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"Retinopati diabetik adalah kelainan vaskular retina yang disebabkan oleh diabetes jangka panjang. Deteksi dini retinopati diabetik pada pasien diabetes diperlukan karena tidak ada gejala yang terlihat selama tahap awal penyakit. Para peneliti mengembangkan metode berbasis komputer untuk membantu dokter dalam proses deteksi dini. Dokter dapat menggunakan output dari metode tersebut sebagai pertimbangan dalam mediagnosis tipe retinopati diabetik yang diderita pasien. Salah satu metode yang populer adalah deep learning. Pada penelitian ini, dibangun gabungan dua algoritma deep learning, yaitu Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) untuk deteksi retinopati diabetik dengan output berupa caption yang menjelaskan kondisi yang ada pada citra fundus pasien. CNN digunakan untuk mengekstraksi fitur lesi retinopati diabetik pada citra fundus, dan LSTM digunakan untuk membuat caption berdasarkan fitur lesi tersebut. Penelitian ini menggunakan empat model CNN, yakni AlexNet, pre-trained AlexNet, GoogleNet, dan pre-trained GoogleNet. Simulasi gabungan algoritma CNN-LSTM dilakukan dengan proporsi data yang berbeda menggunakan data set dari Rumah Sakit Cipto Mangunkusumo. Hasil simulasi menunjukkan bahwa gabungan algortima CNN-LSTM dapat mendeteksi fitur lesi dan membuat caption dengan rata-rata kinerja akurasi tertinggi sebesar 91.69% untuk model pre-trained GoogleNet-LSTM dan proporsi data 80% data training dan 20% data testing.

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Diabetic retinopathy is a retinal vascular disorder caused by long-term diabetes. Early diabetic retinopathy detection in diabetes patients is needed because no symptoms can be seen during the early stage of disease. The researchers developed a computer-based method to assist ophthalmologists in the early detection process. Ophthalmologists can use the output of the method as a consideration in diagnosing the type of diabetic retinopathy. One of the popular methods is deep learning. In this study, a combination of two deep learning algorithms, namely Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM), was constructed for diabetic retinopathy detection with the output in the form of a caption that explains the condition present in the patient’s fundus images. CNN is used to extract features of diabetic retinopathy lesions on fundus images, and LSTM is used to generate a caption based on those lesion features. This study used four CNN models that are AlexNet, pre-trained AlexNet, GoogleNet, and pre-trained GoogleNet. Simulation of a combined CNN-LSTM algorithm has been done with the different proportions of data using a data set from Cipto Mangunkusumo National General Hospital. The simulation results show that a combined CNN-LSTM algorithm can detect lesion features and generate caption with the highest average performance accuracy of 91.69% for pre-trained GoogleNet-LSTM and the proportion 80% training data and 20% testing data."

"Latar belakang: Retinopati diabetik (diabetic retinopathy, DR) merupakan komplikasi diabetes mellitus (DM) yang dapat menyebabkan kebutaan. Kesadaran pasien DM terhadap DR dapat diukur dari pengetahuan, sikap, dan perilaku (knowledge, attitude, practice, KAP) dalam pencegahan DR.Tujuan: Mengetahui serta membandingkan pola karakteristik demografi dan skor KAP pasien DM tanpa DR terhadap DM dengan DR di Puskesmas Provinsi DKI Jakarta menggunakan kuesioner yang teruji valid dan reliabel.Metode: Subjek dirandomisasi menggunakan cluster random sampling terhadap 17 Puskesmas di Provinsi DKI Jakarta yang telah dilakukan skrining DR terhadap pasien DM.Hasil: Subjek terdiri dari 205 subjek dengan DR & 210 subjek tanpa DR. Terdapat perbedaan bermakna antar kelompok durasi DM, pendidikan terakhir, dan penghasilan perbulan terhadap pengetahuan. Terdapat perbedaan bermakna antar kelompok durasi DM, pendidikan terakhir, penghasilan perbulan, dan pekerjaan terhadap sikap. Terdapat perbedaan bermakna antar seluruh variabel kelompok terhadap perilaku. Pada kelompok tanpa DR, terdapat korelasi antara pengetahuan dan perilaku (p <0.001) dengan korelasi lemah (r: 0.37) dan terdapat korelasi antara sikap dan perilaku (p <0.001) dengan korelasi sedang (r: 0.45). Pada kelompok dengan DR, terdapat korelasi antara pengetahuan dan perilaku (p <0.001) dengan korelasi lemah (r: 0.40) dan terdapat korelasi antara sikap dan perilaku (p <0.001) dengan korelasi sedang (r: 0.45). Terdapat perbedaan bermakna rerata skor perilaku (p: 0.036) antar kelompok tanpa DR dan dengan DR, tidak terdapat perbedaan bermakna dari rerata skor pengetahuan dan sikap.Kesimpulan: Terdapat hubungan antara pengetahuan dan sikap terhadap perilaku penderita DM tanpa DR dan dengan DR. Terdapat perbedaan bermakna perilaku antara kelompok tanpa DR dan dengan DR.

