---
title: "Resistance exercise vs non-exercise control for inflammatory markers and T-cell counts in adults w"
id: "frontiers-in-immunology-16-resistance-containing-exercise-versus-non-exercise-control-for-inflammatory"
canonical_url: "https://medichelpline.com/clinical-feed/frontiers-in-immunology-16-resistance-containing-exercise-versus-non-exercise-control-for-inflammatory"
content_type: "clinical_feed_article"
specialty: "Infectious Disease"
source_name: "Frontiers in Immunology"
source_url: "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1949799"
published_at: "2026-10-07T00:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Resistance exercise vs non-exercise control for inflammatory markers and T-cell counts in adults w
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/frontiers-in-immunology-16-resistance-containing-exercise-versus-non-exercise-control-for-inflammatory
- **Specialty:** [Infectious Disease](https://medichelpline.com/clinical-feed/infectious-disease.md)
- **Primary Source:** Frontiers in Immunology
- **Source URL:** [Original Journal Publication](https://www.frontiersin.org/articles/10.3389/fimmu.2026.1949799)
- **Published At:** 2026-10-07T00:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The source is a SYSTEMATIC REVIEW and meta-analysis published in Frontiers in Immunology that compares **resistance exercise** with a **non-exercise control** in adults living with **HIV**, focusing on **inflammatory markers** and **T-cell counts**. - The article type, journal, and primary comparison (resistance-containing exercise versus non-exercise control) are reported by the source metadata, but the body text of the study (methods, results, and conclusions) is not available in the provided source content. - The source repeatedly includes Frontiers in Immunology website navigation, journal sections, and general journal information; no trial-level details, effect sizes, populations, exercise prescriptions, durations, or statistical outcomes are reported in the supplied text. - No information on included studies, eligibility criteria, data extraction, risk-of-bias assessment, specific inflammatory biomarkers measured (for example, CRP, IL-6, TNF-α), or T-cell subsets evaluated (for example, CD4+, CD8+) is provided in the available source content. - The provided content does not report pooled effect estimates, heterogeneity metrics, subgroup analyses, sensitivity analyses, or certainty of evidence ratings (GRADE or similar). - No clinical recommendations, practical exercise prescriptions, or safety/adverse event data are present in the supplied material. - For clinicians or researchers seeking actionable findings (effect sizes, confidence intervals, clinical significance), the full article text must be consulted because those details were not reported in the source material provided here. - The available metadata confirms the topic and article type but not the study findings; users should retrieve the complete Frontiers in Immunology article at the original URL for full methods and results.
## Clinical Analysis & Structured Key Points
Frontiers | Resistance-containing exercise versus non-exercise control for inflammatory markers and T-cell counts in adults living with HIV: a systematic review and meta-analysis SYSTEMATIC REVIEW article Front. Immunol. , 07 October 2026 Sec. Inflammation Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1949799 Published in Frontiers in Immunology Inflammation 7 impact factor 11.3 citescore Part of a Research Topic Immune activation, immunosenescence, and aging-related conditions in chronic infections Submission open 1282 views 1 articles Editor & Reviewers Edited by C K Christina K. Psomas Reviewed by D J Dachuan Jin B M Binoy Mathew K V Outline Figures and Tables Figure 1 View in article Figure 2 View in article Figure 3 View in article Figure 4 View in article Figure 5 View in article Table 1 Characteristics of the included trials. View in article Table 2 Intervention and comparator characteristics of the included trials. View in article Table 3 Primary effects of resistance training or resistance-containing combined exercise versus non-exercise control. View in article Table 4 Overall risk of bias of the included trials. View in article Table 5 Summary of findings: resistance training or resistance-containing combined exercise compared with non-exercise control in adults living with HIV. View in article SYSTEMATIC REVIEW article Front. Immunol. , 07 October 2026 Sec. Inflammation Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1949799 Resistance-containing exercise versus non-exercise control for inflammatory markers and T-cell counts in adults living with HIV: a systematic review and meta-analysis J Z Jiayi Zhang † Y G Yafei Gao † Z Z Zhentao Zhang Z L Zikun Lyu * J M Jingshi Ma * Department of Physical Education, Kunsan National University, Gunsan-si, Republic of Korea Article metrics View details Abstract Background: Adults living with HIV may have persistent immune activation and low-grade inflammation despite effective antiretroviral therapy. We assessed whether resistance training or resistance-containing combined exercise alters inflammatory biomarkers or T-cell counts versus non-exercise control. Methods: Six databases were searched to 1 June 2026 without language restrictions. Controlled intervention studies lasting at least four weeks were eligible. Screening and extraction were performed independently in duplicate. Inflammatory outcomes were expressed as Hedges’ g; final-value SMDs were primary and change-score SMDs were analyzed separately, with one-trial strata reported individually. CD4+ T-cell count was pooled as a mean difference. Random-effects models used restricted maximum