Developing an HIV-specific falls risk prediction model with a novel clinical index : a systematic review and meta-analysis method

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dc.contributor.author Ibeneme, Sam C.
dc.contributor.author Odoh, Eunice
dc.contributor.author Martins, Nweke
dc.contributor.author Ibeneme, Georgian C.
dc.date.accessioned 2025-01-29T08:35:33Z
dc.date.available 2025-01-29T08:35:33Z
dc.date.issued 2024-12
dc.description DATA AVAILABITY STATEMENT: The datasets supporting the conclusions of this article are available in the institutional University of Nigeria repository and will be made easily available on request when required. All requests for the study data should be addressed to the first author via email: sam.ibeneme@unn.edu.ng. en_US
dc.description.abstract BACKGROUND: Falls are a common problem experienced by people living with HIV yet predictive models specific to this population remain underdeveloped. We aimed to identify, assess and stratify the predictive strength of various physiological, behavioral, and HIV-specific factors associated with falls among people living with HIV and inform a predictive model for fall prevention. METHODS: Systematic review and meta-analysis were conducted to explore predictors of falls in people living with HIV. Data was sourced, screened, extracted, and analyzed by two independent reviewers from eight databases up to January 2nd, 2024, following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol. Evidence quality and bias were assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) and the Mixed Method Appraisal Tool (MMAT), respectively. Pooled odds ratios (OR) with 95% confidence intervals (CI) were computed using random-effects models to establish associations between predictors and falls risk. We applied established criteria (Bradford Hill’s criteria, Rothman’s and Nweke’s viewpoints) to stratify risk factors and create a weighted predictive algorithm. RESULTS: This review included 12 studies on falls/balance dysfunction in 117,638 participants (54,513 people living with HIV), with varying ages (45–50 years), sample sizes (32−26,373), study durations (6 months to 15 years), disease stages (CD4+counts 347.2 cells/mm³ to ≥500 cells/µL) and fall definitions (self-reported histories to real-time reporting). Some predictors of falls in people living with HIV including depression, cannabis use, cognitive impairment/ neurocognitive adverse effects (NCAE), hypertension, and stavudine—showed perfect risk responsiveness (Ri=1), indicating their strong association with falls. Notably, cannabis use demonstrated the highest risk weight (Rw=3.0, p<0.05, 95%CI:1.51–5.82), followed by NCAE (Rw=2.3, p<0.05, 95%CI:1.66–3.21) and frailty with a broad confdence interval (Rw=2.2, p<0.05, 95%CI:0.73–14.40). Other significant predictors included hypertension (Rw=1.8, p<0.05, 95%CI:1.33–2.33), depression (Rw=1.6, p<0.05, 95%CI:1.22–2.18), stavudine use (Rw=1.5, p<0.05, 95%CI: 0.95–2.25), neuropathy (Rw=1.3, p<0.05, 95%CI:1.26–2.11), and polypharmacy (Rw=1.2, p<0.05, 95%CI:1.16–1.96). The fall risk threshold score was 12.8, representing the 76th percentile of the specific and sufficient risk weight. CONCLUSION: Our meta-analysis identifies predictors of falls in people living with HIV, emphasizing physiological, behavioral, and HIV-specific factors. Integrating these into clinical practice could mitigate falls-related sequelae. We propose a novel approach to falls risk prediction using a novel clinical index, resulting in a HIV-specific falls risk assessment tool. en_US
dc.description.department Physiotherapy en_US
dc.description.sdg SDG-03:Good heatlh and well-being en_US
dc.description.sdg SDG-10:Reduces inequalities en_US
dc.description.uri https://bmcinfectdis.biomedcentral.com/ en_US
dc.identifier.citation Ibeneme, S.C., Odoh, E., Martins, N. et al. Developing an HIV-specific falls risk prediction model with a novel clinical index: a systematic review and meta-analysis method. BMC Infectious Diseases 24, 1402 (2024). https://doi.org/10.1186/s12879-024-10141-5. en_US
dc.identifier.issn 1471-2334 (online)
dc.identifier.other 10.1186/s12879-024-10141-5
dc.identifier.uri http://hdl.handle.net/2263/100370
dc.language.iso en en_US
dc.publisher BioMed Central en_US
dc.rights © The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. en_US
dc.subject Falls predictive models en_US
dc.subject Physiological en_US
dc.subject Behavioral en_US
dc.subject HIV-specific fall risk factors en_US
dc.subject SDG-03: Good health and well-being en_US
dc.subject SDG-10: Reduced inequalities en_US
dc.subject Human immunodeficiency virus (HIV) en_US
dc.subject People living with HIV (PLHIV) en_US
dc.title Developing an HIV-specific falls risk prediction model with a novel clinical index : a systematic review and meta-analysis method en_US
dc.type Article en_US


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