Search Results (5,625)

Alkaline water is increasingly marketed for musculoskeletal and recovery benefits, yet its relevance to healthy aging, sarcopenia prevention, and functional capacity in older adults remains largely unexplored. This systematic evidence map and translational appraisal examined whether the available comparative human evidence on alkaline water is applicable to aging populations and longevity research. Following PRISMA guidance, PubMed and Scopus were searched from January 2005 to September 2025. Eligible studies were controlled or comparative observational human studies reporting muscle strength, physical performance, or recovery outcomes. Risk of bias was assessed using RoB 2, ROBINS-I, and JBI criteria; evidence certainty was judged narratively using GRADE-informed principles. Ten studies met the inclusion criteria. Most enrolled young athletic populations; only two had partial relevance to aging cohorts. Crucially, no study included participants aged 65 years or older or assessed primary sarcopenia-relevant endpoints such as appendicular lean mass, gait speed, or chair-rise performance; this total absence of data in the target demographic represents the central limitation of the current literature. Risk of bias ranged from some concerns to serious. The most consistent signals were short-term improvements in lactate clearance and perceived exertion in young male athletes. Evidence for strength, functional performance, and safety in older adults was absent or indirect. Current evidence, rated low to very low certainty for aging-relevant outcomes, does not support alkaline water as an evidence-based strategy for healthy aging or muscle preservation in older adults. Age-appropriate trials using EWGSOP2-aligned outcomes are urgently needed. Full article

The emerging potential of low-Earth-orbit (LEO) satellite-based Positioning, Navigation, and Timing services has increased the need for real-time, stable, and accurate orbit determination techniques. Here, we propose a method for estimating sub-meter-level LEO satellite orbits using Global Navigation Satellite System (GNSS) code pseudorange observations. To mitigate ionospheric delay, a dual-frequency ionosphere-free combination was applied, while code-carrier smoothing was employed to reduce code observation noise. A satellite weighting model based on Signal-in-Space Range Error was developed to reflect the orbit and clock error characteristics of different GNSS, and a robust weighting scheme was applied to alleviate the impact of observation outliers. Further, Galileo High Accuracy Service corrections compensated for orbit, clock and code bias errors. The algorithm was validated using the GNSS observation data collected from the Sentinel-6A satellite on 10 August 2023. Each successively applied technique gradually improved orbit determination accuracy, achieving up to a 51% reduction in 3D root mean square error (RMSE). The final RMSE values in the radial, along-track, cross-track, and 3D components were 39.4, 18.8, 23.5, and 49.6 cm, respectively. Temporal analysis showed no distinct periodicity in orbit errors and no significant correlation with satellite visibility or ground track. Full article

Background: Polyendocrine metabolic ovarian syndrome (PMOS/PCOS) is the most common hormonal disorder in women of reproductive age and is linked to infertility as well as long-term metabolic and psychological problems. In the Gulf Cooperation Council (GCC) region, rising obesity, dietary changes, and sedentary lifestyles may be increasing its burden. However, prevalence estimates remain highly inconsistent due to differences in diagnostic criteria and measurement methods rather than true variation in disease rates. Objective: This study aimed to describe the situation by systematically pooling available evidence on the prevalence of PMOS among women in GCC countries and by summarizing the range of clinical features reported across included studies. Methods: We conducted a systematic review and meta-analysis following PRISMA 2020 guidelines. We searched five major bibliographic databases (PubMed, Scopus, Web of Science, Cochrane Library, and Embase) and the Google Scholar search engine for observational studies published up to 1 June 2026. Studies were eligible if they reported PMOS prevalence and related clinical features among women of reproductive age residing in GCC countries. After removing duplicates and screening 570 initially identified records, 25 studies met our inclusion criteria; 24 were included in the quantitative meta-analysis after excluding one high-risk study. Risk of bias was appraised using the Joanna Briggs Institute Checklist for Prevalence Studies. A random-effects meta-analysis using the DerSimonian-Laird method, combined with the Freeman-Tukey double arcsine transformation, was used to estimate the pooled prevalence. Heterogeneity was quantified using the I² statistic and Cochran’s Q test. Subgroup analyses explored differences by country, diagnostic method, study setting, and publication period. Meta-regression was used to identify study-level factors that explained between-study variability. Results: Across 24 studies involving 77,890 women, the pooled prevalence of PMOS was 17.59% (95% CI: 12.98–23.40%). Country-level estimates ranged from 6.56% in Oman to 23.0% in Saudi Arabia. Heterogeneity across all analyses was extremely high (I² = 99.6%), and meta-regression identified the diagnostic tool as the single most important source of variation, explaining 42.7% of between-study variance. Studies using structured clinical criteria (Rotterdam or NIH) yielded prevalence estimates around 13–14%, while those relying on self-report or physician diagnosis without standardized criteria reported considerably higher figures (20–37%). Common clinical features included menstrual irregularity (up to 100% of PMOS cases in clinical cohorts), hirsutism (5–100%), acne and oily skin (17–74%), and obesity (17–73%). Awareness of PMOS among women in the region was highly variable, ranging from under 3% to nearly 100%. Conclusions: PMOS is a significant public health concern across the GCC region. The markedly higher pooled prevalence combined with high rates of obesity and metabolic risk in this population calls for urgent, coordinated action. Standardizing diagnostic practices, investing in population-level screening, and developing culturally tailored awareness programs are essential steps toward reducing the clinical and social burden of PMOS. Full article

