels which play a vital role in reducing the proliferative diabetic retinopathy and for preventing the loss of visual capability. The proposed algorithm which takes advantage of the powerful preprocessing techniques such as the contrast enhancement and thresholding offers an automated segmentation procedure for retinal blood vessels. To evaluate the performance of the new algorithm, experiments are conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm performs better than the other known algorithms in terms of accuracy. Furthermore, the proposed algorithm being simple and easy to implement, is best suited for fast processing applications.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis*
  7. A decision support system for automatic screening of non-proliferative diabetic retinopathy
    Reza AW, Eswaran C
    J Med Syst, 2011 Feb;35(1):17-24.
    PMID: 20703589 DOI: 10.1007/s10916-009-9337-y
    The increasing number of diabetic retinopathy (DR) cases world wide demands the development of an automated decision support system for quick and cost-effective screening of DR. We present an automatic screening system for detecting the early stage of DR, which is known as non-proliferative diabetic retinopathy (NPDR). The proposed system involves processing of fundus images for extraction of abnormal signs, such as hard exudates, cotton wool spots, and large plaque of hard exudates. A rule based classifier is used for classifying the DR into two classes, namely, normal and abnormal. The abnormal NPDR is further classified into three levels, namely, mild, moderate, and severe. To evaluate the performance of the proposed decision support framework, the algorithms have been tested on the images of STARE database. The results obtained from this study show that the proposed system can detect the bright lesions with an average accuracy of about 97%. The study further shows promising results in classifying the bright lesions correctly according to NPDR severity levels.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  8. Diagnosis of diabetic retinopathy: automatic extraction of optic disc and exudates from retinal images using marker-controlled watershed transformation
    Reza AW, Eswaran C, Dimyati K
    J Med Syst, 2011 Dec;35(6):1491-501.
    PMID: 20703768 DOI: 10.1007/s10916-009-9426-y
    Due to increasing number of diabetic retinopathy cases, ophthalmologists are experiencing serious problem to automatically extract the features from the retinal images. Optic disc (OD), exudates, and cotton wool spots are the main features of fundus images which are used for diagnosing eye diseases, such as diabetic retinopathy and glaucoma. In this paper, a new algorithm for the extraction of these bright objects from fundus images based on marker-controlled watershed segmentation is presented. The proposed algorithm makes use of average filtering and contrast adjustment as preprocessing steps. The concept of the markers is used to modify the gradient before the watershed transformation is applied. The performance of the proposed algorithm is evaluated using the test images of STARE and DRIVE databases. It is shown that the proposed method can yield an average sensitivity value of about 95%, which is comparable to those obtained by the known methods.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis*
  9. Application of higher-order spectra for automated grading of diabetic maculopathy
    Mookiah MR, Acharya UR, Chandran V, Martis RJ, Tan JH, Koh JE, et al.
    Med Biol Eng Comput, 2015 Dec;53(12):1319-31.
    PMID: 25894464 DOI: 10.1007/s11517-015-1278-7
    Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39% for MESSIDOR dataset and 95.93 and 93.33% for local dataset, respectively.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis*
  10. Circulating miR-3197 and miR-2116-5p as novel biomarkers for diabetic retinopathy
    Ji H, Yi Q, Chen L, Wong L, Liu Y, Xu G, et al.
    Clin Chim Acta, 2020 Feb;501:147-153.
    PMID: 31678272 DOI: 10.1016/j.cca.2019.10.036
    Diabetic retinopathy (DR) is the leading cause of vision loss among older adults. The goal of this case-control study was to identify circulating miRNAs for the diagnosis of DR. The miRNeasy Serum/Plasma Kit was used to extract serum miRNAs. The μParaflo™ MicroRNA microarray was used to detect the expression levels of the miRNAs. The miRWalk algorithm was applied to predict the target genes of the miRNAs, which were further confirmed by the dual luciferase reporter gene system in HEK293T cells. A microarray was performed between 5 DR cases and 5 age-, sex-, body mass index-, and duration of diabetes-matched type 2 diabetic (T2DM) controls. The quantitative reverse transcription polymerase chain reaction technique was used to validate the differentially expressed circulating miRNAs in 45 DR cases and 45 well-matched controls. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the circulating miRNAs as diagnostic biomarkers for DR. Our microarray analysis screened out miR-2116-5p and miR-3197 as significantly up-regulated in DR cases compared with the controls. Furthermore, two miRNAs were validated in the 45 DR cases and 45 controls. The ROC analysis suggested that both miR-3197 and miR-2116-5p distinguished DR cases from controls. An additional dual-luciferase reporter gene assay confirmed that notch homolog 2 (NOTCH2) was the target gene of miR-2116-5p. Both miR-3197 and miR-2116-5p were identified as promising diagnostic biomarkers for DR. Future research is still needed to explore the molecular mechanisms of miR-3197 and miR-2116-5p in the pathogenesis of DR.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  11. Fulltext Diabetic eye screening in Malaysia: findings from the National Health and Morbidity Survey 2006
    Goh PP, Omar MA, Yusoff AF
    Singapore Med J, 2010 Aug;51(8):631-4.
