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A bimodal large language model reduces misalignment in patient education: A double-blinded randomized trial.

BACKGROUND: Effective patient education requires accurate communication aligned with patients' emotional and semantical needs. Text-based large language models (LLMs) lack access to non-verbal cues, which may contribute to misaligned responses. METHODS: We evaluated emotional and semantic misalignment in a text-based LLM using 64,200 utterances from 16,583 patient education cases across six departments and three centers. Dolphin was developed integrating text and audio cues and evaluated through emotion recognition, semantic consistency assessment, branch-level ablations, and a double-blinded randomized trial against a matched text-based LLM comparator (Chinese Clinical Trial Registry: (ChiCTR2500095933). FINDINGS: The text-based LLM showed emotional misalignment in 36.7% of responses and semantic misalignment in 28.3% of cases, with higher misalignment under greater burden. Dolphin outperformed the text-based LLM in emotion recognition accuracy (0.886 vs. 0.713) and semantic consistency (84.9% vs. 82.1%; both adjusted p < 0.001). Ablations supported contribution of audio branches. Dolphin received higher expert ratings than the text-based LLM and human educators (all p < 0.001). In 555 patients, Dolphin was associated with greater patient satisfaction (98.6% vs. 93.8%), suggestion acceptance (76.1% vs. 58.9%; p < 0.001), proactive disclosure (44.6% vs. 26.5%; p < 0.001), and fewer 7-day unplanned recontact (12.9% vs. 22.9%; p = 0.002). No unsafe recommendations or safety events were identified. CONCLUSIONS: Compared with text-based LLM, Dolphin improved emotional-semantic alignment and patient-education outcomes, supporting bimodal alignment as a strategy for reducing misalignment-driven communication failures. FUNDING: National Natural Science Foundation of China, State Key Laboratory Special Fund, and Chinese Academy of Medical Sciences Innovation Fund.

Humans

Integrative quantum and systems biology of cancer: From molecular fluctuations to ecological outcomes.

This review treats cancer as a multiscale adaptive system, asks what the framework must predict to be worth adopting, and separates at each scale what the evidence establishes from what is proposed. It is an expert narrative synthesis, not a systematic review, and states the limits of that design. Proton transfer and tautomeric shifts contribute to spontaneous mispairing but do not license claims of directed or non-random mutation: replication timing, three-dimensional chromatin organization, sequence context and known mutagenic processes explain most mutational heterogeneity, leaving any quantum contribution as a residual against that baseline. The Waddington quasi-potential is bounded: outside detailed balance the dynamics are not gradient-derivable and require a probability-flux term. Hysteresis, rate-limited bimodality and return to state after perturbation distinguish an attractor from a transcriptomic cluster. Single-cell karyotype and live-imaging evidence supports whole-genome doubling as an unstable intermediate of heterogeneous origin and context-dependent consequence, not a uniform adaptive strategy. Systems and synthetic biology, virtual cells and digital twins are assessed against benchmarks, not promise. Tissue-scale ecology is reported with the spatial measurements now quantifying it, including evidence that stromal niche construction is not uniformly tumor-supporting. RNA modification is a layer in its own right, showing that the interpretation of a regulatory signal, not its magnitude, is biologically decisive. A dedicated section states the framework's commitments, the observable and evidence at each scale, and what would falsify them, asking what this adds to somatic mutation theory with clonal evolution and plasticity.

Neoplasms

Satisfaction with clinical practice environments among early-career health professionals in South Africa: Findings from the WiSDOM cohort study.

