Impact of an Algorithm Based Combination Therapy on Glycemic Control in Newly Diagnosed Type 2 Diabetes Mellitus: A Retrospective Observational Study

Abstract

Background:Early, individualized pharmacotherapy is increasingly advocated to achieve prompt glycemic control and preserve β cell function in type 2 diabetes mellitus (T2DM) . Real world evidence on structured, algorithm driven combination regimens at diagnosis remains limited. Methods: We reviewed computerized outpatient records (January–October 2021) of adults with newly diagnosed T2DM attending a specialty clinic. Patients were stratified by baseline glycated hemoglobin (HbA1c) into Group 1 (7–9%), Group 2 (9–11%), and Group 3 (> 11%). A proprietary software generated treatment lines (triple, quadruple, or quintuple oral combinations) according to fasting/post prandial glucose–derived estimated HbA1c. Weight and glycemic indices were recorded at baseline, 3 and 6 months. The primary outcome was change in HbA1c. Results: Of 890 screened patients, 343 met inclusion criteria. Baseline mean ± SD HbA1c was 7.22 ± 0.54%, 9.09 ± 0.61%, and 12.92 ± 2.54% in Groups 1–3, respectively. HbA1c fell significantly at 3 months (–16.9%, –30.1%, –52.2%; p < 0.01) and was sustained at 6 months (Figure 1). Mean fasting and post prandial glucose declined by 14–57% and 27–61%, respectively (Tables 2–3). Body weight remained neutral in Groups 1–2 but increased modestly in Group 3 (+5.4%, p = 0.016). Medication burden decreased over time: in Group 3 the proportion receiving quintuple therapy fell from 100% to 0.5%, while triple or dual therapy rose to 80.6% by month 6 (Figure 2). No severe hypoglycemia or ketoacidosis was reported. Conclusion: An algorithm based strategy delivering intensive, baseline HbA1c matched oral combinations achieved rapid, durable glycemic control with progressive treatment de escalation in newly diagnosed T2DM. Pragmatic digital algorithms may complement current guidelines by operationalizing early combination therapy.