    PMID: 20848059
    INTRODUCTION: Diabetic retinopathy (DR) is the commonest complication of diabetes mellitus (DM), and is the leading cause of blindness among working adults. Modification of the associated risk factors as well as early detection and treatment of sight-threatening DR can prevent blindness. Clinical practice guidelines recommend annual eye screening for patients with DM. The proportion of patients in Malaysia who adhere to this recommendation was initially unknown.
    METHODS: The Malaysian National Health and Morbidity Survey is a population-based survey conducted once every decade on the various aspects of health, behaviour and diseases. The DM questionnaire on eye screening was administered as face-to-face interviews with 2,373 patients with known DM who were aged 18 years and older.
    RESULTS: In all, 55 percent of patients with known DM had never undergone an eye examination. Among patients who had undergone eye examinations, 32.8 percent had the last examination within the last one year, 49.8 percent within the last one to two years, and 17.4 percent more than two years ago. A significantly lower proportion of younger patients and patients who received treatment for DM from non-government facilities had previously undergone eye examinations.
    CONCLUSION: The prevalence of DM observed among Malaysians aged 30 and above is 14.9 percent; thus, there is a significant number of people with potential blinding DR. Adherence to eye screening guidelines and the prompt referral of sight-threatening DR are essential in order to reduce the incidence of blindness among patients with DM.
    Study name: National Health and Morbidity Survey (NHMS-2006)
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  12. Fulltext A new blood vessel extraction technique using edge enhancement and object classification
    Badsha S, Reza AW, Tan KG, Dimyati K
    J Digit Imaging, 2013 Dec;26(6):1107-15.
    PMID: 23515843 DOI: 10.1007/s10278-013-9585-8
    Diabetic retinopathy (DR) is increasing progressively pushing the demand of automatic extraction and classification of severity of diseases. Blood vessel extraction from the fundus image is a vital and challenging task. Therefore, this paper presents a new, computationally simple, and automatic method to extract the retinal blood vessel. The proposed method comprises several basic image processing techniques, namely edge enhancement by standard template, noise removal, thresholding, morphological operation, and object classification. The proposed method has been tested on a set of retinal images. The retinal images were collected from the DRIVE database and we have employed robust performance analysis to evaluate the accuracy. The results obtained from this study reveal that the proposed method offers an average accuracy of about 97 %, sensitivity of 99 %, specificity of 86 %, and predictive value of 98 %, which is superior to various well-known techniques.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis*
  13. Fulltext Ophthalmology inpatient consultation: does it make a difference to inpatient management?
    Tajunisah I, Azida J, Zurina ZA, Reddy SC
    Med J Malaysia, 2009 Jun;64(2):130-3.
    PMID: 20058572 MyJurnal
    Ophthalmology consultation is one of the commonest requested services for inpatients in a tertiary hospital. A total of 290 ophthalmology consultation requests were received over a period of six months (average 12 consultation requests per week) and from these, 222 patients were examined. The patient demographics, the hospitalization data, type of consultations (screening, new problem, preexisting problem), reasons for consultations and the ophthalmology diagnosis were determined. Out of 290 consultation requests, internal medicine services requested the highest number (95, 32.8%); the commonest type of consultation was screening for eye diseases (161, 55.5%) and the most common reason for consultation was to rule out diabetic retinopathy (125, 43.1%). The top five ophthalmology diagnoses after examination were diabetic retinopathy (45, 20.3%), diabetic retinopathy ruled out (37, 16.6%), conjunctivitis (12, 5.4%), refractive error (11, 4.8%) and normal ocular examination (11, 4.9%). Inpatient ophthalmologic procedures were performed in 146 patients, the commonest of which was retinal laser photocoagulation. A total of 133 (59.9%) inpatients had a change in their management as a result of the ophthalmology consultation.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  14. Automatic tracing of optic disc and exudates from color fundus images using fixed and variable thresholds
    Reza AW, Eswaran C, Hati S
    J Med Syst, 2009 Feb;33(1):73-80.