Background/Objectives: Rehospitalization after traumatic spinal cord injury (SCI) is common, but binary or count summaries may obscure heterogeneity in timing, recurrence, frequency, and duration. We aimed to identify clinically interpretable rehospitalization burden profiles in the SCIMS 2021ARPublic dataset and examine descriptive associations with clinical correlates and participation outcomes. Methods: We analyzed Form I, Form II, and Record Status public-use files. Among 29,310 individuals with at least one non-lost follow-up interview, 28,745 with at least one non-missing rehospitalization indicator entered latent class analysis. Four prespecified indicators captured early, recurrent, frequent, and prolonged rehospitalization. Candidate two- through six-class models were compared using AIC, BIC, entropy, class size, posterior probabilities, and interpretability. Pairwise adjusted logistic models examined candidate clinical correlates in 10,407 participants with complete 2016+ follow-up data. Adjusted linear models examined CHART participation domains in 20,766–20,949 participants. Results: A four-profile solution was retained: low rehospitalization burden (59.8%), early/prolonged rehospitalization (18.9%), frequent/prolonged rehospitalization (7.7%), and high recurrent/frequent/prolonged burden (13.6%). UTI and pressure ulcer history showed the most consistent associations with burdened profiles. Severe pain and frequent sleep problems were associated with selected heavier-burden profiles, while depressive symptoms showed smaller and less precise associations. Sensitivity analyses supported structural stability while highlighting observation-time bias and classification uncertainty inherent to wave-based public-use data. Compared with the low-burden profile, burden profiles showed lower CHART scores, especially for mobility and occupation. Conclusions: Rehospitalization after traumatic SCI is heterogeneous. These utilization burden profiles summarize distinct observed patterns but require prospective validation before use in risk stratification or follow-up planning. Full article

Walking is not merely locomotion but a window into the nervous system, integrating cortical, subcortical, cerebellar, spinal, and peripheral networks into a unified motor behavior. Across neurological diseases—including Parkinson’s disease, atypical parkinsonism, cerebellar ataxias, stroke, multiple sclerosis, neuropathies, neuromuscular disorders, and functional gait syndromes—gait disturbances are among the most disabling clinical features, contributing to falls, loss of independence, institutionalization, and premature mortality. Traditional bedside observation remains indispensable, but it lacks the sensitivity and reproducibility needed to capture subtle, episodic, or prodromal abnormalities. Over the past decade, advances in wearable sensors, marker-based and markerless motion capture, pressure-sensitive walkways, force plates, artificial intelligence, and machine learning have positioned digital mobility outcomes as promising, ecologically valid biomarkers of neurological function. These measures can support differential diagnosis, provide prognostic information on falls and survival, and serve as sensitive endpoints in therapeutic trials. They may also detect early abnormalities, such as increased stride-to-stride variability or prolonged double-support time, before overt clinical deterioration becomes evident. Clinical applications are increasingly evident across disorders, including distinguishing Parkinson’s disease from atypical parkinsonism, quantifying treatment response in normal-pressure hydrocephalus, tracking progression in ataxia and multiple sclerosis, predicting functional decline in motor neuron disease, and guiding rehabilitation after stroke. Integration with neuroimaging, electrophysiology, and molecular biomarkers is beginning to reveal the circuits underlying variability, instability, and freezing, positioning gait as a systems-level marker of neural integrity. Nevertheless, methodological heterogeneity, limited disease-specific validation, insufficient longitudinal data, and lack of consensus on clinically meaningful parameters continue to constrain translation. Cognitive, affective, and environmental influences also remain insufficiently represented in digital frameworks, while equity, accessibility, algorithmic bias, and privacy require careful ethical governance. Reconceptualizing gait as a “sixth vital sign” reframes mobility as a multidimensional biomarker of neural and systemic health. With harmonized protocols, robust validation, multimodal integration, and appropriate ethical frameworks, gait analysis could become a cornerstone of precision neurology. Full article