BACKGROUND: The work or practice environments of health professionals play a central role in their retention in the healthcare system and their ability to provide quality patient care. The aim of the study was to examine and compare the satisfaction of early-career health professionals in the WiSDOM (Wits longitudinal Study to Determine the Operation of the labour Market among its health professional graduates) study with their clinical practice environments (CPEs) in South Africa, and the factors influencing their satisfaction. METHODS: WiSDOM, a prospective longitudinal cohort study, consists of eight health professions: clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists, and physiotherapists. Every year we collect information on the cohort's involvement in direct patient care, their perceived workload, availability of medicines and equipment for patients in their care, and their satisfaction with the clinical practice environment (CPE).We used Stata&#xae;19 for analysis. We used panel linear regression to investigate factors associated with the cohort's satisfaction with their clinical practice environments from 2018 to 2024, and logistic regression to evaluate the association between CPE and intention to leave in 2024. RESULTS: In 2024, the mean age of the cohort was 30.9 (&#xb1; 2.0), the majority were female (74.4%) and working in urban areas (92.7%). In 2024, 59.7% of the overall cohort reported a heavy workload compared to 69.2% in 2018. Over the follow-up period, reported problems with the availability of medicines or equipment were worse in the public sector and in rural areas, compared to the private sector and urban areas respectively.The cohort's satisfaction score with the CPE was 6.7 out of 10 in 2018 and 6.9 in 2024. The predictors of CPE were year of follow-up, health profession, employment sector, and geographic location. Nurses (&#x3b2;=-1.2; 95% CI -1.7, -0.7; p&#x2009;<&#x2009;0.001), and pharmacists (&#x3b2;=-0.7; 95% CI -1.1, -0.4; p&#x2009;<&#x2009;0.001) scored their CPE significantly lower compared to the other professional groups. Health professionals in the public sector (&#x3b2;=-1.1; 95% CI -1.3, -0.9; p&#x2009;<&#x2009;0.001) and in rural areas (&#x3b2;=-0.6; 95% CI -0.9, -0.3; p&#x2009;<&#x2009;0.001) were less satisfied with their CPE compared to those in the private sector and urban areas respectively. Dissatisfaction with the CPE was significantly associated with intention to leave the workplace and the profession. CONCLUSION: The study findings underscore the need for positive clinical practice environments for early-career health professionals in South Africa both as a health workforce and patient safety imperative.

South Africa

Systemic biomarkers of treatment response to methotrexate in people with painful knee osteoarthritis: A biological substudy of the PROMOTE randomised controlled clinical trial.

OBJECTIVE: Stratification of therapeutic responses may help identify efficacious therapies for osteoarthritis (OA). In the PROMOTE randomised trial, participants with elevated baseline high-sensitivity C-reactive protein (hs-CRP) showed greater pain reduction after methotrexate treatment. We set out to interrogate a broader panel of serum/plasma inflammatory response markers relevant to methotrexate actions as potential biomarkers of therapeutic effect. Our objectives were to: (i) characterize changes in these systemic markers during methotrexate treatment; determine whether (ii) baseline levels or (iii) changes in any marker during treatment were associated with treatment response; and (iv) compare these findings with the more established clinical inflammatory marker, hs-CRP. DESIGN: Plasma/serum samples from participants in PROMOTE's biological substudy were analysed for 35 inflammatory markers at baseline (pre-treatment) and at 6-months (post-treatment), by MesoScale V-plex multiplex assay. Those with paired biological and clinical data at both baseline and 6-months were included in the substudy analysis set. Relationships between markers and overall data structure were assessed by Pearson correlation and Principal Component analysis. Associations between markers (baseline levels or change over time) and change in average knee pain severity in past week (numerical rating scale, NRS) were evaluated by univariable linear regression, adjusting for baseline age, sex, and body mass index. Least Absolute Shrinkage and Selection Operator (LASSO) regression with bootstrap resampling enabled marker selection. Benjamini-Hochberg correction adjusted for multiple testing (Padj). RESULTS: 87 participants with paired blood marker and clinical data were eligible for substudy analysis. 18/35 markers were quantifiable and analysed. Systemic IL-8 and TNF-&#x3b1; levels decreased (Padj=0.015, 0.048 respectively) while IL-15 increased (Padj=0.033) with methotrexate treatment over 6-months. Analysing within this active treatment randomised arm, higher baseline IFN-&#x3b3; was associated with greater reduction in NRS pain change (0.66 [0.01, 1.31], P=0.047), as was decreasing TNF-&#x3b1; over 6-months (2.25 [0.00, 4.5], P=0.049). LASSO identified higher IFN-&#x3b3;, lower plasma IL-15 and IL-16, and younger age as the most important baseline predictors of pain improvement. hs-CRP was highly selected by LASSO for treatment response in both arms. In a secondary univariate treatment arm-by-biomarker interaction analysis, of the 19 markers, only hs-CRP showed consistent effects in adjusted models (at baseline, coeffic. 2.34 [0.53, 4.15], P=0.001; change over 6-months, (0.36 [0.06, 0.66], P=0.018). CONCLUSIONS: Blood measurement of IFN-&#x3b3;, TNF-&#x3b1;, IL-15 and IL-16 as well as hs-CRP could act as potential markers to stratify the treatment response by average knee pain to methotrexate in knee osteoarthritis.

