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All Journal Proceeding Mulawarman International Conference on Tropical Public Health
Teruna, Muhammad Muaz Shahriman
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Public Health

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Survival Analysis of Diabetic Retinopathy Among Type 2 Diabetic Patients: A Systematic Review Teruna, Muhammad Muaz Shahriman; Razak, Tajul Rosli; Yasin, Siti Munira; Ali, Abdullah Ashraf Rafique; Isa, Mohamad Rodi
Mulawarman International Conference on Tropical Public Health Vol. 2 No. 2 (2025): The 4th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Background : Diabetic retinopathy (DR) is a major preventable microvascular complication of type 2 diabetes mellitus (T2DM) and a leading cause of visual impairment. Understanding survival time to DR onset and its modifiable predictors is essential for optimizing screening and management. This review synthesizes recent cohort and observational evidence on DR incidence, progression, and prognostic factors in adults with T2DM. Objective : This study aims to systematically review survival time to the onset or progression of diabetic retinopathy in adults with type 2 diabetes mellitus, evaluate prognostic factors influencing retinopathy-free survival, and compare survival patterns across populations and study designs to inform future prognostic models and prevention strategies. Research Methods/ Implementation Methods : A systematic search was conducted for articles published between 2016 and 2025 across major databases including PubMed, Scopus, ScienceDirect, and the Cochrane Library. Studies were included if they applied longitudinal, cohort, or survival analysis methods to assess the risk or progression of DR among T2DM patients. Seventeen eligible studies were identified, covering diverse populations across Asia and Europe. Data were extracted on study design, sample size, follow-up duration, key predictors, and outcomes. Findings were synthesized narratively due to heterogeneity in statistical models and outcome definitions. Results : Across the included studies, the cumulative incidence of DR ranged from 8% to 42% over follow-up periods of 3 to 15 years. Significant predictors of DR onset and progression included poor glycaemic control (HbA1c ≥ 7.5%), longer diabetes duration, hypertension, dyslipidaemia, and obesity indices. Novel biomarkers such as the glycaemic risk index (GRI), neutrophil-to-lymphocyte ratio, and vitamin D deficiency demonstrated emerging prognostic potential. Conversely, metformin use and higher physical activity levels were protective against DR development. Time-to-event analyses revealed that patients maintaining a tight glycaemic range (3.9–7.8 mmol/L) and regular physical activity exhibited longer DR-free survival. Geographic variations were observed, with higher incidence reported in East and Southeast Asian cohorts compared to European populations. Conclusion/Lesson Learned : This systematic review highlights the multifactorial determinants influencing the survival and progression of diabetic retinopathy among individuals with T2DM. Glycaemic variability, metabolic dysregulation, and inflammatory markers remain strong predictors of reduced DR-free survival, while lifestyle modification and pharmacological control confer protective benefits. These findings underscore the importance of integrated, longitudinal monitoring and early preventive strategies in diabetic eye care. Future survival models should incorporate composite risk indices and real-world data to improve prediction accuracy and clinical applicability.
Prognostic Models for Recurrent Bacteriologically ConfirmedTuberculosis: Evidence and Applications in Malaysia Rameli, Nur Adila Che; Razak, Tajul Rosli; Ismail, Nurhuda; Ismail, Ahmad Izuanuddin; Teruna, Muhammad Muaz Shahriman; Salleh, Muhammad Muzzammil Mohamad; Yusoff, Mohamad Zuhair Mohamed; Khebir, Muhammad Hariz ‘Ammar; Sallehhu, Muhammad Irfan Mohd
Mulawarman International Conference on Tropical Public Health Vol. 2 No. 2 (2025): The 4th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Background : Bacteriologically confirmed recurrent tuberculosis (TB) continues to become a hurdle to TB elimination efforts. Patients experiencing recurrence face poorer treatment outcomes, higher mortality and increased risk of community transmission. Early identification of high-risk individuals for recurrence is important to support targeted surveillance, timely clinical follow-up and optimised preventive strategies. A prognostic risk score offers a systematic approach to risk-stratifying and promotes proactive intervention before disease reactivation. Objective : To develop and validate a prognostic bacteriologically-confirmed recurrent TB risk score Methods : Research The process will be conducted in three phases: identification of independent predictors associated with bacteriologically confirmed recurrent TB and development of the risk score, internal validation and external validation. Predictor selection and model development will be using multivariable regression techniques. Model performance will be assessed through discrimination and calibration indices and will be evaluated across phases.Methods/ Implementation Results :This study will produce a validated bacteriologically confirmed Recurrent TB risk score tool. The parameters of sensitivity, specificity, receiver operative characteristics, will be calculated and compared to determine the performance of the tool. Conclusion/Lesson Learned : This study will be able to identify high risk individuals prior to recurrence and has the potential to guide targeted monitoring, strengthen TB control efforts and reduce TB burden. Findings also support evidence based risk stratification for other infectious disease with recurrence potential.
