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HIV and Premature Aging: A Field Still in Its Infancy

2010· letter· en· W2029012724 on OpenAlexaboutno aff
Jeffrey N. Martin, Paul A. Volberding

Bibliographic record

VenueAnnals of Internal Medicine · 2010
Typeletter
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVeterans AffairsLife expectancyGerontologyAntiretroviral therapyCohortHuman immunodeficiency virus (HIV)PediatricsInternal medicineFamily medicinePopulationViral load

Abstract

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Editorials5 October 2010HIV and Premature Aging: A Field Still in Its InfancyJeffrey Martin, MD, MPH and Paul Volberding, MDJeffrey Martin, MD, MPHFrom University of California San Francisco, San Francisco, CA 94107; and University of California San Francisco and Veterans Affairs Medical Center, San Francisco, CA 94121.Search for more papers by this author and Paul Volberding, MDFrom University of California San Francisco, San Francisco, CA 94107; and University of California San Francisco and Veterans Affairs Medical Center, San Francisco, CA 94121.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-153-7-201010050-00013 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Potent antiretroviral therapy has changed the world for most patients with HIV infection, their clinicians, and researchers. Where therapy is available, most patients experience a successful virologic and immunologic response and avoid the opportunistic infections that initially defined the epidemic. However, antiretroviral therapy cannot be considered an unqualified success. In particular, data from treated populations show that lifespan remains shorter compared with uninfected persons, and this diminished lifespan cannot be obviously attributed to any single complication (1, 2). Instead, a growing number of comorbid conditions seem to be more common in HIV-infected patients, and they often occur at younger ages ...References1. Lohse N, Hansen AB, Pedersen G, Kronborg G, Gerstoft J, Sørensen HT, et al. Survival of persons with and without HIV infection in Denmark, 1995-2005. Ann Intern Med. 2007;146:87-95. [PMID: 17227932] LinkGoogle Scholar2. Antiretroviral Therapy Cohort Collaboration. Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies. Lancet. 2008;372:293-9. [PMID: 18657708] CrossrefMedlineGoogle Scholar3. Desquilbet L, Jacobson LP, Fried LP, Phair JP, Jamieson BD, Holloway M, et al; Multicenter AIDS Cohort Study. HIV-1 infection is associated with an earlier occurrence of a phenotype related to frailty. J Gerontol A Biol Sci Med Sci. 2007;62:1279-86. [PMID: 18000149] CrossrefMedlineGoogle Scholar4. McCutchan JA, Wu JW, Robertson K, Koletar SL, Ellis RJ, Cohn S, et al. HIV suppression by HAART preserves cognitive function in advanced, immune-reconstituted AIDS patients. AIDS. 2007;21:1109-17. [PMID: 17502721] CrossrefMedlineGoogle Scholar5. Odden MC, Scherzer R, Bacchetti P, Szczech LA, Sidney S, Grunfeld C, et al. Cystatin C level as a marker of kidney function in human immunodeficiency virus infection: the FRAM study. Arch Intern Med. 2007;167:2213-9. [PMID: 17998494] CrossrefMedlineGoogle Scholar6. Grinspoon SK, Grunfeld C, Kotler DP, Currier JS, Lundgren JD, Dubé MP, et al. State of the science conference: Initiative to decrease cardiovascular risk and increase quality of care for patients living with HIV/AIDS: executive summary. Circulation. 2008;118:198-210. [PMID: 18566320] CrossrefMedlineGoogle Scholar7. Triant VA, Brown TT, Lee H, Grinspoon SK. Fracture prevalence among human immunodeficiency virus (HIV)-infected versus non-HIV-infected patients in a large U.S. healthcare system. J Clin Endocrinol Metab. 