Humans

Volumetric bone marrow cellularity (VBMC) assessment from routinely processed trephines using three-dimensional x-ray histology and gaussian peak modelling.

Objective.Bone marrow cellularity is routinely estimated from a small number of two-dimensional histology sections, making assessment sensitive to section representativeness, processing artefacts and observer interpretation. Three-dimensional (3D) x-ray histology (XRH), using x-ray computed microtomography (&#xb5;CT), enables non-destructive whole-block imaging of trephine biopsies. This study evaluated whether XRH combined with Gaussian peak modelling could provide a pragmatic whole-block volumetric bone marrow cellularity (VBMC) estimate from formalin-fixed paraffin-embedded (FFPE) trephine biopsy blocks.Approach.Six routinely processed FFPE bone marrow trephine blocks were imaged using &#xb5;CT-based XRH at &#x223c;15 &#xb5;m spatial resolution. VBMC was defined as the red-marrow (RM) fraction of the marrow soft-tissue compartment, RM/(RM + intra-biopsy wax), with wax serving as the volumetric proxy for adipocyte/yellow marrow space. Whole-volume greyscale histograms were modelled using a three-peak Gaussian approach representing intra-biopsy wax, RM and demineralised trabecular matrix. Peak-height and area-under-the-curve metrics were compared with whole-volume 3D segmentation and clinical two-dimensional (2D) cellularity estimates.Main Results.Gaussian peak modelling successfully approximated the segmented tissue-phase distributions. The peak-height-derived VBMC metric showed the closest agreement with whole-volume 3D segmentation, with an average absolute percentage difference of 9.3%, compared with 18.6% for clinical expert 2D cellularity estimates. The area-under-the-curve metric followed similar trends but consistently overestimated VBMC. Clinical 2D cellularity broadly followed whole-biopsy trends but showed one discordant case not explained by slice-position sampling alone. XRH also enabled unrestricted virtual reslicing and visualisation of sectioning-associated artefacts prior to further microtomy.Significance.Pre-sectioning XRH combined with Gaussian peak modelling provides a rapid, segmentation-free route to volumetric cellularity estimation from intact clinical FFPE trephine blocks. The approach supports objective whole-biopsy assessment while remaining compatible with routine histopathology workflows, reflecting the expected limitations of section-based visual estimation despite its role as the current clinical standard. In the near term, it could provide a non-disruptive adjunct to conventional 2D cellularity reporting, pending larger validation studies.

Imaging, Three-Dimensional

A STORM-based protocol for nanoscale imaging and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber.

Stochastic Optical Reconstruction Microscopy (STORM) enables nanoscale mapping of molecular components beyond the diffraction limit; however, its reproducible implementation in hydrophobic polymer matrices remains challenging because fluorescence-labeling specificity, fluorophore photoswitching, three-dimensional localization, chromatic registration, and quantitative image analysis must be carefully controlled. This protocol presents a standardized experimental workflow for dual-color labeling, astigmatism-based three-dimensional STORM acquisition, and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber (NR). The workflow covers sample pretreatment, Cy5 NHS ester labeling of protein-associated primary amines, DiI labeling of phospholipid-rich domains, STORM imaging-buffer preparation, three-dimensional single-molecule localization, dual-channel registration, generation of standardized xy projections, aggregate-size analysis, and projected lateral spatial correlation assessment. Reproducibility is supported by defined acquisition and localization criteria, three independent sample preparations with at least five fields of view analyzed per condition, and unlabeled, single-color, dye-only matrix, and processing-associated Cy5 controls. Mean lateral localization precisions of 11.8&#x202f;&#xb1;&#x202f;2.3&#x202f;nm for Cy5 and 13.5&#x202f;&#xb1;&#x202f;2.9&#x202f;nm for DiI were obtained, while two-dimensional Fourier ring correlation analysis of the xy projections yielded effective lateral image resolutions of approximately 25 and 28&#x202f;nm, respectively. Image-based particle segmentation and localization-coordinate-based density-based spatial clustering of applications with noise (DBSCAN) were applied to standardized xy projections as complementary quantitative approaches. Application of the protocol to untreated, centrifuged, and protease-treated NR samples demonstrated treatment-associated changes in the detected abundance and projected size distributions of protein- and phospholipid-associated aggregates, together with a non-monotonic change in their projected lateral spatial correlation. These observations describe alterations in nanoscale organization but do not, by themselves, establish stable protein-phospholipid complex formation. Unlike previous studies that primarily demonstrated the feasibility of STORM imaging in rubber materials, the principal contribution of this work is an end-to-end, step-by-step protocol incorporating defined controls, three-dimensional localization, image-quality metrics, chromatic-registration procedures, and complementary quantitative-analysis pipelines for non-expert users. The workflow may be adaptable to other hydrophobic polymers and soft-material systems after appropriate optimization and validation.

