The protocol for this systematic review was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 10 April 2025 (Registration ID: CRD420251030235). The full registration details are publicly accessible through the PROSPERO database at https://www.crd.york.ac.uk/PROSPERO/myprospero (accessed during the protocol development phase).

Two reviewers independently extracted data using a piloted Excel template adapted from DECiMAL guidelines. Extracted variables included: (1)

Study ID (author/year)

Given the predominance of intra-participant comparator frameworks within the trial architectures, bias risk quantification was conducted through the Cochrane ROBINS-I instrument for non-randomized studies, while methodological rigor assessment leveraged the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for quasi-experimental investigations. Key appraisal criteria were used to assign quality ratings and scores to each study.

The Cochrane ROBINS-I instrument systematically evaluates methodological distortions across seven critical dimensions: (1)

Uncontrolled confounding variables

The JBI critical appraisal checklist includes the following criteria: 1.

Appropriateness of study design

This investigation quantified core pulmonary responses to functional electrical stimulation (FES) in spinal cord injury patients through four principal biomarkers: forced vital capacity (FVC), peak expiratory flow (PEF), and maximum pressure thresholds during expiration/inspiration (MEP/MIP).Aerobic capacity parameters, including peak ventilation (VE) and peak oxygen uptake (VO2peak), were also assessed to determine the impact of combined exercise interventions (Table 1).

Evidence synthesis was operationalized through Cochrane Review Manager 5.4 (RRID: SCR_003581) under continuous measurement paradigms, with all endpoints undergoing interval-scale normalization. Restricted maximum likelihood (REML) estimation procedures were implemented for between-study variance components, accompanied by prediction interval construction for clinical interpretability enhancement. When studies used the same measurement methods and units, the mean difference (MD) and 95% confidence interval (CI) were used as the effect size. When measurement methods or units differed, the standardized mean difference (SMD) and 95% CI were used. Heterogeneity among studies was assessed using the χ2 test (significance level α = 0.1). A fixed-effects model was used when P ≥ 0.1 and I² < 50%, indicating low heterogeneity. A random-effects model was used when P < 0.1 and I² ≥ 50%, Continuous outcomes: Standardized mean difference (SMD) with 95% CI using:Fixed-effects model (I² < 50%, p ≥ 0.1)Random-effects model (I² ≥ 50%, p < 0.1) Sensitivity analyses excluded studies with high ROBINS-I bias Publication bias: Egger's test (p < 0.05 considered significant) Sensitivity analyses were conducted to assess the robustness of the pooled estimates. These included: (a) Leave-one-out validation: Systematically excluding one study at a time to quantify its influence on the composite effect magnitude. (b) Stratified sensitivity analysis based on methodological quality: Studies were stratified based on their risk of bias assessment (e.g., “low risk of bias” vs. “moderate/high/critical risk of bias” as determined by ROBINS-I and/or JBI appraisals). The pooled effect sizes were then re-calculated for subgroups of higher-quality studies, or by excluding studies with a high risk of bias/low methodological quality, to ascertain the impact of study quality on the overall findings. Indicating substantial heterogeneity. Stratified covariate interrogation was conducted through Bayesian multilevel modeling to identify moderator variables contributing to inter-study variance. Robustness validation employed iterative leave-one-out validation protocols, systematically excluding singular datasets to quantify their influence on composite effect magnitude. For outcomes demonstrating significant dispersion metrics (I² ≥ 50%), publication bias diagnostics were implemented via radial regression asymmetry profiling (Egger's test equivalence), with all inferential analyses maintaining Bonferroni-adjusted α thresholds of 0.05 for two-tailed hypothesis testing.

To address potential ambiguity, it is noted that control groups in the included primary studies varied. For analyses of “FES alone,” the comparators (termed “non-FES” in forest plots) included sham FES, no intervention, or standard care without FES. For analyses of “FES combined with exercise,” the comparators (termed “non-FES exercise” or similar) consisted of the equivalent exercise modality (e.g., rowing, cycling) performed without FES.

The initial search identified 1005 articles. After removing duplicates using EndNote 21 and screening titles and abstracts for relevance, 29 articles were considered potentially eligible. Following full-text review, 23 articles met the inclusion criteria and were included in the meta-analysis (Figure 3).