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Background: Diabetic retinopathy (DR) is a complication of diabetes mellitus (DM) which can cause blindness. DM patient awareness of DR can be measured from knowledge, attitude and practice (KAP) in preventing DR.

Purpose: Determine and compare the pattern of demographic characteristics and KAP scores of DM without DR to DM with DR groups at the DKI Jakarta Provincial Health Center using a valid and reliable questionnaire.Methods: Subjects were randomized using the cluster random sampling to 17 Community Health Centers in DKI Jakarta Province which had DR screening done for DM patients.

Result: Subject consists of 205 subjects with DR & 210 subjects without DR. There were significant differences between groups of duration of DM, last education, and monthly income towards knowledge. There were significant differences between groups of duration of DM, last education, monthly income, and job towards attitude. There were significant differences between all group variables towards practice. In the group without DR, there was a correlation between knowledge and practice (p <0.001) with a weak correlation (r: 0.37) and there was a correlation between attitude and practice (p <0.001) with a moderate correlation (r: 0.45). In the group with DR, there was a correlation between knowledge and practice (p <0.001) with a weak correlation (r: 0.40) and there was a correlation between attitude and practice (p <0.001) with a moderate correlation (r: 0.45). There was a significant difference in the mean practice score (p: 0.036) between two groups, but there was no significant difference in the mean knowledge and attitude scores.

Conclusion: There were a correlation between knowledge and attitude towards the practice of without DR and with DR groups. There were significant differences in practice between DM with DR and DM without DR groups."

"Latar Belakang: Sindrom renal-retinal diabetes (SRRD) merupakan koinsidensi nefropati dan retinopati diabetik yang menimbulkan komplikasi serius berupa penurunan kualitas hidup dan peningkatan mortalitas dengan risiko kardiovaskular sebesar 4,15 kali lipat. Sementara itu, angka deteksi dini retinopati dan nefropati masih rendah dan faktor-faktor yang berhubungan dengan SRRD pada penyandang DMT2 di Indonesia belum diketahui.Tujuan: Mengetahui faktor-faktor yang berhubungan dengan sindrom renal-retinal diabetes pada DMT2 di RSCM.Metode: Penelitian ini merupakan studi observasional potong lintang yang dilakukan pada 157 subjek DMT2 berusia > 18 tahun. Data karakteristik subjek didapat dari anamnesis, pemeriksaan fisik, pemeriksaan foto fundus retina, dan pengambilan sampel darah dan urin. Hubungan antara faktor-faktor yang berhubungan dengan SRRD dianalisis secara bivariat dengan chi square dan multivariat dengan regresi logistik menggunakan Statistical Package for the Social Sciences (SPSS) versi 21.0.Hasil: Sebanyak 157 pasien terlibat dalam penelitian ini. Prevalensi SRRD adalah 28,7%, dengan rerata usia 56 (27-76) tahun, rerata IMT 25,7 (21,3-33,8) kg/m, median durasi DM 12 (1-25) tahun dengan HbA1c 8,6 (4,8-15,8) %, prevalensi hipertensi 86,7%, prevalensi dislipidemia 91%, 76,4% pasien tidak merokok, 33,3% pasien albuminuria derajat A2 dan 66,7% derajat A3. Pada SRRD, prevalensi derajat nefropati berdasarkan klasifikasi adalah 0% risiko rendah, 13,3% risiko sedang, 20% risiko tinggi, dan 66,7% risiko sangat tinggi dan prevalensi derajat retinopati diabetik adalah 42,2% NPDR, 55,6% PDR, 24,2% DME, dengan angka deteksi dini retinopati dan nefropati adalah sebesar 20% dan 17,8%. Analisis bivariat dan multivariat menunjukkan terdapat hubungan bermakna antara durasi DM (p=0,001) dan albuminuria (p=0,008) dengan kejadian SRRD.Simpulan: Proporsi SRRD pada penyandang DMT2 cukup tinggi (28,7%) dan pada studi ini, faktor-faktor yang berhubungan dengan kejadian SRRD pada DMT2 adalah durasi DM dan albuminuria.