    PMID: 19238899
    The detection of bright objects such as optic disc (OD) and exudates in color fundus images is an important step in the diagnosis of eye diseases such as diabetic retinopathy and glaucoma. In this paper, a novel approach to automatically segment the OD and exudates is proposed. The proposed algorithm makes use of the green component of the image and preprocessing steps such as average filtering, contrast adjustment, and thresholding. The other processing techniques used are morphological opening, extended maxima operator, minima imposition, and watershed transformation. The proposed algorithm is evaluated using the test images of STARE and DRIVE databases with fixed and variable thresholds. The images drawn by human expert are taken as the reference images. The proposed method yields sensitivity values as high as 96.7%, which are better than the results reported in the literature.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  15. Fulltext Status of diabetic retinopathy among diabetics registered to the Diabetic Eye Registry, National Eye Database, 2007
    Goh PP, National Eye Database Study Group
    Med J Malaysia, 2008 Sep;63 Suppl C:24-8.
    PMID: 19230243
    Diabetic Eye Registry, a web based registry hosted at the National Eye Database (www.acrm.org.my/end) collects data in a systematic and prospective nature on status of diabetic retinopathy (DR) among diabetics seen for the first time at Ministry of Health ophthalmology clinics. The 2007 report on 10,586 diabetics revealed that 63.3% of eyes examined had no DR, 36.8% had any form of DR, of which 7.1% had proliferative diabetic retinopathy. Up to 15.0% of eyes had vision threatening DR requiring laser or surgery at their first visit. Data on diabetic eye registry is useful in monitoring the quality of diabetic management, particularly in eye screening as reflected by the proportion of patients with severe DR needing intervention at the first visit to Ophthalmology clinics.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  16. Fulltext Awareness and knowledge of common eye diseases among the academic staff (non-medical faculties) of University of Malaya
    Chew YK, Reddy SC, Karina R
    Med J Malaysia, 2004 Aug;59(3):305-11.
    PMID: 15727374 MyJurnal
    A cross sectional study was conducted to assess the level of awareness and knowledge of common eye diseases (cataract, glaucoma, diabetic retinopathy and refractive errors) among 473 academic staff (non-medical faculties) of University Malaya. The awareness of cataract was in 88.2%, diabetic retinopathy in 83.5%, refractive errors in 75.3% and glaucoma in 71.5% of the study population. The knowledge about all the above common eye diseases was moderate, except presbyopia which was poor. Multivariate analysis revealed that females, older people, and those having family history of eye diseases were significantly more aware and more knowledgeable about the eye diseases. Health education about eye diseases would be beneficial to seek early treatment and prevent visual impairment in the society.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  17. Fulltext Sensitivity and specificity of automated analysis of single-field non-mydriatic fundus photographs by Bosch DR Algorithm-Comparison with mydriatic fundus photography (ETDRS) for screening in undiagnosed diabetic retinopathy
    Bawankar P, Shanbhag N, K SS, Dhawan B, Palsule A, Kumar D, et al.
    PLoS One, 2017;12(12):e0189854.
    PMID: 29281690 DOI: 10.1371/journal.pone.0189854
    Diabetic retinopathy (DR) is a leading cause of blindness among working-age adults. Early diagnosis through effective screening programs is likely to improve vision outcomes. The ETDRS seven-standard-field 35-mm stereoscopic color retinal imaging (ETDRS) of the dilated eye is elaborate and requires mydriasis, and is unsuitable for screening. We evaluated an image analysis application for the automated diagnosis of DR from non-mydriatic single-field images. Patients suffering from diabetes for at least 5 years were included if they were 18 years or older. Patients already diagnosed with DR were excluded. Physiologic mydriasis was achieved by placing the subjects in a dark room. Images were captured using a Bosch Mobile Eye Care fundus camera. The images were analyzed by the Retinal Imaging Bosch DR Algorithm for the diagnosis of DR. All subjects also subsequently underwent pharmacological mydriasis and ETDRS imaging. Non-mydriatic and mydriatic images were read by ophthalmologists. The ETDRS readings were used as the gold standard for calculating the sensitivity and specificity for the software. 564 consecutive subjects (1128 eyes) were recruited from six centers in India. Each subject was evaluated at a single outpatient visit. Forty-four of 1128 images (3.9%) could not be read by the algorithm, and were categorized as inconclusive. In four subjects, neither eye provided an acceptable image: these four subjects were excluded from the analysis. This left 560 subjects for analysis (1084 eyes). The algorithm correctly diagnosed 531 of 560 cases. The sensitivity, specificity, and positive and negative predictive values were 91%, 97%, 94%, and 95% respectively. The Bosch DR Algorithm shows favorable sensitivity and specificity in diagnosing DR from non-mydriatic images, and can greatly simplify screening for DR. This also has major implications for telemedicine in the use of screening for retinopathy in patients with diabetes mellitus.

    Study site: India
    Matched MeSH terms: Diabetic Retinopathy/diagnosis*
  18. Fulltext Retinopathy in type 2 diabetic patients with microalbuminuria
    Reddy SC, Kihn YM, Nurjahan MI, Ramil A
    Nepal J Ophthalmol, 2013;5(1):69-74.