likelihood and Hartung-Knapp-Sidik-Jonkman intervals. RoB 2 or ROBINS-I and GRADE were applied. Results: Fifteen trials (18 reports) were included; 13 contributed quantitative data. All primary final-value confidence intervals included no effect: interleukin-6, −0.19 (95% CI −1.14 to 0.76; k = 4); tumor necrosis factor alpha, 0.07 (−1.44 to 1.57; k = 3); C-reactive protein, −0.02 (−1.46 to 1.41; k = 3); interleukin-1 beta, −0.47 (−10.09 to 9.15; k = 2); and interleukin-10, 0.04 (−11.37 to 11.46; k = 2). Interleukin-8 was reported by one final-value trial, −0.63 (−1.39 to 0.12), and was not pooled. Separate change-score analyses were also inconclusive except for one unpooled C-reactive protein trial. The pooled estimate for CD4+ T-cell count favored exercise by 124.2 cells/mm 3 (54.6 to 193.7; k = 7), but the prediction interval crossed no effect. Certainty was very low. Conclusion: The effects of resistance-containing exercise on inflammatory biomarkers remain undetermined. The CD4+ estimate suggests a possible increase, but confidence is very limited because the evidence is sparse, heterogeneous, at risk of bias, and its prediction interval includes no effect. Larger trials with well-defined comparators and complete contrast-form reporting are needed. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261425700 , identifier CRD420261425700. 1 Introduction Antiretroviral therapy has transformed HIV infection from a progressive, usually fatal illness into a chronic condition compatible with a near-normal lifespan ( 1 , 2 ). That success has revealed a second problem. Even among adults with durable viral suppression and restored CD4+ T-cell counts, markers of immune activation and low-grade systemic inflammation frequently remain above the levels seen in people without HIV ( 1 , 3 ). This residual inflammatory state is not a laboratory curiosity. Elevated interleukin-6, C-reactive protein and D-dimer concentrations predict all-cause mortality and non-AIDS events in treated cohorts ( 4 , 5 ), soluble inflammatory markers outperform T-cell activation markers in forecasting non-AIDS morbidity during suppressive therapy ( 6 ), and the same biology is implicated in the excess burden of cardiovascular, metabolic and skeletal disease observed in this population ( 7 , 8 ). Reducing residual inflammation has therefore become an explicit therapeutic target alongside virological control. The mechanisms that sustain this state are several and partly independent of viral replication: microbial translocation across a damaged gut mucosa, persistent low-level antigen stimulation, thymic dysfunction, co-infections and the cumulative toxicity of long-term therapy ( 3 ). Because no single pharmacological agent addresses this cluster, attention has turned to interventions that act broadly on the inflammatory milieu. Exercise is the most prominent of these. Regular physical activity lowers circulating inflammatory markers in a range of chronic conditions, and the proposed mechanisms — reduction in visceral adipose tissue and its adipokine output, and the acute anti-inflammatory environment created by each bout of contraction, mediated in part by muscle-derived signaling molecules — are plausible in HIV ( 9 – 11 ). Resistance training has a particular claim in this setting. Loss of skeletal muscle mass and function is common in long-term HIV infection, and skeletal muscle is itself an endocrine organ whose secretory output changes with loading ( 11 ). Resistance exercise is thus advocated both to counter the muscle-specific consequences of infection and therapy and, more speculatively, to modify the inflammatory state directly. Trials in adults living with HIV have accordingly examined resistance training alone and combined programs containing a resistance component, measuring cytokine panels and immune cell counts alongside functional endpoints. The evidence these trials have produced is not easy to read. Existing systematic reviews of exercise in HIV have concentrated on cardiorespiratory fitness, strength, body composition and psychological outcomes, treating immunological endpoints as secondary ( 12 – 15 ). Where inflammatory outcomes have been synthesized, reviews have tended to combine aerobic and resistance modalities, or to pool across biomarkers whose biology and measurement differ ( 16 , 17 ). Individual trials are small, and their reported effects for the same biomarker range from substantial reduction to substantial increase; one trial found that adding resistance training to inpatient care improved skeletal muscle health without altering cytokine concentrations at all ( 18 ). Physical activity levels in this population are low ( 19 ), which makes the question practically as well as biologically consequential. Three features of this literature warrant a synthesis designed specifically around them. First, the outcomes are chemically and biologically distinct constructs, so pooling should be organized by construct rather than by an aggregate notion of “inflammation”. Second, trials differ in whether they report post-intervention values or change from baseline. Standardized effects derived from these forms use different standardizing standard deviations and are not directly comparable, so they require separate synthesis. Third, comparators vary from genuine no-exercise control to recreationally active control and to placebo, medication, or care backgrounds applied equally in both arms; this variation may contribute to between-trial differences but does not necessarily make the exercise contrast indirect. We therefore conducted a systematic review and meta-analysis to determine the effects of structured resistance training or resistance-containing combined exercise, compared with a non-exercise comparator, on inflammatory biomarkers and T-cell counts in adults living with HIV, synthesizing each construct separately. For the inflammatory constructs, final-value standardized mean differences were designated as the primary evidence and change-score standardized mean differences as supporting evidence; variation by study characteristics was examined only in post hoc exploratory analyses. 