The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Incidence and Risk Factors for New-Onset Diabetes in HIV-Infected Patients
Open accessAbstract
OBJECTIVE—The aims of this study were to determine the incidence of diabetes among HIV-infected patients in the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) cohort, to identify demographic, HIV-related, and combination antiretroviral therapy (cART)-related factors associated with the onset of diabetes, and to identify possible mechanisms for any relationships found. RESEARCH DESIGN AND METHODS—D:A:D is a prospective observational study of 33,389 HIV-infected patients; diabetes is a study end point. Poisson regression models were used to assess the relation between diabetes and exposure to cART after adjusting for known risk factors for diabetes, CD4 count, lipids, and lipodystrophy. RESULTS—Over 130,151 person-years of follow-up (PYFU), diabetes was diagnosed in 744 patients (incidence rate of 5.72 per 1,000 PYFU [95% CI 5.31–6.13]). The incidence of diabetes increased with cumulative exposure to cART, an association that remained significant after adjustment for potential risk factors for diabetes. The strongest relationship with diabetes was exposure to stavudine; exposures to zidovudine and didanosine were also associated with an increased risk of diabetes. Time-updated measurements of total cholesterol, HDL cholesterol, and triglycerides were all associated with diabetes. Adjusting for each of these variables separately reduced the relationship between cART and diabetes slightly. Although lipodystrophy was significantly associated with diabetes, adjustment for this did not modify the relationship between cART and diabetes. CONCLUSION—Stavudine and zidovudine are significantly associated with diabetes after adjustment for risk factors for diabetes and lipids. Adjustment for lipodystrophy did not modify the relationship, suggesting that the two thymidine analogs probably directly contribute to insulin resistance, potentially through mitochondrial toxicity.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Stamler, J., Vaccaro, O., Neaton, J. D., Wentworth, D., & The Multiple Risk Factor Intervention Trial Research Group (1993) · Diabetes Care · doi:10.2337/diacare.16.2.434 · Cited by 4,063
Impaired Mitochondrial Activity in the Insulin-Resistant Offspring of Patients with Type 2 Diabetes
Petersen, K. F., Dufour, S., Befroy, D., Garcia, R., & Shulman, G. I. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa031314 · Cited by 2,193
The U.K. Prospective Diabetes Study. A review
Turner, R. C. (1998) · Diabetes Care · doi:10.2337/diacare.21.3.c35 · Cited by 267
Fleischman, A., Johnsen, S., Systrom, D. M., Hrovat, M., Farrar, C. T., Frontera, W., Fitch, K., Thomas, B. J., Torriani, M., Côté, H. C. F., et al. (2007) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00550.2006 · Cited by 160
Cited by
Insulin resistance: review of the underlying molecular mechanisms
Yaribeygi, H., Farrokhi, F. R., Butler, A. E., & Sahebkar, A. (2019) · Journal of Cellular Physiology · doi:10.1002/jcp.27603 · Cited by 929
Williams, E. C., Hahn, J. A., Saitz, R., Bryant, K., Lira, M. C., & Samet, J. H. (2016) · Alcoholism: Clinical and Experimental Research · doi:10.1111/acer.13204 · Cited by 294
HIV infection and cardiovascular disease
Hemkens, L. G., & Bucher, H. C. (2014) · European Heart Journal · doi:10.1093/eurheartj/eht528 · Cited by 251
Hernandez-Romieu, A. C., Garg, S., Rosenberg, E. S., Thompson-Paul, A. M., & Skarbinski, J. (2017) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2016-000304 · Cited by 213
Obesity and weight gain in persons with HIV
Bailin, S. S., Gabriel, C. L., Wanjalla, C. N., & Koethe, J. R. (2020) · Current HIV/AIDS Reports · doi:10.1007/s11904-020-00483-5 · Cited by 213
Metadata
- Authors
- De Wit, S., Sabin, C. A., Weber, R., Worm, S. W., Reiss, P., Cazanave, C., El-Sadr, W., Monforte, A. D., Fontas, E., Law, M. G., Friis-Møller, N., & Phillips, A.
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2008-06-01
- Volume
- 31
- Issue
- 6
- Pages
- 1224-1229
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- OpenAlex
- W2110717475
- Cited by
- 482
- References
- 5
- FWCI
- 33.79
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Incidence and Risk Factors for New-Onset Diabetes in HIV-Infected Patients. https://app.cochat.ai/papers/10.2337/dc07-2013
- The paper
- De Wit, S., Sabin, C. A., Weber, R., Worm, S. W., Reiss, P., Cazanave, C., El-Sadr, W., Monforte, A. D., Fontas, E., Law, M. G., Friis-Møller, N., & Phillips, A. (2008). Incidence and Risk Factors for New-Onset Diabetes in HIV-Infected Patients. Diabetes Care. https://doi.org/10.2337/dc07-2013
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.