The Association Between Poor Glycaemic Control (Hba1c Levels ≥ 7%) and Higher Incidence of Diabetic Retinopathy in Small Group of Type 2 Diabetes Mellitus Patients Attending Mahatma Gandhi Memorial Government Hospital, Trichy

Sigamani, Vijayalakshmi; Kanagaraj, Nirmala Devi; Rajagantham, Vijayabharathi Kuppuswamy

doi:10.14260/jemds/2017/1031

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…17 Relationship between diabetic retinopathy and HbA1c levels showed that severity of retinopathy increased as HbA1c levels were raised and this is also supported by many other similar studies. [18][19][20][21] A study conducted by Rebecka Andreasson et al in Sweden showed similar results in children with type 1 diabetes. Increase in HbA1c levels corresponded to the severity of diabetic retinopathy.…”

Section: Discussionmentioning

confidence: 89%

Relationship between HbA1c Levels and Severity of Diabetic Retinopathy

Jamshed¹,

Hanif²,

Malik³

et al. 2021

pak J Ophthalmol

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Purpose: To determine the relationship between HbA1c and severity of retinopathy in diabetic patients. Study Design: Cross sectional study. Place and Duration of Study: Eye department of DHQ-UTH Gujranwala, from July 2020 to Dec 2020. Methods: An observational cross-sectional study including 100 patients was conducted at eye department of DHQ-UTH Gujranwala from January 2018 to December 2018. After approval from institutional review board, written informed consent with demographic variables was collected from every patient. Patients of either gender between 40-80 years of age with both types I and type II diabetes were included in this study. Complete ophthalmic examination including Best Corrected Visual Acuity, slit lamp biomicroscopy, Goldmann Applanation tonometry and fundus examination carried out. Diabetic retinopathy was classified from grade 0 to grade 5. Results: Out of 100 patients, 46 (46%) were males and 54 (54%) were females. Mean age was 60 ± 2.4 years with a range of 40 – 80 years among males and 40 – 70 years among females. Forty patients presented with grade 1 diabetic retinopathy and 4% presented with grade 5. Thirty two patients had good glycemic control while 20% had glycemic control of grade III. Patients with grade 4 diabetic retinopathy had the worst glycemic control of HbA1c level of 11.5. Conclusion: This study concluded that patients with poor glycemic control had severe diabetic retinopathy as compared to the patients with good diabetic control. There is a direct relation between HbA1c level and severity of diabetic retinopathy. Key Words: HbA1C, Diabetic retinopathy, Non proliferative diabetic retinopathy, Proliferative diabetic retinopathy, Vitreous hemorrhage.

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Section: Discussionmentioning

confidence: 89%

Relationship between HbA1c Levels and Severity of Diabetic Retinopathy

Jamshed¹,

Hanif²,

Malik³

et al. 2021

pak J Ophthalmol

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Microvascular Complications in Type-2 Diabetes: A Review of Statistical Techniques and Machine Learning Models

Sambyal

Saini

Syal

2020

Wireless Pers Commun

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A Review of Statistical and Machine Learning Techniques for Microvascular Complications in Type 2 Diabetes

Sambyal

Saini

Syal

2021

CDR

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Background and Introduction: Diabetes mellitus is a metabolic disorder that has emerged as a serious public health issue worldwide. According to the World Health Organization (WHO), without interventions, the number of diabetic incidences is expected to be at least 629 million by 2045. Uncontrolled diabetes gradually leads to progressive damage to eyes, heart, kidneys, blood vessels and nerves. Method: The paper presents a critical review of existing statistical and Artificial Intelligence (AI) based machine learning techniques with respect to DM complications namely retinopathy, neuropathy and nephropathy. The statistical and machine learning analytic techniques are used to structure the subsequent content review. Result: It has been inferred that statistical analysis can help only in inferential and descriptive analysis whereas, AI based machine learning models can even provide actionable prediction models for faster and accurate diagnose of complications associated with DM. Conclusion: The integration of AI based analytics techniques like machine learning and deep learning in clinical medicine will result in improved disease management through faster disease detection and cost reduction for disease treatment.

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The Association Between Poor Glycaemic Control (Hba1c Levels ≥ 7%) and Higher Incidence of Diabetic Retinopathy in Small Group of Type 2 Diabetes Mellitus Patients Attending Mahatma Gandhi Memorial Government Hospital, Trichy

Cited by 3 publications

References 14 publications

Relationship between HbA1c Levels and Severity of Diabetic Retinopathy

Relationship between HbA1c Levels and Severity of Diabetic Retinopathy

Microvascular Complications in Type-2 Diabetes: A Review of Statistical Techniques and Machine Learning Models

A Review of Statistical and Machine Learning Techniques for Microvascular Complications in Type 2 Diabetes

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