Potential Effect of Hydroxychloroquine in Diabetes Mellitus: A Systematic Review on Preclinical and Clinical Trial Studies
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus is a chronic metabolic disorder characterized by persistent hyperglycemia. It affects millions of people globally. In spite of many antidiabetic drugs that are available, an adequate level of control remains challenging. Hydroxychloroquine is an immunomodulatory drug that has been used for the treatment of malaria and autoimmune diseases. There is an emerging evidence that suggests its beneficial effect against diabetes mellitus. Therefore, this systematic review is aimed at discoursing the role of hydroxychloroquine against diabetes mellitus and its potential mechanisms of actions. METHODS: A systematic and manual searching was carried out to retrieve relevant articles (preclinical and clinical studies) published from January 2014 to July 2019. Electronic databases including PubMed and Scopus as well as clinicaltrials.gov have been searched using different searching terms: "hydroxychloroquine," "diabetes mellitus," "hyperglycemia," and "insulin resistance." The MeSH terms (PubMed) and text words were combined with "AND" or "OR." In addition, manual searching of Google Engine and Google Scholar was conducted. Quality assessment of all the included studies was performed using CAMARADES (preclinical studies) and the Newcastle-Ottawa Scale and Cochrane Collaboration's tools (clinical studies). RESULTS: A total of eighteen studies (three experimental and fifteen clinical studies) were found to be eligible for the present systematic review. Among the included clinical studies (six randomized control trials, five observational studies, and four cohort studies), about 55,776 study participants were involved. Most of these studies showed significant improvement of lipid profile and insulin levels and substantial diminution of hemoglobin A1c, fasting plasma glucose, and postprandial blood glucose levels. Reduction in lysosomal degradation of the internal insulin-insulin receptor complex and enhancement in insulin sensitivity and adiponectin levels are some of the hypothesized mechanisms for the antidiabetic effect of hydroxychloroquine. CONCLUSION: The current review provides preliminary evidence for potential antidiabetic properties of hydroxychloroquine. Though the provided available data were promising, further clinical trials and mechanistic studies are needed to determine its long-term effects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".