Factors Associated with Ischemic Heart Disease (IHD) among Type 2 Diabetes Mellitus Patients: Evidence from the National DiabetesRegistry of Johor, Malaysia Salleh, Muhammad Muzzammil Mohamad; Kasim, Sazzli Shahlan; Razak, Tajul Rosli; Azahar, Nazar Mohd; Ismail, Norzaher; Yusoff, Mohamad Zuhair Mohamed; Khebir, Muhammad Hariz ‘Ammar; Teruna, Muhammad Muaz Shahriman; Rameli, Nur Adilla Che; Moh, Muhammad Irfan
Mulawarman International Conference on Tropical Public Health Vol. 2 No. 2 (2025): The 4th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Background : IHD remains a leading cause of mortality among individuals with type 2 diabetes mellitus (T2DM). Despite the availability of extensive registry data, limited local evidence exists regarding factors associated with IHD among Malaysian diabetic populations. Objective : This study aimed to identify demographic, clinical, and pharmacological associated factors of IHD using data from the National Diabetes Registry (NDR) of Johor, Malaysia. Research Methods/ Implementation Methods : A cross-sectional analysis was conducted using NDR data from 11,082 adults with T2DM registered between 2019 and 2021. Sociodemographic, clinical, biochemical, and medication variables were analyzed. Univariable and multivariable logistic regression identified independent associated factors of IHD, expressed as adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Results : The prevalence of IHD among T2DM patients was 10.4% (95% CI=9.8, 11.0). Independent predictors of IHD included age ≥60 years (aOR = 1.57, 95% CI: 1.33–1.86), male sex (aOR = 1.46, 95% CI: 1.25–1.71), Chinese ethnicity (aOR = 1.60, 95% CI: 1.28–1.98), hypertension (aOR = 1.86, 95% CI: 1.38–2.51), dyslipidaemia (aOR = 1.47, 95% CI: 1.16–1.86), diabetes duration > 10 years (aOR = 1.35, 95% CI: 1.10–1.65), and diabetic retinopathy (aOR = 1.52, 95% CI: 1.28–1.79). Non- use of calcium channel blockers (aOR = 1.52, 95% CI: 1.32–1.76) increased IHD risk, while paradoxical inverse associations were noted for non-use of aspirin, ticlopidine, and beta-blockers, likely reflecting confounding by indication. Glitazone use showed a strong association with IHD (aOR = 10.46, 95% CI: 1.423, 76.960), possibly due to small sample bias. Conclusion/Lesson Learned : IHD prevalence among Malaysian diabetics is substantial and driven by multiple modifiable and demographic factors. Integrating artificial intelligence (AI) predictive models within the NDR using these variables could enhance early risk stratification and targeted cardiovascular prevention.
Co-Authors Ali, Abdullah Ashraf Rafique Azahar, Nazar Mohd Isa, Mohamad Rodi Ismail, Ahmad Izuanuddin Ismail, Norzaher Ismail, Nurhuda Kasim, Sazzli Shahlan Khebir, Muhammad Hariz ‘Ammar Moh, Muhammad Irfan Rameli, Nur Adila Che Rameli, Nur Adilla Che Razak, Tajul Rosli Salleh, Muhammad Muzzammil Mohamad Sallehhu, Muhammad Irfan Mohd Yasin, Siti Munira Yusoff, Mohamad Zuhair Mohamed