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Backgrounds: Diabetic renal-retinal syndrome (DRRS) is a coincidence of diabetic nephropathy and retinopathy that cause serious complications as decreased quality of life and increased mortality with cardiovascular event risk 4,15 times higher. Meanwhile, early detection rate of retinopathy and nephropathy are still low and associated factors of DRRS among Indonesian type 2 diabetes mellitus (T2DM) patients has not been known.

Objective: To obtain the factors related to DRRS among T2DM patients in Cipto Mangunkusumo hospital.

Methods: This was a cross-sectional study involving 157 T2DM subjects aged 18 characteristics were obtained from anamnesis, physical examination, retinal fundus, and blood and urine sample. Bivariate and multivariate analysis using statistical package for the social sciences (SPSS) version 21.0 was used to analyze the factors related to DRRS.

Results: 157 patients were included in this study. The prevalence of DRRS was 28,7% with median age was 56 (27-76) year old, mean BMI was 25,7 (21,3-33,8) kg/m2, median duration of DM was 12 (1-25) year old and HbA1c 8,6% (4,8-15,8%), prevalence of hypertension was 86,7%, prevalence of dyslipidemia was 91%, 76,4% patients were not smoker, 33,3% patients with albuminuria grade A2 and 66,7% patients with grade A3. In DRRS, the prevalence of nephropathy was classified as 0% low risk, 13,3% moderate risk, 20% high risk, and 66,7% very high risk and the the prevalence of diabetic retinopathy was 42,2% NPDR, 55,6% PDR, 24,2% DME with early detection rate of retinopathy and nephropathy were 20% and 17,8%. Bivariate and multivariate analysis showed significant correlation with duration of DM (p=0,001) and albuminuria (p=0,008) with DRRS.

Conclusions: DRRS proportion in T2DM was high (28,7%) and this study showed that duration of DM and albuminuria were correlated with DRRS."

"Diabetes melitus (DM) dapat menyebabkan berbagai komplikasi, salah satunya diabetik retinopati yang merupakan penyebab utama kebutaan pada orang dewasa. Salah satu pengobatan yang dilakukan terhadap penyakit ini ialah injeksi intravitreal senyawa kortikosteroid yang umumnya hanya bertahan hingga 3 bulan. Injeksi yang cukup sering dapat meningkatkan resiko katarak, pseudo-endophtalmitis dan meningkatkan tekanan intraokular. Sehingga dibutuhkan sistem pelepasan terkendali agar obat dapat memberikan efek terapeutik lebih lama setidaknya hingga 6 bulan. Sistem enkapsulasi senyawa aktif deksametason menggunakan polimer PolyLactic Co-Glycolic Acid (PLGA) 90:10 dengan penambahan surfaktan kationik Dioctadecyldimethylammonium Bromide diharapkan dapat meningkatkan lama tinggalnya obat. Penambahan surfaktan pada nanopartikel dilakukan dengan dua metode. Dalam penelitian ini diperoleh efisiensi enkapsulasi dan pemuatan obat partikel PLGA-PVA-DDAB sebesar 13.47% dan 3.26%, sementara PLGA-DDAB-PVA sebesar 11.54% dan 2.74%. Morfologi partikel sferis dan tidak beragregat. Ukuran partikel yang dihasilkan ialah PLGA-PVA = 2151.2 11.8 nm, PLGA-PVA-DDAB = 1308.2 59.5 nm, PLGA-DDAB = 626.9 nm, dan PLGA-DDAB-PVA = 547.4 87.02 nm. Muatan permukaan partikel ialah PLGA-PVA = -27.7 mV, PLGA-PVA-DDAB = -22.6 mV, PLGA-DDAB = +22.5 mV, dan PLGA-DDAB-PVA = -15.4 mV.

