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

dc.contributor.authorIbeneme, Sam C.
dc.contributor.authorOdoh, Eunice
dc.contributor.authorMartins, Nweke
dc.contributor.authorIbeneme, Georgian C.
dc.date.accessioned2025-01-29T08:35:33Z
dc.date.available2025-01-29T08:35:33Z
dc.date.issued2024-12
dc.descriptionDATA 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.abstractBACKGROUND: 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.departmentPhysiotherapyen_US
dc.description.sdgSDG-03:Good heatlh and well-beingen_US
dc.description.sdgSDG-10:Reduces inequalitiesen_US
dc.description.urihttps://bmcinfectdis.biomedcentral.com/en_US
dc.identifier.citationIbeneme, 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.issn1471-2334 (online)
dc.identifier.other10.1186/s12879-024-10141-5
dc.identifier.urihttp://hdl.handle.net/2263/100370
dc.language.isoenen_US
dc.publisherBioMed Centralen_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.subjectFalls predictive modelsen_US
dc.subjectPhysiologicalen_US
dc.subjectBehavioralen_US
dc.subjectHIV-specific fall risk factorsen_US
dc.subjectSDG-03: Good health and well-beingen_US
dc.subjectSDG-10: Reduced inequalitiesen_US
dc.subjectHuman immunodeficiency virus (HIV)en_US
dc.subjectPeople living with HIV (PLHIV)en_US
dc.titleDeveloping an HIV-specific falls risk prediction model with a novel clinical index : a systematic review and meta-analysis methoden_US
dc.typeArticleen_US

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