Transient Blindness in Metformin-associated Lactic Acidosis: Resolution With Supportive Care
Abstract
Metformin remains the first-line pharmacologic treatment for type 2 diabetes mellitus due to its well-established efficacy and safety profile. However, a rare but serious complication is metformin-associated lactic acidosis (MALA), which carries a mortality rate of up to 36.2% in hospitalized patients. Those with chronic kidney disease and cardiovascular comorbidities are particularly vulnerable to severe outcomes. Among the rare manifestations of MALA is complete bilateral blindness, which typically requires urgent hemodialysis for reversal. Here, we present a case of MALA-induced blindness that was unexpectedly reversed through supportive medical management alone, prior to hemodialysis. This case underscores the critical role of early recognition and intervention by intensive care physicians in optimizing MALA outcomes. Further studies are warranted to elucidate the effects of MALA on the visual pathways, particularly the susceptibility of retinal cells and photoreceptors to metformin toxicities.
How strong is the evidence?
Evidence Hub reads this as a case report, done in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- Metformin as an adjuvant in breast cancer treatment
- Metformin Lysosomal Targeting: A Novel Aspect to Be Investigated for Metformin Repurposing in Neurodegenerative Diseases?
- Aberrant HSF1 signaling activation underlies metformin amelioration of myocardial infarction in mice
- Metformin induces ZFP36 by mTORC1 inhibition in cervical cancer-derived cell lines
- Protein Interaction Network for Identifying Vascular Response of Metformin (Oral Antidiabetic)
- Preventing Long COVID With Metformin
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.