2008;93:3499-504. [PMID: 18593764] CrossrefMedlineGoogle Scholar8. Bhavan KP, Kampalath VN, Overton ET. The aging of the HIV epidemic. Curr HIV/AIDS Rep. 2008;5:150-8. [PMID: 18627664] CrossrefMedlineGoogle Scholar9. Effros RB, Fletcher CV, Gebo K, Halter JB, Hazzard WR, Horne FM, et al. Aging and infectious diseases: workshop on HIV infection and aging: what is known and future research directions. Clin Infect Dis. 2008;47:542-53. [PMID: 18627268] CrossrefMedlineGoogle Scholar10. Deeks SG, Phillips AN. HIV infection, antiretroviral treatment, ageing, and non-AIDS related morbidity. BMJ. 2009;338:a3172. [PMID: 19171560] CrossrefMedlineGoogle Scholar11. Shiels MS, Pfeiffer RM, Engels EA. Age at cancer diagnosis among persons with AIDS in the United States. Ann Intern Med. 2010;153:452-60. LinkGoogle Scholar12. Demopoulos BP, Vamvakas E, Ehrlich JE, Demopoulos R. Non-acquired immunodeficiency syndrome-defining malignancies in patients infected with human immunodeficiency virus. Arch Pathol Lab Med. 2003;127:589-92. CrossrefMedlineGoogle Scholar13. Bräu N, Fox RK, Xiao P, Marks K, Naqvi Z, Taylor LE, et al; North American Liver Cancer in HIV Study Group. Presentation and outcome of hepatocellular carcinoma in HIV-infected patients: a U.S.-Canadian multicenter study. J Hepatol. 2007;47:527-37. CrossrefMedlineGoogle Scholar14. Brock MV, Hooker CM, Engels EA, Moore RD, Gillison ML, Alberg AJ, et al. Delayed diagnosis and elevated mortality in an urban population with HIV and lung cancer: implications for patient care. J Acquir Immune Defic Syndr. 2006;43:47-55. [PMID: 16936558] CrossrefMedlineGoogle Scholar15. Crum-Cianflone NF, Hullsiek KH, Marconi VC, Ganesan A, Weintrob A, Barthel RV, et al; Infectious Disease Clinical Research Program HIV Working Group. Anal cancers among HIV-infected persons: HAART is not slowing rising incidence. AIDS. 2010;24:535-43. [PMID: 19926961] CrossrefMedlineGoogle Scholar16. Frisch M, Biggar RJ, Engels EA, Goedert JJ; AIDS-Cancer Match Registry Study Group. Association of cancer with AIDS-related immunosuppression in adults. JAMA. 2001;285:1736-45. [PMID: 11277828] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAuthors: Jeffrey Martin, MD, MPH; Paul Volberding, MDAffiliations: From University of California San Francisco, San Francisco, CA 94107; and University of California San Francisco and Veterans Affairs Medical Center, San Francisco, CA 94121.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M10-2011.Corresponding Author: Paul Volberding, MD, 4150 Clement Street, San Francisco, CA 94121; e-mail, paul.volberding@va.gov.Current Author Addresses: Dr. Martin: University of California, San Francisco, 185 Berry Street, Suite 5700, San Francisco, CA 94107.Dr. Volberding: 4150 Clement Street, San Francisco, CA 94121. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoAge at Cancer Diagnosis Among Persons With AIDS in the United States Meredith S. Shiels , Ruth M. Pfeiffer , and Eric A. Engels Age at Cancer Diagnosis Among Persons With AIDS Meredith S. Shiels , Ruth M. Pfeiffer , and Eric A. Engels Metrics Cited byHIV, pathology and epigenetic age acceleration in different human tissuesAktywność spoczynkowa mózgu a funkcje neuropsychologiczne osób zakażonych HIVCurrent Challenges and Solutions in Research and Clinical Care of Older Persons Living with HIV: Findings Presented at the 9th International Workshop on HIV and AgingChronicity, crisis, and the ‘end of AIDS’HIV and Age Do Not Synergistically Affect Age-Related T-Cell MarkersHuman Immunodeficiency Virus and Aging in the Era of Effective Antiretroviral TherapyGeriatric syndromesGenetic, Epigenetic, and Transcriptomic Studies of NeuroAIDSJak starzeje się mózg w infekcji HIV: doniesienia z badań nad spoczynkową aktywnością mózgu metodą czynnościowego rezonansu magnetycznegoHIV and AgingAccelerated epigenetic aging in brain is associated with pre-mortem HIV-associated neurocognitive disordersSerum total estradiol, but not testosterone is associated with reduced bone mineral density (BMD) in HIV-infected men: a cross-sectional, observational studyRegulatory T Cells, Frailty, and Immune Activation in Men Who Have Sex With Men in the Multicenter AIDS Cohort StudyAccelerated Longitudinal Gait Speed Decline in HIV-Infected Older MenHIV-1 Infection Accelerates Age According to the Epigenetic