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Diabetes melitus (DM) can leads to various of complications, one of those is diabetic retinopathy, the main cause of blindness in adults. The latest common treatment for this disease is corticosteroids intravitreal injection that is generally lasted for only three months. High frequency of injection could increase the risk of cataract, pseudo-endophthalmitis and increasing intraocular pressure. Thus, a controlled release drug system is needed to obtain drug that give a longer therapeutic effect, at least for six months. Encapsulation of dexamethasone using PolyLactic Co-Glycolic Acid (PLGA) 90:10 with addition of Dioctadecyldimethylammonium Bromide as the cationic surfactant is expected to prolong drugs retention time. There are two methods used for addition of cationic surfactant. In this research, we obtained that the encapsulation efficiency and loading capacity of PLGA-PVA-DDAB particles are 13.47% and 3.26%, meanwhile PLGA-DDAB-PVA particles are 11.54% dan 2.74%. The particles? morphology are spheres without aggregation. Particles size are PLGA-PVA = 2151.2 11.8 nm, PLGA-PVA-DDAB = 1308.2 59.5 nm, PLGA-DDAB = 626.9 nm, and PLGA-DDAB-PVA = 547.4 87.02 nm. Surface charge of particles are PLGA-PVA = -27.7 mV, PLGA-PVA-DDAB = -22.6 mV, PLGA-DDAB = +22.5 mV, and PLGA-DDAB-PVA = -15.4 mV."

"ABSTRACTBACKGROUND:proliferative diabetic retinopathy (DR) is an advanced form of DR that eventually could lead to blindness. Levels of vitreous advanced glycation end products (AGEs) and D-dimer may reflect the pathological changes in the retina, but only few studies have assessed their correlation with blood hemoglobin A1C (HbA1c) levels. This study aimed to find the association between blood HbA1c levels with vitreous AGEs and D-dimer levels in patients with proliferative DR. METHODS:an analytical cross-sectional study was performed in subjects with proliferative DR who underwent vitrectomy. Subjects were divided into 2 subgroups, i.e. uncontrolled (HbA1c >7%) and controlled (HbA1c <7%) groups. Vitreous AGEs and D-dimer levels were assessed; the levels were compared between uncontrolled and controlled hyperglycemic patients. Statistic correlation tests were also performed for evaluating blood HbA1c, vitreous AGEs, and D-dimer levels.RESULTS:a total of 47 patients were enrolled in this study and 32 (68.1%) of them were women. Median vitreous AGEs level was 11.0 (3.0 - 48.0) µg/mL; whereas median vitreous D-dimers level was 5,446.0 (44.0 - 37,394.0 ) ng/mL. The median vitreous AGEs levels was significantly higher in patients with uncontrolled vs. controlled hyperglycemia (14.0 vs. 4.0 mg/mL; p<0.001). There was a significant positive correlation with moderate strength between blood HbA1c level and vitreous AGEs level (r=0.524; r2=0.130; p=0.0001). Blood HbA1c level could be used to predict vitreous AGEs level by using the following calculation: vitreous AGEs = -1.442+ (1.740xblood HbA1c). Vitreous D-dimer levels were not significantly different between uncontrolled and controlled hyperglycemia (median 4607.5 vs. 5701.6 ng/mL; p = 0.458). There was a positive significant correlation between blood HbA1c and vitreous D-dimer levels (r = 0.342; p = 0.019); however the correlation was weak. Vitreous AGEs level had a positive significant correlation with vitreous D-dimer levels (r = 0.292; p = 0.046) and the correlation strength was also weak.CONCLUSION:median vitreous AGEs levels were significantly higher in proliferative DR patients with uncontrolled than those with controlled hyperglycemia. Blood HbA1c level can be used to assess vitreous AGEs level in patients with proliferative DR by using the following calculation: vitreous AGEs = -1.442+(1.740 x HbA1c). However, the blood HbA1c level can not be used to predict vitreous D-dimer level in patients with proliferative DR."

"Retinopati Diabetik adalah salah satu penyakit pada retina disebabkan oleh komplikasi diabetes yang dapat berujung pada kebutaan. Retinopati Diabetik tidak bisa dideteksi langsung secara kasat mata karena tanda-tandanya berada di bagian syaraf retina. Dari beberapa penelitian yang telah dilakukan pendeteksian Retinopati Diabetik dimungkinkan dapat dilakukan dengan melakukan klasifikasi menggunakan data citra retina atau yang biasa disebut sebagai citra fundus. Dalam penelitian ini diterapkan metode segmentasi citra yaitu Watershed dan Efficient Graph-Based beserta metode klasifikasi yaitu K-Nearest Neighbor dan Support Vector Machine dalam pendeteksian Retinopati Diabetik. Dari hasil implementasi, metode untuk segmentasi Efficient Graph-Based menggunakan data citra fundus dari DIARETDB0 diperoleh nilai akurasi, recall, dan precision lebih tinggi dibandingkan dengan metode segmentasi Watershed.