Rubber

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry

Community-tailored One Health educational intervention to enhance knowledge and practices for zoonotic disease prevention in rural Thailand: A protocol for a prospective cluster randomised controlled Trial in Chanthaburi, Thailand (Saan Suk trial).

BACKGROUND: Zoonotic infectious disease risk arises at human-animal-environment interfaces where pathogen spillover can occur. Rural communities living in biodiverse settings may experience frequent contact with wildlife and shared environments through livelihoods, food practices, and economic activities. Reducing spillover risk and strengthening pandemic prevention requires both structural and individual-level change. Community-based interventions that promote awareness, risk perception, self-efficacy, pro-environmental behaviour, and safe coexistence with wildlife may support prevention by shifting behavioural determinants of zoonotic disease risk. The Saan Suk intervention was co-developed with rural communities in Thailand using a Human-Centred Design approach and is grounded in the Health Belief Model and One Health principles. The intervention is intended to be feasible, acceptable, and deliverable through Thailand's established Village Health Volunteer (VHV) system. METHODS: This protocol describes a parallel-arm, cluster-randomised controlled superiority trial that will be conducted during July - October 2026, in Chanthaburi Province, Thailand. 24 villages will be equally randomised to the Saan Suk intervention or the current practice (control). In intervention villages, trained VHVs will deliver, once a week over four weeks, a multimodal One Health educational intervention designed to improve knowledge of zoonotic spillover, promote protective behaviours, reduce risky wildlife-related contacts, and support respectful coexistence with wildlife. Trained outcome assessment teams will conduct structured interviews with 42 adult participants per village, yielding a total sample size of 1,008 participants. The sample size was calculated for the primary outcome, accounting for clustering, with 90% power to detect a medium effect size (6 points on the 0-100 knowledge scale) at a significance level of 0.05, accounting for a design effect with an ICC of 0.028. The primary outcome is knowledge of zoonotic spillover, transmission pathways, risk factors, protective and risky behaviours, and safe coexistence with wildlife. Secondary outcomes include attitudes, self-efficacy, preventive and risky behaviours, and reported contacts with major local reservoir hosts. A structured questionnaire was developed, expert-reviewed, and piloted for the outcome assessment. Outcomes will be analysed using mixed-effects regression models with random effects for village and adjustment for relevant pre-specified confounders. Primary analyses will follow the intention-to-treat principle. DISCUSSION: This trial will evaluate whether a co-designed, VHV-delivered One Health educational programme can improve knowledge of zoonotic disease prevention and behavioural determinants in rural communities living in close contact with wildlife and shared ecosystems. If effective and feasible, Saan Suk could inform integration into routine VHV training and community-based zoonotic disease and pandemic prevention strategies. TRIAL REGISTRATION: The Saan Suk trial is registered with the German Clinical Trials Register (DRKS). Registration ID: DRKS00038582; date of registration: 11 May 2026.

Zoonoses

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans

How do we counsel patients on short- and long-term complications after hypospadias repair? - A survey study.

