Metformin in an HIV-Infected Patient with Protease Inhibitor—Induced Diabetic Ketoacidosis
Bibliographic record
Abstract
OBJECTIVE: To describe a case of diabetes mellitus and diabetic ketoacidosis in a patient receiving protease inhibitor therapy and to describe the patient's response to treatment with metformin. CASE SUMMARY: A 49-year-old HIV-positive white man who was receiving indinavir, stavudine, and lamivudine for more than two years presented with shortness of breath and significant weight loss over the previous month. On admission, he had a pH of 7.11 and PaCO2 of 12.9 mm Hg. Laboratory investigations revealed glucose 420 mg/dL, a total carbon dioxide 5 mEq/L, and anion gap of 32. Beta-hydroxybutyrate was 5.9 mmol/L (normal value <0.4 mmol/L). Urine was highly positive for glucose and ketones. The patient was given intravenous fluids and an insulin infusion was started. Five days later, he was discharged on 60 units of insulin per day. Following discharge, efavirenz was substituted for indinavir. Metformin was added and six months following discharge the patient's blood glucose was well controlled with 36 units of insulin per day. DISCUSSION: New-onset diabetes mellitus has been reported in HIV-infected patients receiving protease inhibitors. To date, diabetic ketoacidosis has been an infrequent acute complication. The mechanism by which protease inhibitors cause diabetes is unclear; however, studies have noted insulin resistance and increased proinsulin. Metformin increases the sensitivity of peripheral tissues to insulin and appeared to be useful in this patient. However, further clinical research is needed. CONCLUSIONS: Monitoring glucose concentrations in HIV-positive patients receiving protease inhibitors is important to prevent the development of acute complications, including diabetic ketoacidosis. We recommend that these patients have their fasting serum glucose concentration measured at baseline, with follow-up every three months. The role of metformin and the thiazolidinedione antidiabetic agents in the management of protease inhibitor-induced diabetes requires further study.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".