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Record W4242761144 · doi:10.1097/qai.0b013e318157b0f0

Author's Response to “Persistence of Neuropsychologic Deficits Despite Long-Term Highly Active Antiretroviral Therapy in Patients With HIV-Related Neurocognitive Impairment”

2007· article· en· W4242761144 on OpenAlexfundno aff
Valerio Tozzi, Pietro Balestra, Chrysoula Vlassi, Maria Flora Salvatori

Bibliographic record

VenueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2007
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsnot available
FundersCanadian Foundation for AIDS Research
KeywordsNeurocognitiveMedicineSerologyCohortInternal medicineHepatitis CImmunologyPediatricsPsychiatryCognitionAntibody

Abstract

fetched live from OpenAlex

In Reply: This letter is in response to Dr. Garvey and colleagues' concerns regarding our article,1 in which we describe prevalence and risk factors for persistent neuropsychologic (NP) deficits despite long-term highly active antiretroviral therapy (HAART) in a cohort of 94 patients with HIV-related neurocognitive impairment (NCI) treated with potent antiretroviral therapy. We found, at univariate analyses, an association of persistent NP deficits with positive hepatitis C virus (HCV) serology. However, this difference was no longer significant at Cox model. Dr. Garvey and colleagues' concern was that we could have underestimated the potential role of HCV in contributing to the persistence of NP deficits. The association of positive HCV serology with cognitive impairment in HIV-infected patients has been well documented in the literature. HCV, as well as HIV, has been associated with significant deficits in sustained attention and psychomotor speed.2,3 HCV in association with HIV may lead to more profound neurocognitive impairment than either virus alone.4,5 Given the high prevalence of patients with positive HCV serology in our cohort, Dr. Garvey and colleagues correctly ask for detailed information on serum HCV RNA levels, liver function tests, and HCV therapy in the patients studied. Among the 43 patients with positive HCV serology, the prevalence of patients with abnormal liver enzymes did not differ between patients with persistent and reversible NP deficits. Four patients had evidence of cirrhosis at liver biopsy. Moreover, 5 patients received pegylated interferon plus ribavirin during the study, and 2 of them cleared HCV. However, no conclusion was possible with this limited set of patients. Twenty-nine patients had detectable plasma HCV RNA. Notably, we found that 24 of 59 (40.7%) patients with persistent NP deficits were HCV RNA positive, compared to 5 of 35 (14.3%) patients with reversible NP deficits. This difference was statistically significant (P = 0.014). However, after including the HCV RNA results (either detectable or not detectable) in the multivariable model, this difference did not remain independently associated with persistent NP deficits (odds ratio [OR] = 0.9; 95% confidence interval [CI]: 0.4 to 2.8). Although the results of the multivariable model seem to preclude the involvement of HCV in persistent NP deficits, we agree that further studies on this topic are needed. Our study was not aimed to assess the contribution of HCV infection on changes in NP performance over time. To our knowledge, whether HCV-coinfected patients during HAART might respond neurocognitively worse than patients infected solely with HIV is unknown. We agree that studies on this topic are needed, and we appreciate Dr. Garvey and colleagues' insights. Valerio Tozzi, MD Pietro Balestra, PsyD Chrysoula Vlassi, MD Maria Flora Salvatori, DSc National Institute for Infectious Diseases Rome, Italy

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)0.003
metaresearch head score (Gemma)0.028
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: Commentary
Teacher disagreement score0.019
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0190.017
Insufficient payload (model declined to judge)0.0080.006

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 head0.018
GPT teacher head0.277
Teacher spread0.260 · 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".

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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