THE EFFECT OF LUMBRICUS RUBELLUS DLBS1033 EXTRACT IN PATIENTS WITH TYPE 2 DIABETES MELLITUS

Type 2 Diabetes Mellitus (T2DM) is a major global health problem characterized by chronic hyperglycemia, persistent low-grade systemic inflammation, and vascular endothelial dysfunction. These pathological processes are central to the development of micro- and macrovascular complications, which are the leading causes of morbidity, mortality, and reduced quality of life in patients with T2DM.

Chronic hyperglycemia activates multiple pathophysiological pathways, including mitochondrial oxidative stress, the Advanced Glycation End Products (AGEs)-RAGE signaling axis, and impaired insulin signaling, collectively creating sustained systemic microinflammation and progressive endothelial damage. This endothelial dysfunction underlies the development of atherosclerosis, microcirculatory impairment, and pathological angiogenesis in T2DM patients.

High-sensitivity C-Reactive Protein (hs-CRP), a sensitive marker of systemic inflammation, is significantly elevated in T2DM and correlates with increased cardiovascular complication risk. Concurrently, Vascular Endothelial Growth Factor (VEGF), the primary mediator of endothelial cell proliferation and survival, exhibits the so-called 'VEGF paradox' in T2DM, whereby systemically elevated VEGF fails to produce functional neovascularization and instead promotes dysangiogenesis and pathological vascular permeability. These two pathways-hs-CRP-mediated inflammation and VEGF-mediated angiogenesis-interact in a mutually reinforcing pathological cycle that accelerates vascular complication progression.

Current T2DM management primarily targets glycemic control, which, while effective in reducing long-term complications, is insufficient to fully suppress chronic inflammation and correct vascular dysfunction. Adjuvant therapeutic strategies targeting non-glycemic pathogenic pathways, particularly inflammation and endothelial dysfunction, are therefore needed.

Lumbricus Rubellus extract (DLBS1033), produced by PT Dexa Medica through the Dexa Laboratories of Biomolecular Sciences (DLBS) in compliance with Good Manufacturing Practice (GMP) standards, contains low molecular weight proteins (Lumbricus Low Molecular Weight Proteins/LLP), including lumbrokinase-a serine protease enzyme with fibrinolytic, antithrombotic, and anti-inflammatory activities. Previous studies have demonstrated that lumbrokinase can suppress inflammatory mediators such as TNF-α and NF-κB, inhibit platelet aggregation, degrade fibrinogen, and improve microcirculatory function. However, its simultaneous effects on both hs-CRP and VEGF in T2DM patients remain insufficiently studied.

Eligible patients with T2DM attending the Endocrinology Outpatient Clinic of RSUD Dr. Moewardi Surakarta will be recruited consecutively and randomized using a block randomization method (fixed block size of 4) into three parallel groups: Intervention Group A (standard DM therapy + DLBS1033 490 mg t.i.d. as 3×1 tablet daily for 4 weeks), Intervention Group B (standard DM therapy + DLBS1033 490 mg t.i.d. as 3×2 tablets daily for 4 weeks), and Control Group (standard DM therapy alone). Randomization sequences will be generated independently using web-based software (www.random.org) and secured to maintain allocation concealment.

At baseline, all subjects will undergo clinical and demographic data collection, physical examination, and venous blood sampling for complete blood count, HbA1C, creatinine, SGOT, SGPT, hs-CRP (by immunoturbidimetric method), and VEGF (by Enzyme-Linked Immunosorbent Assay/ELISA). During the 4-week intervention period, biweekly follow-up visits will assess therapy adherence using the Medication Adherence Report Scale (MARS) and monitor for adverse effects. At week 4, repeat measurements of hs-CRP, VEGF, creatinine, SGOT, SGPT, MARS score, and health-related quality of life using the EQ-5D-5L questionnaire will be performed. Statistical analysis will use One-Way ANOVA (normally distributed data) or Kruskal-Wallis test (non-normally distributed data), with Analysis of Covariance (ANCOVA) and constrained Longitudinal Data Analysis (cLDA) for sensitivity analyses controlling for confounders including age, sex, nutritional status, comorbidities, and baseline biomarker values.