INTRODUCTION: Hypospadias correction remains one of the most performed pediatric urologic procedures, affecting up to 1/150 males born in the United States. Current studies suggest that surgical counseling has a significant impact on shared decision making, decisional regret, and long-term follow-up. However, no set paradigm currently exists for long-term follow-up or counseling. We sought to obtain consensus from established pediatric urologists the optimal content and potential short, intermediate, and long-term complications to be considered when counseling patients and parents of patients with hypospadias. METHODS: We conducted an IRB-approved survey study, which sampled the responses of Pediatric Urologists from National and International listservs. A google scholar search was performed using key words including "hypospadias" and "long-term complications." Descriptions of pertinent short, intermediate and long-term complications were identified and compiled from existing patient handouts. Survey items were then developed asking respondents to rate proposed descriptions, provide potential edits, and describe their overall approach to counseling. RESULTS: A total of 290 surgeons were contacted with 120 (41 %) responding. In total, 89 respondents (74 %) identified as male and 105 (88 %) had undergone a pediatric urology fellowship. Most surgeons described a reliance on verbal counseling (95 %) with the assistance of hand-drawn diagrams (75 %) to explain long-term care, rather than electronic or audiovisual materials (3-12 %). Of note, fewer surgeons endorsed routine discussion of long-term complications (Range 29.2 %-50.8 %) than shorter-term complications (56.7 %-89.2 %). On a Likert scale, physicians reported that they were mostly satisfied (72 %) with their current approaches to counseling. DISCUSSION: Perioperative counseling has an important yet often overlooked role in surgical care. The aim of this study was to better understand current counseling practices in pediatric hypospadias to identify gaps in urologic care and areas for improvement as one of the most common conditions treated by pediatric urologists. Our results suggest that surgeons who perform hypospadias repairs have potential to include more comprehensive discussion during post-operative follow-up. We proposed a preliminary counselling guide for these concerns which incorporates language from the most commonly selected complication description by survey respondents. Future studies will involve expert consensus and patient input to confirm the adequacy of the content, the method of delivery, content appearance, and accommodations for health literacy. Limitations of the study include small sample size and response bias. The results are reflective of the summed responses of participants and are not reflective of individual providers or practices. Importantly, this study omits the input of other advanced practice providers (nurse practitioners, physician assistants, etc.), nurses, and ancillary staff who are also crucial to hypospadias care. The proposed counseling guide represents a first attempt at creating standardization of hypospadias counseling. CONCLUSION: Surgeons who perform hypospadias repair do not routinely discuss long-term complications after repair, though are overall satisfied with their counseling practices. Better tools, such as improved multimodal counseling guides, could be used to deliver this counseling efficiently and accurately to ensure patients receive optimal long-term care. Future studies will focus on developing educational materials for short, intermediate, and long-term counseling on complications after hypospadias repair with input from patients and clinicians.

Humans

Cardiorespiratory training for people with stroke.