Background: Physical activity is a well-established modifiable lifestyle factor associated with reduced cancer risk; however, the optimal weekly volume of moderate-to-vigorous physical activity (MVPA) for cancer prevention, particularly when assessed using objective measures, remains unclear. Most existing evidence relies on self-reported physical activity, which may introduce measurement bias and obscure accurate dose–response relationships. Methods: We analyzed data from UK Biobank participants with valid accelerometer measurements to quantify habitual MVPA. Observational associations between MVPA and incident cancer were evaluated using multivariable Cox proportional hazards regression and restricted cubic splines. One-sample Mendelian randomization (MR) analyses, including both linear and nonlinear approaches, were conducted to evaluate potential causal associations and explore possible dose–response patterns. Results: Higher MVPA was associated with lower total cancer risk (HR 0.971, 95% CI 0.954–0.988, p = 0.001). Consistent associations were observed for several site-specific cancers, particularly lung, colorectal, breast, kidney, and bladder cancer. MR analyses supported a directionally consistent association between genetically predicted MVPA and lower total cancer risk (HR 0.977, 95% CI 0.962–0.992, p = 0.002). Nonlinear MR analyses suggested a potential nonlinear association, with lower cancer risk observed at a model-derived exploratory point of approximately 5 h of weekly MVPA. Conclusions: These findings provide supportive evidence that higher accelerometer-measured MVPA is associated with lower total cancer risk and contribute to a better understanding of the dose–response relationship between MVPA and cancer incidence. Full article

Background: Insomnia and stress-related sleep disorders are increasingly recognized as systemic conditions linked to the microbiota–gut–brain axis (MGBA). With growing clinical interest in natural products that modulate the gut environment, this systematic review evaluates the efficacy and mechanisms of non-pharmacological interventions, specifically probiotics, prebiotics, dietary indices, and botanicals, in alleviating insomnia, restoring circadian rhythms, and modulating neurochemical markers. Methods: In strict accordance with PRISMA 2020 guidelines, we searched PubMed, ScienceDirect, Scopus, and The Cochrane Library for English language studies published from inception to March 31, 2026. Eligibility was restricted to studies with rigorously controlled designs, specifically randomized controlled trials (RCTs) and controlled in vivo animal studies. Interventions had to target the gut microbiota, with primary outcomes measuring sleep quality (subjective or objective) or sleep-related neurochemical markers. We excluded uncontrolled, single-arm, or observational designs; in vitro studies; non-original research; and studies involving subjects with severe medical or psychiatric comorbidities (e.g., cancer, ADHD, severe psychiatric disorders) to prevent confounding variables, though mild-to-moderate anxiety and depression were permitted. Risk of bias was assessed using the Cochrane RoB 2.0 and SYRCLE tools. Due to significant methodological heterogeneity, a narrative synthesis stratified by intervention and population was conducted. This review was not registered in PROSPERO. Results: A total of 56 studies (33 humans, 23 animals) met the inclusion criteria. Taxonomic nomenclature was updated to reflect 2020 reclassifications (e.g., Lactiplantibacillus plantarum). In human trials, interventions significantly improved subjective sleep metrics (PSQI, ISI). Recent additions demonstrated the efficacy of the Dietary Index for Gut Microbiota (DI-GM) and the improvement in N3 sleep latency by yeast mannan. Furthermore, whole-food patterns (e.g., the MIND diet) and Traditional Chinese Medicine (TCM) decoctions successfully enriched beneficial taxa, such as Bacteroides coprophilus, and increased short-chain fatty acid (SCFA) production. Animal models demonstrated that “psychobiotic” strains (Bifidobacterium breve, Lacticaseibacillus paracasei), prebiotics (GOS/PDX), and TCM formulas effectively restored GABA/5-HT profiles, lowered morning cortisol, and facilitated REM rebound in PCPA-induced models, while also consolidating non-rapid eye movement (NREM) sleep and downregulating clock genes (Per1/Per2). Conclusions: Psychobiotics, prebiotics, and botanicals represent a highly viable non-pharmacological strategy for treating insomnia. However, current evidence is constrained by a heavy reliance on subjective human questionnaires, short follow-up durations limiting insight into long-term stability, and a substantial translational gap between mechanistic rodent models and human clinical outcomes. Full article