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Diabetic Retinopathy is one of disease on retina because of Diabetic complication that can cause blindness. Diabetic Retinopathy cant detected directly from the eyes because sign of Diabetic Retinopathy itself is in the eyes nerve. From several research that has been done prove that Diabetic Retinopathy can be detected by using retinas image or usually called fundus image.

In this research use segmentation method that is Watershed and Efficient Graph-Based with classification method that is K-Nearest Neighbor and Support Vector Machine for detection of Diabetic Retinopathy. From the implementation result, the Efficient Graph-Based segmentation method using fundus image data from the DIARETDB0 obtained that the accuracy, recall, and precision score is higher than Watershed segmentation method."

"Penelitian ini bertujuan mengetahui efek hiperglikemia postprandial terhadap kemampuan memori jangka pendek pada pasien DM tipe 2. Penelitian ini adalah penelitian kuantitatif dengan desain quasy experiment post test group.Jumlah sampel sebanyak 35 responden. Hasil penelitian ini menyatakan ada perbedaan kadar gula darah dan kemampuan memori jangka pendek antara satu jam dan dua jam setelah makan. Saran penelitian ini adalah perlu dilakukan skrining kognitif sejak dini kepada pasien DM, edukasi pasien DM diberikan dua jam setelah makan dan perlu ada penelitian lanjutan yang melibatkan jumlah sampel yang besar dan faktor-faktor yang berkontribusi terhadap penurunan kognitif pasien DM.

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This study aims to determine the effects of postprandial hyperglycemia on the ability of short-term memory in patients with type 2 diabetes. This research is a quantitative research with quasy experiment posttest design. Number of respondents were 35 people. The results there are differences in blood sugar level and short term memory ability one hour and two hour after meal.

Suggestion study was conducted in early cognitive screening for diabetic patients, education were given two hours after a meal and there needs to be further research involving a large number of samples and the factors that contribute to cognitive decline."

"Jatuh merupakan penyebab utama kedua cedera dan kematian yang tidak disengaja di seluruh dunia. Kejadian ini sering terjadi pada lansia dan frekuensinya meningkat setiap tahun. Sistem pendeteksi aktivitas jatuh yang reliabel dapat mengurangi risiko cedera yang dialami. Mengingat jatuh adalah kejadian yang tidak dikehendaki atau terjadi secara tiba-tiba, sulit untuk mengumpulkan data jatuh yang sebenarnya. Deteksi jatuh juga sulit karena kemiripannya dengan beberapa aktivitas seperti jongkok, dan mengambil objek dari lantai. Selain itu, beberapa tahun belakangan dataset mengenai aktivitas jatuh yang tersedia secara publik juga terbatas. Oleh karena itu, di tahun 2019, beberapa peneliti mencoba membuat dataset jatuh yang komprehensif yang mensimulasikan kejadian yang sebenarnya dengan menggunakan perangkat kamera dan sensor. Dataset yang dihasilkan dataset multimodal bernama UP-Fall. Menggunakan dataset tersebut, penelitian ini mencoba mendeteksi aktivitas jatuh dengan pendekatan Convolutional Neural Network (CNN) dan Long Short Term Memory (LSTM). CNN digunakan untuk mendeteksi informasi spasial dari data citra, sedangakan LSTM digunakan untuk mengeksploitasi informasi temporal dari data sinyal. Kemudian, hasil dari kedua model digabungkan dengan strategi majority voting. Berdasarkan hasil evaluasi, CNN memperoleh akurasi sebesar 98,49% dan LSTM 98,88%. Kedua model berkontribusi kepada performa strategi majority voting sehingga mendapatkan akurasi (98,31%) yang melebihi akurasi baseline (96,4%). Metrik evaluasi lain juga meningkat seperti precision naik 11%, recall 14%, dan F1-score 12% jika dibandingan dengan baseline

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.Fall is the second leading cause of accidental injury and death worldwide. This event often occurs in the elderly and the frequency is increasing every year. Reliable fall activity detection system can reduce the risk of injuries suffered. Since falls are unwanted events or occur suddenly, it is difficult to collect actual fall data. It is also difficult because of the similarity to some activities such as squatting, and picking up objects from the floor. In addition, in recent years the fall dataset that is publicly available is limited. Therefore, in 2019, some researchers tried to create a comprehensive fall dataset that simulates the actual events using camera and sensor devices. The experiment produced a multimodal dataset UP-Fall. Using this dataset, this study tries to detect falling activity using Convolutional Neural Network and Long Short Term Memory approaches. CNN is used to detect spatial information from image data, while LSTM is used to exploit temporal information from signal data. Then, the results of the two models are combined with the majority voting strategy. Based on the evaluation results, CNN obtained an accuracy of 98.49% and LSTM 98.88%. Both models contribute to the performance of the majority voting strategy with the result that the accuracy (98.31%) exceeds baseline accuracy (96.4%). Other evaluation metrics also improved such as precision goes up to 11%, recall 14%, and F1-score 12% in comparison with baseline."

