Diagnosis and Management of Common Chronic Metabolic Complications in HIV-infected Patients
Bibliographic record
Abstract
Human immunodeficiency virus (HIV) infection has become a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Metabolic complications such as dyslipidemia, insulin resistance, diabetes mellitus, obesity, and fat distribution abnormalities are associated with increased risk of cardiovascular disease. Cardiovascular disease is now a leading cause of death among HIV-infected patients. Lipid abnormalities, now often characteristically seen with HIV infection, include elevated triglycerides and low elevated total cholesterol (TC), and low high-density lipoprotein (HDL) levels of total and HDL cholesterol. Many antiretroviral drugs are associated with lipid abnormalities, which commonly include hypertriglyceridemia and increased total and low-density lipoprotein cholesterol levels. The management of dyslipidemia includes lifestyle modifications, lipid-lowering therapy, and switching antiretroviral therapy (ART). The increased prevalence of insulin resistance, impaired glucose tolerance, and diabetes is multifactorial in etiology. Management and goals of diabetes should follow the same practice guidelines in non-HIV-infected patients. Drug interactions and switching ART are additional management measures in diabetic HIV-infected patients. Since the treatment of lipodystrophy is a challenge, its prevention by selecting appropriate ART is the key.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".