Objective diagnosis in psychiatry remains challenging due to the lack of reliable biological markers and the presence of confounding variables in observational data. While EEG-based machine learning models have shown promising classification performance, their validity remains unclear when confounding factors such as age are not explicitly controlled. In this work, we propose a confound-aware mathematical framework for supervised learning, where classification is formulated as a mapping $f:{\mathbb{R}}^{E\times C\times T}\to \mathcal{Y}$ under the presence of a confounding variable A. Within this formulation, model performance is interpreted as a function of both predictive structure and confound dependence. The proposed framework integrates classification, regression, and feature selection into a unified evaluation pipeline. A central contribution is the Cross-Task Explanation Concordance (CTEC) index, a rank-based metric that quantifies the stability of feature importance across models and predictive tasks. Experimental results on a large-scale EEG dataset (N = 670) demonstrate that deep learning models outperform handcrafted approaches under standard evaluation. However, under confound-controlled settings, handcrafted models show a dual response to confound control: age residualization improves classification by removing feature-level noise (+20.3%), while age-matching collapses performance to chance (balanced accuracy, BA = 0.238) by eliminating demographic separability. Deep learning models retain partial robustness under both conditions. These findings highlight that conventional performance metrics may overestimate model validity in the presence of structured bias. The proposed framework provides a general mathematical approach for evaluating supervised learning models under confounding effects and is applicable to a wide range of data-driven systems beyond EEG. Full article

Vessel port stay time is a key indicator for berth allocation, crane planning, and short-term operational coordination in container terminals. However, existing prediction approaches often rely mainly on numerical operational data and assume complete information availability, limiting their reliability when localized visibility constraints or incomplete sensing occur. This study develops and evaluates an availability-aware multimodal prediction framework for vessel port stay time estimation. The framework adapts cross-attention-based fusion to integrate structured operational variables, numerical marine weather observations, and image-derived visibility information extracted from port monitoring images under incomplete monitoring image availability. In the framework, operational and numerical weather variables form the structured predictive state, whereas image-derived visibility information is conditionally incorporated as an auxiliary visual signal only when a matched and usable monitoring image is available. The proposed approach was evaluated using long-term vessel call data from a major container terminal. Compared with commonly used machine learning and deep learning baselines, the proposed model improved prediction accuracy, while residual analyses indicated reduced systematic prediction bias. These findings suggest that the proposed framework can support more reliable short-term berth planning under practical data-collection constraints. Full article

Accurate and reliable localization is a fundamental requirement for autonomous mobile robots operating in structured indoor environments. Adaptive Monte Carlo Localization (AMCL), widely used due to its probabilistic flexibility, suffers from performance degradation in challenging situations such as low-motion, sensor degradation, symmetry ambiguity, and abrupt position changes (kidnapped robot). This study proposes the Confidence-Gated Virtual Scan Motion AMCL (CG-VSM-AMCL) approach, which extends the standard AMCL structure with a selective and confidence-based posterior enhancement mechanism to overcome these limitations. The proposed method integrates beam partitioning, cluster-based dominance analysis, observability-aware gating, and recovery-driven adaptive particle injection components within a holistic architecture. The method was evaluated on a structured department map under seven representative scenarios: cold-start, low-motion, kidnapped robot recovery, odometry bias, scan dropout, world–model mismatch, and symmetry ambiguity. Experimental results demonstrate that the proposed approach systematically reduces localization error, false-lock rate, and convergence time compared to basic AMCL variants, and improves stability under challenging conditions. The significant improvements achieved, particularly in low-motion and symmetry-containing environments, reveal that selectively activated correction strategies can substantially increase localization robustness without altering the fundamental probabilistic structure of AMCL. Full article