    PMID: 23584650 DOI: http://dx.doi.org/10.3126/nepjoph.v5i1.7830
    OBJECTIVE: To determine the prevalence of retinopathy in type 2 diabetic patients with micoalbuminuria and to evaluate the association of risk factors with prevalence of retinopathy in these patients.
    MATERIAL AND METHODS: A fundus examination of 137 patients suffering from type 2 diabetes mellitus with microalbuminuria was done, with direct ophthalmoscope/ binocular indirect ophthalmoscope after dilating the pupils with 1 % tropicamide eye drops. Retinal changes were graded as no retinopathy, non-proliferative retinopathy, proliferative retinopathy and maculopathy. The association of the duration of diabetes, control of diabetes, hypertension, hyperlipidemia, smoking, obesity and peripheral neuropathy was assessed with the prevalence of retinopathy in these patents.
    RESULTS: The mean age of the patients was 58 years (range 35 - 79 years); 62 % were females, and 49.6 % were Chinese. Diabetic retinopathy was seen in 36.5 % of the patients - non proliferative in 29.2 %, proliferative in 7.3 % and maculopathy in 5.1 % of patients. A longer duration of diabetes (p = 0.002), poor control of diabetes (p = 0.002), presence of hypertension (p = 0.03), and presence of peripheral neuropathy (p = 0.001) were significantly associated with the prevalence of retinopathy; while hyperlipidemia (p = 0.29), smoking (p = 0.43) and obesity (p = 0.43) were not associated with retinopathy.
    CONCLUSION: Retinopathy was seen in 36.5 % of type 2 diabetic patients with microalbuminuria; 7.3 % had proliferative retinopathy and 5.1 % maculopathy (both sight threatening changes). All diabetic patients with microalbuminuria should be screened for retinopathy so that treatment can be instituted in the required patients to prevent ocular morbidity/ blindness.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  19. An efficient algorithm for retinal blood vessel segmentation using h-maxima transform and multilevel thresholding
    Saleh MD, Eswaran C
    Comput Methods Biomech Biomed Engin, 2012;15(5):517-25.
    PMID: 21331960 DOI: 10.1080/10255842.2010.545949
    Retinal blood vessel detection and analysis play vital roles in early diagnosis and prevention of several diseases, such as hypertension, diabetes, arteriosclerosis, cardiovascular disease and stroke. This paper presents an automated algorithm for retinal blood vessel segmentation. The proposed algorithm takes advantage of powerful image processing techniques such as contrast enhancement, filtration and thresholding for more efficient segmentation. To evaluate the performance of the proposed algorithm, experiments were conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm yields an accuracy rate of 96.5%, which is higher than the results achieved by other known algorithms.
    Matched MeSH terms: Diabetic Retinopathy/diagnosis
  20. Fulltext Diabetic Macular Edema Management in Asian Population: Expert Panel Consensus Guidelines
    Chhablani J, Wong K, Tan GS, Sudhalkar A, Laude A, Cheung CMG, et al.
    Asia Pac J Ophthalmol (Phila), 2020;9(5):426-434.
    PMID: 32956188 DOI: 10.1097/APO.0000000000000312
    PURPOSE: The aim of this consensus article was to provide comprehensive recommendations in the management of diabetic macular edema (DME) by reviewing recent clinical evidence.

    DESIGN: A questionnaire containing 47 questions was developed which encompassed clinical scenarios such as treatment response to anti-vascular endothelial growth factor and steroid, treatment side effects, as well as cost and compliance/reimbursement in the management of DME using a Dephi questionnaire as guide.

    METHODS: An expert panel of 12 retinal specialists from Singapore, Malaysia, Philippines, India and Vietnam responded to this questionnaire on two separate occasions. The first round responses were compiled, analyzed and discussed in a round table discussion where a consensus was sought through voting. Consensus was considered achieved, when 9 of the 12 panellists (75%) agreed on a recommendation.

    RESULTS: The DME patients were initially profiled based on their response to treatment, and the terms target response, adequate response, nonresponse, and inadequate response were defined. The panellists arrived at a consensus on various aspects of DME treatment such as need for classification of patients before treatment, first-line treatment options, appropriate time to switch between treatment modalities, and steroid-related side effects based on which recommendations were derived, and a treatment algorithm was developed.

    CONCLUSIONS: This consensus article provides comprehensive, evidence-based treatment guidelines in the management of DME in Asian population. In addition, it also provides recommendations on other aspects of DME management such as steroid treatment for stable glaucoma patients, management of intraocular pressure rise, and recommendations for cataract development.

    Matched MeSH terms: Diabetic Retinopathy/diagnosis
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links