2 Methods 2.1 Reporting guidance This review is reported in accordance with the PRISMA 2020 statement and its explanation and elaboration document ( 20 , 21 ), and the search is reported in accordance with the PRISMA-S extension ( 22 ). Methods followed the Cochrane handbook for systematic reviews of interventions ( 23 , 24 ). The review protocol was registered in PROSPERO (registration number CRD420261425700). The separation of final-value and change-score standardized mean differences, the designation of final values as primary, and all subgroup and robustness analyses were not specified in the registered protocol and are therefore reported as post hoc exploratory analyses. 2.2 Eligibility criteria Studies were eligible according to the following criteria. Population. Adults aged 18 years or older living with HIV, regardless of antiretroviral regimen or treatment status. Intervention. Structured resistance training, or combined/concurrent exercise containing an identifiable resistance component, lasting at least four weeks. Comparator. A non-exercise comparator: usual care, waiting list, recreational or health-education control, or a shared medication background without exercise. Outcomes. Inflammatory biomarkers and T-cell measures defined the review question; the quantitative outcome set comprised interleukin-6, tumor necrosis factor alpha, C-reactive protein, interleukin-1 beta, interleukin-8, interleukin-10, and CD4+ T-cell count. The secondary outcome set, detailed in Supplementary Table S7 , included additional inflammatory and T-cell measures, HIV-1 viral load, growth factors, adipokines, neurotrophic factors and hormones; safety and adherence were also assessed narratively. The secondary outcomes were listed at the eligibility stage so that each report was screened once against the complete outcome set, and they were prespecified for narrative rather than quantitative synthesis; they are reported in Section 3.8, with the reason for narrative synthesis recorded for each in the Supplementary Material . Study designs. Randomized controlled trials, quasi-randomized controlled trials, and non-randomized controlled intervention studies with a parallel non-exercise comparator. Studies were excluded when the comparator was an active exercise arm with no non-exercise arm; when a multicomponent intervention could not be isolated to its exercise element; when only acute (single-bout) exercise was studied; when the design was uncontrolled; and when outcome data contained internal errors that could not be recovered. The unit of synthesis was the trial. Where several reports described the same trial, they were merged under a single trial identifier and counted once. 2.3 Information sources and search strategy Six databases were searched from inception to 1 June 2026: PubMed, Web of Science Core Collection, Embase, Cochrane Library, Scopus and SPORTDiscus. No language restriction was applied. The search combined four concept blocks — HIV, resistance or combined exercise, inflammatory and immunological outcomes, and controlled trial design — using database-appropriate controlled vocabulary and free-text terms. Reference lists of included reports and of prior reviews were inspected for additional records. The database-specific search strategies, together with the recorded search date and number of records retrieved from each database, are reported in Supplementary Table S1 . Trial registries were not searched as a separate information source, authors of included reports were not contacted, and the search strategy was not peer reviewed by a second information specialist. Registry records were covered in part through the Cochrane Library (CENTRAL), which incorporates records from ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform; however, this indirect coverage is not equivalent to direct registry searching, and unpublished or ongoing studies may therefore have been missed. Because fewer than 10 trials contributed to every pooled construct, funnel-plot methods were not used and small-study effects cannot be excluded. This limitation is considered further in Section 4.5. This review was not an update of an earlier review. 2.4 Selection and data collection Records were deduplicated and then screened on title and abstract against the eligibility criteria by two reviewers (JZ and YG) working independently; a record retained by either reviewer proceeded to full text. Full-text reports were assessed for eligibility by the same two reviewers, again independently and in duplicate. Data were extracted independently and in duplicate by the same two reviewers into a piloted extraction form, and the two records were compared item by item. Disagreements at the screening, eligibility and extraction stages were resolved by discussion between the two reviewers, and a third reviewer (JM) adjudicated any that remained; the third reviewer’s decision was final. Every extracted value was additionally checked against the source report by the third reviewer in a separate source-verification step, in which the numeric values, group denominators, units, contrast form and outcome labels were compared with the corresponding table, figure or text in the original publication. Discrepancies identified at verification were resolved by returning to the source report. Extracted items comprised study