In this work, plasmonic photoconductive antenna (PCA) structures with different grating-width and gap configurations were numerically investigated to evaluate their influence on transient-current generation and terahertz (THz) emission performance. Two geometrical scaling strategies were considered: a fixed-gap configuration with a constant 100 nm photoconductive gap and a proportional-gap configuration in which the gap size was equal to the grating width. Three-dimensional finite element method (FEM) simulations were performed to analyze transient carrier dynamics, THz pulse electric-field behavior, and frequency-domain spectral response under 800 nm optical excitation. The results demonstrate that reducing the inter-grating gap enhances plasmonic near-field confinement and carrier localization near the metal–semiconductor interface, leading to stronger transient-current responses and enhanced THz characteristics. Spatial field and carrier-distribution analyses further confirmed improved electric-field localization and carrier confinement for the fixed-gap structures. In addition, voltage-dependent investigations showed that increasing the applied bias voltage strengthens carrier acceleration and enhances the simulated THz response within the investigated operating range. The results further demonstrate that the observed enhancement is governed not only by grating periodicity but also by the grating-width/gap-size ratio, highlighting the importance of geometrical fill-factor optimization. Polarization-dependent simulations confirmed the plasmonic origin of the enhanced transient-current generation and THz emission. These findings demonstrate that optimal THz performance arises from a balanced interplay between plasmonic field localization, optical absorption, and carrier-transport dynamics, providing design guidelines for the optimization of plasmonic THz PCAs. Full article

Background: Motor competence (MC), physical activity (PA), and physical fitness (PF) are interrelated components of child development, yet evidence on the MC–PF–PA triad in middle childhood remains inconsistent due to methodological heterogeneity. Objective: To synthesise associations between MC, PF, and PA in children aged 5–10 years (2020–2025) and to appraise methodological quality and certainty. Methods: A PRISMA 2020-compliant systematic review (PROSPERO: CRD42024617560) searched six databases (PubMed, Scopus, Web of Science, SportDiscus, SciELO, PsycINFO) from January 2020 to April 2025, updated November 2025. Eligible observational studies in English reported quantitative associations between ≥2 constructs in 5–10-year-olds using validated instruments. Risk of bias was appraised in duplicate with JBI checklists. Quantitative pooling was unfeasible under a pre-specified pooling matrix; associations were synthesised narratively and certainty rated using a GRADE-style framework. Results: Thirteen studies (n = 43–1064; 11 cross-sectional, 2 longitudinal) were included; six were low, five moderate, and two high risk of bias. MC–PA was predominantly positive, especially with objective instruments; MC–PF was consistently positive; PF–PA was less consistent but trended positive longitudinally. Mediation/moderation analyses (k = 3) supported roles for perceived competence, self-efficacy, and PF. Null/negative findings clustered among subjective PA measures and higher risk of bias. GRADE certainty was low-to-moderate. Conclusions: MC, PF, and PA are interconnected in middle childhood, but cross-sectional predominance and instrument heterogeneity preclude causal inference; findings are provisional and should drive longitudinal, methodologically standardised research. Full article

Fusing spatial observations from sensors with heterogeneous error characteristics is a persistent challenge in geostatistics. Classical kriging assumes a Gaussian likelihood for all observations, an assumption that fails when sensors exhibit one-sided or asymmetric noise. We present a Variable Rank Kriging (VRK) formulation that supports per-observation heterogeneous likelihoods where each observation may define its own likelihood function, thus enabling principled fusion of sensors whose noise structures are significantly different in terms of distribution family and magnitude. Within this framework, we use the exponential (one-sided) likelihood as a case study to demonstrate the method and compare it with sampling-based numerical alternatives for general likelihoods without closed forms. A non-collocated RTK calibration workflow uses kriging predictions from a sparse high-accuracy reference to characterise sensor-specific likelihood parameters without requiring co-located paired observations. Synthetic 1-D and 2-D experiments show that correct per-point likelihood specification reduces RMSE by up to 92% (1-D) and 57% (2-D) relative to a misspecified Gaussian model while also eliminating systematic positive bias. A demonstration using NEON Airborne Observation Platform lidar data at Harvard Forest confirms these findings in a practical, real-world scenario. Across multiple subsamples of the lidar dataset, the exponential likelihood reduces vegetated-zone RMSE by $20.6\%$ (open zone: $18.6\%$) and mean absolute bias by $26.5\%$ relative to a heteroscedastic Gaussian baseline. The open-source vrk Python ($>=$3.10) package provides a reproducible implementation that can be applied to any spatial domain that requires multi-sensor spatial fusion with heterogeneous error structures. Full article

