Risk evaluation of metformin use in patients with kidney injury.
Bibliographic record
Abstract
Background: In a world where the prevalence of Diabetes is ever increasing metformin plays an important role in the management of the disease. The most feared adverse effect of metformin is lactic acidosis, a rare situation that has a poor prognosis. This study aims to report the cases of metformin associated lactic acidosis (MALA) in Centro Hospitalar Universitário de São João (CHUSJ) evaluated by the Nephrology department. Methods: All cases of MALA in diabetic patients admitted to our tertiary center that had an evaluation by the nephrology department from the year of 2017 until 2019 were included. Data referring to clinical status, blood analysis, evolution and outcome were retrospectively analyzed. Results: We identified 10 patients with MALA and verified only 1 death, which wasn't directly attributable to this condition. At admission patients presented with arterial blood pH of 7.07 ± 0.14 and plasma lactate of 9.67 ± 4.09. There was no significant association between days of hospitalization and either pH, plasma creatinine or lactate at admission. Conclusion: MALA diagnostic and metformin's association with lactic acidosis remains not completely clarified. Our study shows lower mortality than what has been previously published. To date, no reliable predictor of mortality has been identified. More studies are needed to evaluate the usefulness of determining metformin concentrations and to assess the true influence of the drug in the development of lactic acidosis.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".