Gap detection responses modelled using the Hill equation in adults with well-controlled HIV

Abstract

Objective

This study’s objective was determining whether gap detection deficits are present in a longstanding cohort of people living with HIV (PLWH) compared to those living without HIV (PLWOH) using a new gap detection modelling technique (i.e. fitting gap responses using the Hill equation and analysing the individual gap detection resulting curves with non-linear statistics). This approach provides a measure of both gap threshold and the steepness of the gap length/correct detection relationship.

Design

The relationship between the correct identification rate at each gap length was modelled using the Hill equation. Results were analysed using a nonlinear mixed-effect regression model.

Study sample

45 PLWH (age range 41–78) and 39 PLWOH (age range 38–79) were enrolled and completed gap detection testing.

Results

The likelihood ratio statistic comparing the full regression model with the HIV effects to the null model, assuming one population curve for both groups, was highly significant (p < 0.001), suggesting a less precise relationship between gap length and correct detection in PLWH.

Conclusions

PLWH showed degraded gap detection ability compared to PLWOH, likely due to central nervous system effects of HIV infection or treatment. The Hill equation provided a new approach for modelling gap detection ability.

Keywords:

• Gap detection
• HIV
• Hill equation
• non-linear modeling
• central auditory processing

Acknowledgements

The authors gratefully acknowledge the contributions of the Baltimore and Washington, DC, study participants and dedication of the staff at the MWCCS sites.

Author contribution

The authors have no financial or personal relationships that could inappropriately bias their work. Statement of author contribution: CEN performed data analysis, data interpretation and was primarily responsible for writing the manuscript; CC performed statistical analysis and developed the nonlinear mixed model approach; GG developed the idea of using the Hill equation to model gap detection responses; GS performed statistical analysis; AMF was involved in study design and training on auditory tests; PT was involved with study design and data analysis; HJH provided guidance on study design and assisted with data review; JCB was involved with study design, data analysis and manuscript preparation and MWP was involved with study design, overall study management and direction and data analysis. All authors contributed to the manuscript, assisted with revising the final work and approved the final version to be published. All authors agreed to be accountable for all aspects of the work and ensuring that questions about the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). MWCCS (principal investigators): Baltimore CRS (Todd Brown and Joseph Margolick), U01-HL146201; data analysis and coordination centre (Gypsyamber D’Souza, Stephen Gange and Elizabeth Golub), U01-HL146333; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01-HL146205. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute, with additional co-funding from the Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institute on Ageing, National Institute of Dental & Craniofacial Research, National Institute of Allergy and Infectious Diseases, National Institute of Neurological Disorders and Stroke, National Institute of Mental Health, National Institute on Drug Abuse, National Institute of Nursing Research, National Cancer Institute, National Institute on Alcohol Abuse and Alcoholism, National Institute on Deafness and Other Communication Disorders, National Institute of Diabetes and Digestive and Kidney Diseases and National Institute on Minority Health and Health Disparities, and in coordination and alignment with the research priorities of the National Institutes of Health, Office of AIDS Research. MWCCS data collection is also supported by grants UL1-TR000004 (UCSF CTSA), UL1-TR003098 (JHU ICTR), UL1-TR001881 (UCLA CTSI), P30-AI-050409 (Atlanta CFAR), P30-AI-073961 (Miami CFAR), P30-AI-050410 (UNC CFAR), P30-AI-027767 (UAB CFAR) and P30-MH-116867 (Miami CHARM).