Insulin and Metformin Administration: Unravelling the Multifaceted Association with Mortality across Various Clinical Settings Considering Type 2 Diabetes Mellitus and COVID-19
Łukasz Lewandowski, Agnieszka Bronowicka-Szydełko, Maciej Rabczyński, Dorota Bednarska-Chabowska, Joanna Adamiec-Mroczek, Adrian Doroszko, Małgorzata Trocha, Krzysztof Kujawa, Agnieszka Matera-Witkiewicz, Edwin Kuźnik, Paweł Lubieniecki, Marcin Madziarski, Janusz Sokołowski, Ewa A Jankowska, Katarzyna Madziarska
Biomedicines, doi:10.3390/biomedicines12030605
Due to the molecular mechanisms of action of antidiabetic drugs, they are considered to be effective in the treatment of both COVID-19 and the post-COVID-19 syndromes. The aim of this study was to determine the effect of administering insulin and metformin on the mortality of patients with type 2 diabetes (T2DM) with symptomatic COVID-19 with the use of logistic regression models. The association between death and insulin and metformin was weak and could not be included in the multivariate model. However, the interaction of both drugs with other factors, including remdesivir and low-molecular-weight heparin (metformin), age and hsCRP (insulin), modulated the odds of death. These interactions hint at multifaceted (anti-/pro-) associations of both insulin and metformin with the odds of death, depending on the patient's characteristics. In the multivariate model, RDW-SD, adjusted with low-molecular-weight heparin treatment, age, sex and K + , was associated with mortality among patients with COVID-19 and T2DM. With a 15% increase in RDW-SD, the risk of death increased by 87.7%. This preliminary study provides the foundations for developing further, more personalized models to assess the risk of death in T2DM patients, as well as for identifying patients at an increased risk of death due to COVID-19.
Conflicts of Interest: The authors declare no conflicts of interest. The Wald test was utilized in assessing the value of the factors to be included in the model. The score test (Lagrange multiplier test) was used to check if, at any step, the previously excluded factors should be re-included into the current model. The final model is described in Table 2 and visualized in Figure 3 .
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