RATIONALE: Low levels of cardiorespiratory fitness are common after stroke and are associated with post-stroke disability and increased risk of secondary stroke. Cardiorespiratory training interventions aim to increase cardiorespiratory fitness, improve physical function, reduce disability, and help prevent future strokes. Clinical guidelines recommend exercise as part of lifestyle modification for secondary prevention, and strongly recommend exercise for rehabilitation. This review is one of three reviews that were originally a single review on physical fitness training for stroke. OBJECTIVES: The primary objective of this review was to determine whether cardiorespiratory training after stroke has an effect on death, disability, adverse events, risk factors, fitness, walking, and indices of physical function when compared to a non-exercise control. SEARCH METHODS: In April 2025, we searched nine bibliographic databases and two trials registers to identify studies for inclusion in the review. We checked reference lists, tracked citations, and contacted experts. ELIGIBILITY CRITERIA: We included randomised controlled trials comparing cardiorespiratory training interventions with usual care, no intervention, or a non-exercise intervention in people with stroke. OUTCOMES: Our critical outcomes were death, disability, adverse events, risk factors, fitness, walking, and indices of physical function, assessed at the end of the intervention and the end of the longest follow-up. RISK OF BIAS: We used the Cochrane RoB 1 tool to assess the risk of bias in the included studies. SYNTHESIS METHODS: The studies evaluated different comparisons (e.g. cardiorespiratory training versus no intervention/waiting list control or versus attention control or versus usual care), which we synthesised into a single comparison: cardiorespiratory training versus control. We used random-effects meta-analysis on arm-level data (risk difference (RD) for dichotomous data, and mean difference (MD) or standardised mean difference (SMD) for continuous data, with 95% confidence intervals (CIs)). For outcome data that we did not meta-analyse, we followed Synthesis Without Meta-analysis (SWiM) guidance. We used GRADE to assess the certainty of the evidence for critical outcomes. INCLUDED STUDIES: We included 53 studies (2672 participants, with an average age of 61.9 years). Most studies recruited ambulatory participants in the early subacute (7 days to 3 months) or chronic (> 6 months) phases of recovery. Exercise duration recommendations were met in 49 studies, and frequency recommendations in 48. Twenty-eight studies lacked balanced exposure between groups. Programme duration was 12 weeks or more in 16 studies (maximum: 24 weeks). Sixteen studies had a post-intervention follow-up period (12 weeks to 12 months from baseline). One study planned a six-month follow-up but did not report it. SYNTHESIS OF RESULTS: Cardiorespiratory training does not increase or decrease deaths at the end of intervention (RD 0.00, 95% CI -0.01 to 0.01; 36 studies, 1563 participants; high-certainty evidence) or the end of follow-up (RD -0.00, 95% CI -0.02 to 0.02; 10 studies, 713 participants; high-certainty evidence). Cardiorespiratory training may improve indices of disability slightly at the end of intervention (SMD 0.35, 95% CI 0.12 to 0.57; 17 studies, 1073 participants; very low-certainty evidence), but the evidence is very uncertain. Re-expressed using the Barthel Index (0 to 20), the equivalent effect is MD 1.68, 95% CI 0.59 to 2.74. It is unclear if the effect is clinically meaningful (the minimal clinically important difference (MCID) is +1.85). The effect is unclear at the end of follow-up (SMD -0.14, 95% CI -0.36 to 0.08; 5 studies, 347 participants; low-certainty evidence). Cardiorespiratory training does not increase or decrease the incidence of secondary cardiovascular or cerebrovascular events at the end of intervention (RD -0.00, 95% CI -0.03 to 0.02; 8 studies, 544 participants; high-certainty evidence) and probably does not affect them at the end of follow-up (RD -0.02, 95% CI -0.08 to 0.04; 4 studies, 412 participants; moderate-certainty evidence). It is very uncertain whether cardiorespiratory training affects systolic blood pressure (mmHg) at the end of intervention (MD -2.12, 95% CI -5.81 to 1.57; 9 studies, 535 participants; very low-certainty evidence) (MCID -2 mmHg) or follow-up (MD 0.93, 95% CI -4.30 to 6.16; 3 studies, 155 participants; very low-certainty evidence); the 95% CIs include the MCID. Cardiorespiratory training probably results in a slight improvement in cardiorespiratory fitness (VO2 ml/kg/min) at the end of intervention (MD 2.37, 95% CI 1.39 to 3.36; 13 studies, 608 participants; moderate-certainty evidence); it is unclear if the effect is clinically meaningful (MCID +3.5 ml/kg/min). The effect may be similar at the end of follow-up (MD 2.76, 95% CI 1.36 to 4.16; 5 studies, 237 participants; low-certainty evidence). Subgroup analysis favoured longer interventions. Cardiorespiratory training probably results in a slight increase in comfortable walking speed (metres per second) at the end of intervention (MD 0.08, 95% CI 0.04 to 0.12; 16 studies, 647 participants; moderate-certainty evidence), but the effect is not clinically meaningful (MCID +0.13). The effect is unclear at the end of follow-up (MD 0.02, 95% CI -0.05 to 0.10; 3 studies, 182 participants; low-certainty evidence). Cardiorespiratory training may improve indices of balance at the end of intervention (SMD 0.31, 95% CI 0.15 to 0.47; 18 studies, 772 participants; very low-certainty evidence), but the evidence is very uncertain. Re-expressing using the Berg Balance Scale, the equivalent effect is MD 2.09, 95% CI 1.10 to 3.07; and it is unclear if it is clinically meaningful (MCID of +2). The effect is unclear at the end of follow-up (MD 0.90, 95% CI -1.32 to 3.12; 6 studies, 253 participants; low-certainty evidence). Overall, our certainty about the evidence is limited for most outcomes by imprecision (small number of studies and participants) or risks of bias (e.g. imbalanced exposure doses) or both. AUTHORS' CONCLUSIONS: Cardiorespiratory training after stroke does not affect mortality or the incidence of secondary events at the end of the aerobic exercise training programme or end of follow-up. It may increase fitness, reduce disability, increase walking speed, and improve balance at the end of intervention, but it is unclear if these improvements are clinically meaningful. Further well-designed randomised trials are needed to fully understand the potential benefits and long-term effects of cardiorespiratory training and the optimal exercise prescription. FUNDING: No dedicated funding REGISTRATION: Protocol (and previous versions) available via DOI 10.1002/14651858.CD003316.

Humans