ClockEditorial Commentary: Age-Old Questions: When to Start Antiretroviral Therapy and in Whom?: Figure 1.Accelerating aging research: How can we measure the rate of biologic aging?Understanding Frailty, Aging, and Inflammation in HIV InfectionLow testosterone is associated with poor health status in men with human immunodeficiency virus infection: a retrospective studyComparison of Risk and Age at Diagnosis of Myocardial Infarction, End-Stage Renal Disease, and Non-AIDS-Defining Cancer in HIV-Infected Versus Uninfected AdultsReduced neural specificity in middle-aged HIV+ women in the absence of behavioral deficitsHIV: A Chronic ConditionCross-sectional Comparison of the Prevalence of Age-Associated Comorbidities and Their Risk Factors Between HIV-Infected and Uninfected Individuals: The AGEhIV Cohort StudyIs HIV a Model of Accelerated or Accentuated Aging?HIV and agingMultimorbidity and functional status assessmentMale sexual dysfunction and HIV—a clinical perspectiveAge, Comorbidities, and AIDS Predict a Frailty Phenotype in Men Who Have Sex With MenManifestaciones reumatológicas de la infección por el virus de la inmunodeficiencia humanaAccelerated biological ageing in HIV-infected individuals in South AfricaIncreased Ocular Lens Density in HIV-Infected Individuals With Low Nadir CD4 Counts in South AfricaFrailty as a Novel Predictor of Mortality and Hospitalization in Individuals of All Ages Undergoing HemodialysisHIV, Age, and the Severity of Hepatitis C Virus–Related Liver Disease A Cohort StudyGregory D. Kirk, MD, MPH, PhD, Shruti H. Mehta, PhD, MPH, Jacquie Astemborski, MS, Noya Galai, PhD, Jonathan Washington, BA, Yvonne Higgins, PA, Ashwin Balagopal, MD, and David L. Thomas, MD, MPHPrediction of Health Preference Values from CD4 Counts in Individuals with HIVCorneal Endothelial Cells Provide Evidence of Accelerated Cellular Senescence Associated with HIV Infection: A Case-Control StudyFrailty in HIV-Infected Adults in South AfricaIncidence of HIV-Related Anal Cancer Remains Increased Despite Long-Term Combined Antiretroviral Treatment: Results From the French Hospital Database on HIVRetinal Arterioles Narrow with Increasing Duration of Anti-Retroviral Therapy in HIV Infection: A Novel Estimator of Vascular Risk in HIV?HIV Infection and Older Americans: The Public Health PerspectiveImpact of Antiretroviral Therapy on Tuberculosis Incidence Among HIV-Positive Patients in High-Income CountriesThe Frequency of Low Muscle Mass and Its Overlap With Low Bone Mineral Density and Lipodystrophy in Individuals With HIV—A Pilot Study Using DXA Total Body Composition AnalysisHIV and ageingEmotional Impact of Premature Aging Symptoms in Long-Term Treated HIV-Infected SubjectsPremature Decline of Serum Total Testosterone in HIV-Infected Men in the HAART-EraThe impact of HIV research on health outcome and healthcare policyThe spectrum of malignancies in HIV-infected patients in 2006 in France: The ONCOVIH studySexual Dysfunction, HIV, and AIDS in Men Who Have Sex with MenAge at Cancer Diagnosis Among Persons With AIDSCharlotte Sakarovitch, PhD and Eric Fontas, MD, PhDAge at Cancer Diagnosis Among Persons With AIDSMeredith S. Shiels, PhD, MHS, Ruth M. Pfeiffer, PhD, and Eric A. Engels, MD, MPHAssessment of Kidney Safety Parameters Among Hiv-Infected Patients Starting a Tenofovir-Containing Antiretroviral Therapy 5 October 2010Volume 153, Issue 7Page: 477-479KeywordsAgingAIDSCancer risk factorsEpidemiologyHIVHIV infectionsLiverLung and intrathoracic tumorsMedical risk factorsPopulation statistics ePublished: 5 October 2010 Issue Published: 5 October 2010 PDF downloadLoading ...

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0030.001
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0150.008

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.

Opus teacher head0.039
GPT teacher head0.374
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations73
Published2010
Admission routes1
Has abstractyes

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