identifiers and design; country; participant characteristics including age, sex distribution and baseline clinical status; the content, duration, frequency, session length, intensity prescription, progression rule, supervision and delivery mode of the intervention; the nature of the comparator; adherence; the timing of outcome assessment; and, for every outcome, the reported group means, dispersion measures, denominators, units and contrast form. 2.5 Outcome constructs The outcome-level data used to compute every effect estimate, including the group means, dispersion measures, denominators, units, contrast form and the derivation of any reconstructed dispersion, are reported in full in Supplementary Table S2 . Outcomes were standardized to clinical-biological constructs before synthesis. Values reported under different assay-specific labels or in convertible units were mapped onto a single construct where they measured the same analyte, and distinct analytes were never merged. Original outcome labels were retained for traceability but were not used as analysis units. For a primary inflammatory construct, two or more independent trials within the same contrast form were required for meta-analysis; a stratum containing one trial was reported as an individual study result. The prespecified secondary outcomes remained narrative regardless of study count, as specified in Section 2.2. Analysis roles are defined consistently throughout this review: Primary denotes final-value estimates for the six quantitative inflammatory constructs and the combined-form CD4+ mean-difference analysis; Supporting denotes the separate inflammatory change-score estimates; Sensitivity denotes a post hoc robustness check of a Primary or Supporting reference analysis; and Narrative denotes descriptive reporting without cross-trial pooling. A one-trial Primary or Supporting stratum retains that role and is reported individually, whereas Narrative outcomes may have individual contrasts tabulated without being meta-analyzed. 2.6 Effect measures Each construct was analyzed on a single effect metric, and standardized and unstandardized estimates were never combined within an analysis. CD4+ T-cell count was expressed as a mean difference in cells/mm 3 . Every inflammatory biomarker construct was expressed as a standardized mean difference using Hedges’ g with the small-sample bias correction ( 25 ). Final-value and change-score standardized effects were not combined. Final-value standardized mean differences were designated as primary because they provided a common standardization basis across the construct set without requiring an unavailable within-person pre-post correlation; change-score standardized mean differences were synthesized separately as supporting evidence. For CD4+ T-cell count, final-value and change-score effects were combined as unstandardized mean differences because both estimate the absolute between-group difference in the same unit. All contrasts were oriented as exercise minus comparator. Directions were harmonized before analysis so that, for the pro-inflammatory constructs, a negative value indicates lower concentrations in the exercise group; for CD4+ T-cell count a positive value indicates a higher count in the exercise group. Interleukin-10 was treated as directionally neutral, because a higher concentration is interpretable as anti-inflammatory or pro-inflammatory depending on context. Where a trial reported dispersion in a form other than the standard deviation, the standard deviation was reconstructed using the standard relationships set out in the Cochrane handbook ( 23 ), and the derivation was recorded for each affected estimate. Trials contributing more than one eligible stratum or arm were handled so that no participant group entered a single pooled estimate more than once. One trial, Soares et al. ( 51 ), had two eligible exercise arms sharing a single comparator group. Its two exercise arms were combined into one group using the Cochrane handbook formulae for combining means and standard deviations across groups ( 23 ) before the contrast was formed, so the comparator entered the analysis once and at its full size; dividing the comparator was therefore not required, and no participant was counted twice. For the factorial trial, Zanetti et al. ( 55 ), the placebo-background stratum contributed to the Supporting inflammatory change-score analyses, with the alternative statin-background stratum and the merged trial examined in Sensitivity analyses; all fibrinogen contrasts remained Narrative. Companion reports of the same trial were merged under a single trial identifier before extraction, so no trial contributed more than once through duplicate publication. 2.7 Synthesis methods Domain-level risk-of-bias judgments are provided in Supplementary Table S3 ; robustness analyses are reported in Supplementary Table S4 ; and subgroup eligibility, separate contrast-form analyses, and moderator screening are detailed in Supplementary Table S5 . Randomized, quasi-randomized and non-randomized controlled studies were eligible together because the evidence base for this question is small. The consequences of that choice were handled analytically: risk of bias was assessed with the tool matched to each design, the design composition and statistical weight of non-randomized evidence were reported, and any mixed-design construct was additionally restricted to randomized trials. For inflammatory outcomes, only post-intervention final-value standardized effects entered the primary analysis; change-score standardized effects were analyzed separately as supporting evidence. A contrast-form stratum was meta-analyzed when at leas
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