Background: Dental ankylosis (DA) in growing patients leads to progressive infraocclusion and alveolar ridge deformities, compromising future implant rehabilitation. Decoronation has been proposed as a biologically driven alternative to extraction for preserving alveolar bone during growth. Objective: We aimed to evaluate the clinical outcomes of decoronation—alveolar ridge preservation, infraocclusion progression, implant site development, and the influence of treatment timing—in growing patients with ankylosed permanent anterior teeth. Methods: This systematic review was conducted in accordance with PRISMA 2020 guidelines. A comprehensive search of MEDLINE (EBSCO), EMBASE, Scopus, and Web of Science was performed (January 2006–May 2026), supplemented by grey literature screening. Eligible studies included clinical investigations reporting outcomes of decoronation in patients ≤18 years. Risk of bias was assessed using the Newcastle–Ottawa Scale (NOS) and Joanna Briggs Institute (JBI) checklist. Certainty of evidence was evaluated using the GRADE framework. Lastly, an inter-rater agreement was quantified using Cohen’s kappa coefficient. Results: Five studies (two retrospective cohorts and three case series) comprising 140 decoronated teeth with follow-up periods ranging from 1 to 30 years were included. A total of 78 records were identified across four databases; five studies met the eligibility criteria after duplicate removal and screening. Inter-rater agreement at the full-text eligibility stage was good (κ = 0.70). The overall risk of bias was low to moderate, and the certainty of evidence was rated as low using the GRADE framework. Vertical alveolar bone preservation or gain was consistently observed, particularly when decoronation was performed during the prepubertal or pubertal growth phases. The largest cohort (n = 103) reported substantial vertical bone gain when intervention occurred at a mean age of 13.0 years in girls and 14.6 years in boys. Infraocclusion stabilisation or improvement was reported across all studies. In contrast, horizontal ridge reduction persisted, with the only quantitative study reporting a mean bucco-palatal loss of 1.67 ± 1.12 mm (p = 0.004). No included study directly assessed implant placement outcomes. Overall, the certainty of evidence was low due to observational study designs, heterogeneity in outcome assessment, and absence of controlled comparators. Conclusions: Decoronation appears to be a promising strategy for preserving vertical alveolar bone and stabilising infraocclusion in growing patients with ankylosed teeth, particularly when performed before or during the pubertal growth phase. Evidence showed considerable bone height preservation, though horizontal ridge reduction persisted across cases. However, the certainty of evidence remains low because available studies are observational, heterogeneous, and lack direct extraction comparators. Therefore, high-quality prospective studies with standardised outcome measures and controlled comparisons are required to establish definitive clinical protocols. Participants underwent decoronation during childhood or adolescence (≤18 years); reported follow-up periods of up to 30 years reflect monitoring that extended into adulthood. Clinical significance: For clinical decision-making, decoronation should be considered once ankylosis with progressive infraocclusion is confirmed during active growth, ideally before the pubertal spurt; the decision should be guided by growth stage rather than chronological age, and clinicians should anticipate likely horizontal ridge reduction by planning for possible augmentation at implant placement and coordinating multidisciplinary follow-up until skeletal maturity. Full article

Background: Torque teno virus (TTV) is a ubiquitous, non-pathogenic component of the human virome whose role in people living with HIV (PLWH), particularly during antiretroviral therapy (ART)-mediated immune reconstitution, remains unclear. This systematic review aimed to synthesize available evidence on TTV viral load in PLWH, focusing on its relationship with immunological markers. Methods: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A comprehensive literature search was conducted in MEDLINE, Web of Science, and Scopus in January 2026 to identify studies assessing plasma TTV viral load before and/or during ART and reporting immunological outcomes. Eligible studies included prospective and retrospective longitudinal studies, cross-sectional studies, and mixed designs assessing plasma TTV viral load in relation to ART status and immune recovery markers. Results: Thirteen studies (n = 1700 PLWH) were included, predominantly observational and conducted in adult populations. Most studies (76.9%) reported a significant inverse association between TTV viral load and CD4 T-cell count, while all studies assessing HIV viral load found a direct correlation with TTV levels. An inverse relationship with the CD4/CD8 ratio was consistently observed where evaluated. Higher TTV loads were reported in ART-naïve individuals and in those with advanced immunosuppression, with longitudinal studies indicating a general decline during ART. Overall, methodological heterogeneity and moderate risk of bias were common. Conclusions: TTV viral load shows a consistent inverse association with CD4 cell count and may reflect global immune dysfunction in PLWH beyond conventional markers. However, its clinical utility remains investigational due to the heterogeneity in the study design, limited data on longitudinal dynamics, and lack of standardized assays and thresholds. Full article