"Latar Belakang : Pasien Non-Proliferative Diabetic Retinopathy (NPDR), Proliferative Diabetic Retinopathy (PDR) dengan neuropati kornea akan mengalami terganggunya stabilitas air mata. Penurunan sekresi dan konsituen air mata akan menyebabkan gangguan berupa mata kering. Pada pasien Diabetes dengan retinopati diabetik, gangguan kornea ini berpotensi lebih memperburuk gangguan penglihatan yang terjadi. Tujuan : Menilai stabilitas air mata pada pasien NPDR, PDR dengan neuropati kornea sebelum, sesudah diberikan tetes mata Sodium hyaluronat+Vitamin A,E (HA+Vit A,E) atau Sodium Hyaluronat saja (HA). Metodologi : Penelitian ini merupakan uji eksperimental randomisasi acak terkontrol, dengan dua kelompok utama (NPDR, PDR), kedua kelompok mendapatkan tetes mata HA+Vit A,E atau HA selama 28 hari. Sensitivitas kornea, Skoring Ocular Surface Disease Index (OSDI), Non-Invasive Break Up Time (NIBUT), Schirmer I, jumlah sel goblet konjungtiva dinilai pada 0, 2, 4 minggu. Hasil : 96 subyek berpartisipasi, 65.6% wanita, 34.4% laki-laki (rerata usia 54.4 tahun). Skor OSDI memperlihatkan perbaikan signifikan, nilai terbesar pada kelompok PDR HA+Vit A,E dengan -4.86±5.76 (P= 0.000), NIBUT memperlihatkan perbaikan signifikan, nilai terbesar pada kelompok NPDR HA dengan 4.79±2.63 (P= 0.000), Schirmer I memperlihatkan perbaikan signifikan, hasil terbesar pada kelompok NPDR HA dengan 2.41±2.35 (P= 0.000). Sitologi impressi konjungtiva memperlihatkan perbaikan signifikan, terutama pada kelompok NPDR HA+Vit A,E (66% perbaikan). Seluruh kelompok memperlihatkan perbaikan signifikan, tetapi perbaikan antar kelompok tidak bermakna. Kesimpulan : Parameter seluruh kelompok memperlihatkan perbaikan yang signifikan setelah diberikan tetes mata HA+Vit A,E maupun HA saja, Tetapi jika dibandingkan antar kelompok, tidak terdapat perbedaan perbaikan yang signifikan.

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Background : Patient with Non-Proliferative Diabetic Retinopathy (NPDR), Proliferative Diabetic Retinopathy (PDR) with corneal neuropathy will experiencing disruption in tear film stability. Decrease in tear film secretion and constituent will cause dry eyes. In Diabetic patients with diabetic retinopathy, this corneal disorder has the potential to further worsen visual impairment.

Purpose : To Assess tear film stability in NPDR, PDR patients with corneal neuropathy before, after treatment with topical Sodium hyaluronat+Vitamin A,E (HA+Vit A,E) or Sodium Hyaluronat only (HA).

Method : This study was a double blind experimental randomized control trial with two parallel groups (NPDR, PDR), both group receives HA+Vit A,E or HA for 28 days. Corneal sensitivity, Ocular Surface Disease Index (OSDI), Non-Invasive Break Up Time (NIBUT), Schirmer I, conjungtival goblet cells will be assessed on 0, 2, 4 weeks.

Result : 96 subjects participated, 65.6% female, 34.4% male, mean age 54.4 years old. OSDI score shows significant improvement, highest improvement seen on PDR HA+Vit A,E with -4.86±5.76 (P= 0.000), NIBUT hows significant improvement, highest improvement seen on NPDR HA with 4.79±2.63 (P= 0.000), Schirmer I shows significant improvement, highest improvement seen on NPDR HA with 2.41±2.35 (P= 0.000). Conjungtival goblet cells shows significant improvement, highest improvement seen on NPDR HA+Vit A,E (66% improved). All groups shows shows significant improvement, but between groups the improvement was not statistically significant.

Conclusion : Parameters on all groups shows statistically significant improvement after topical HA+Vit A,E or HA. But, if compared between groups, the improvement was not significantly differed."