Bibliographic record
Abstract
Metformin (MTF) is one of the most common oral agents used to treat diabetes mellitus. Intoxication is associated with lactic acidosis and has significant clinical consequences. We report 12 cases requiring dialytic intervention. Twelve patients were analyzed from 2005 to 2010; 10 of these patients were treated with dialysis. Conventional hemodialysis (HD) and continuous veno-venous hemodialysis treatments with bicarbonate dialysis were used, and the results were presented as mean and standard deviation. The results are as follows: 33% of the patients were male, hospital stay was 9.3 (± 12) days, average MTF dose 1.7 g/day, mortality was 25%. Baseline glomerular filtration rate for these patients was 51.5 mL/min, with an average age of 64 (± 11) years. On presentation, all had acute kidney injury with blood urea nitrogen/creatinine 75 (± 30)/8.1 (± 3.7) mg/dL, lactic acid 12.4 (± 8.1) mmol/L, pH 7.04 (± 0.19), bicarbonate 7.2 (± 4.5) mmol/L. Metformin level was 25 (± 17) µg/mL; anion gap was 28 (± 9), and serum potassium was 5.4 (± 1.3) mEq/L. Seventy percent of patients were treated with conventional HD. Patients required 4 (± 5) dialysis treatments at blood flow QB 330 (± 53), dialysis flow QD 571 (± 111) for 305 (± 122) minutes. Postdialysis, the acidosis parameters improved: bicarbonate 19.2 (± 4.1) mmol/L, lactic acid 6 (± 4) mmol/L and MTF levels decreased 8.9 (± 5.7) µg/mL. Metformin percentage removal was calculated to be 60% (± 24). No difference was found between HD and continous veno-venous hemodialysis. The only difference between survivors was the age 53 (± 7) vs. 78 (± 10) (P < 0.05). Metformin toxicity is a serious clinical condition and causes severe lactic acidosis and significant mortality. Hemodialysis is an efficient method to treat MTF intoxication and correct the metabolic abnormalities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".