Non-Severe Hypoglycemia Risk Difference Between Sulfonylurea and Sodium-Glucose Cotransporter-2 Inhibitors (Sglt2-I) as an Add-On to Metformin in Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Non-severe hypoglycemia reduces well-being, lowers quality of life, reduces productivity and increases treatment costs. The non-severe hypoglycemia rate, attributable to sulfonylurea (SU) utilization compared with newer classes such as SGLT2-I, could be of clinical significance. OBJECTIVES: To explore the non-severe hypoglycemia risk difference (RD) for SU use compared with SGLT2-I in randomized controlled trials (RCTs) as an add on to metformin. METHODS: A search was conducted for RCTs of SGLT2-I. PubMed database were utilized for this search. The search was limited to RCTs reported in English language for canagliflozin, dapagliflozin, and empagliflozin. SU dose comparison was utilized to convert the dose of SUs to glimepiride equivalent doses. RESULTS: Totally, 118 RCTs were reviewed; 6 articles had an arm for a SU as add on to metformin. Six articles belong to 3 RCTs, which reported results for 52 weeks and 104 weeks. Average non-severe hypoglycemia rate for SU arm was 30% (5.5%) [Mean (SD)] for 52 weeks and 35.6% (6.1%) for 104 weeks. RD for non-severe hypoglycemia events for SU compared to SGLT2-I was 26.7% (4.9%) for 52 weeks (p-value less than 0.001) and 30.6% (5.5%) for 104 weeks (p-value less than 0.001). There was a significant correlation between dose of SU and hypoglycemia rate (Pearson correlation 0.995; R-square 99%). CONCLUSIONS: This study illustrated that a large proportion of patients who had exposure to SU in RCTs of SGLT2-I experienced non-severe hypoglycemia compared to SGLT2-I. There was a close relation between SU dose and increased probability of non-severe hypoglycemia events.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".