The final analysis comprised 23 articles, with 3 identified through supplementary searches. Twelve studies investigated the effect of functional electrical stimulation (FES) on respiratory function in individuals with spinal cord injury (SCI) (8, 13, 18–26, 41), while 11 examined the effect of FES combined with exercise on aerobic capacity (27–36). Among the 12 exclusive FES trials, outcome documentation frequencies were distributed as: 8 investigations quantified peak airflow rates (PEF), 5 assessed expiratory force thresholds (MEP), 4 evaluated forced breathing capacity (FVC), and 2 measured inspiratory pressure limits (MIP). The 11 exercise-combined FES protocols incorporated rowing-based (n = 7) and cycling-focused (n = 4) interventions. A subset of six rowing investigations concurrently measured ventilatory output maxima (VE) and maximal aerobic capacity (VO2peak).Outcome reporting was less consistent for cycling, with 2 studies reporting VO2peak and 2 reporting VE. Detailed characteristics of the included studies are presented in Tables 2, 3.

The initial search identified 1,005 articles. After removing duplicates using EndNote 21 and screening titles and abstracts for relevance, 29 articles underwent full-text assessment. After comprehensive full-text appraisal, 9 manuscripts were disqualified during quality triage, retaining 20 investigations meeting phase I eligibility thresholds. Post hoc incorporation of 3 supplemental datasets was achieved through supplementary retrieval protocols (including citation tracking and grey literature mining), culminating in 23 methodologically validated studies for quantitative synthesis, as delineated in the PRISMA flow diagram (Figure 3).

Funnel plots were generated using RevMan 5.4 software to assess publication bias for outcome measures related to respiratory function (FVC, PEF, MEP, MIP) and aerobic capacity (VEpeak, VO2peak). These plots are provided in Supplementary Figures S1–S8. Visual inspection of the funnel plots for MEP and FVC revealed relative symmetry, suggesting a low likelihood of publication bias. This was supported by non-significant Egger's regression test results (P > 0.05 for both). In contrast, the funnel plots for PEF, MIP, VEpeak (rowing), and VO2peak (rowing) exhibited some asymmetry, suggesting a potential risk of publication bias. Egger's tests for these outcomes were statistically significant (P < 0.05), supporting the visual interpretation of asymmetry and suggesting that smaller studies showing no significant effects might be underrepresented in the literature for these specific outcomes. The analyses for VEpeak (cycling) and VO2peak (cycling) involved only two studies, making formal assessment of publication bias challenging and less reliable; however, caution is warranted (Figures 4–11). These plots are provided in Supplementary Figures S1–S8.

Leave-One-Out Analysis: For outcomes with high heterogeneity, a leave-one-out sensitivity analysis was performed. In the analysis of FES-assisted rowing on VO₂peak, initial heterogeneity was substantial (I² = 69%). The exclusion of the Laskin et al. study, which lacked detailed protocol information, significantly reduced heterogeneity to I² = 0% (p = 0.99) and maintained the statistical significance of the pooled effect. This suggests the findings are robust, but highlights the influence of outlier studies.

Stratified Analysis by Study Quality: We also conducted a sensitivity analysis stratified by study quality. We recalculated the pooled estimates after excluding studies deemed to have a “high” or “critical” risk of bias. For the primary outcomes (PEF, MEP, FVC, and VO₂peak), the direction and significance of the effects remained consistent. For example, the SMD for MEP, when restricted to studies with low-to-moderate risk of bias, remained large and statistically significant [SMD = 0.89, 95% CI (0.21, 1.57)]. This stability increases our confidence in the validity of the overall conclusions.

The observed improvements in FVC, PEF, and MEP align with the proposed mechanism of abdominal FES. By inducing contraction of the abdominal muscles, FES increases intra-abdominal pressure, leading to a cephalad displacement of the diaphragm. This action augments expiratory force, facilitating more complete lung emptying and thereby directly improving MEP and indirectly FVC (8, 19, 20, 23). For instance, the pooled SMD for PEF (0.42) corresponded to an approximate improvement of 0.8 L/s, exceeding the minimal important difference (MID) of 0.5 L/s and suggesting a clinically relevant enhancement in the ability to generate forceful exhalations. Similarly, the large effect size for MEP (SMD = 0.93) indicates a substantial increase in expiratory muscle strength, which is a critical factor for effective cough and airway clearance, and has been identified as an independent predictor of successful extubation and reduced morbidity (17). The improvement in FVC further supports the notion that FES can enhance overall lung volumes accessible for ventilation in individuals with SCI. These findings are consistent with previous research, such as Langbein et al. (22), who also reported FVC and PEF improvements with FES in SCI. The enhanced PEF is particularly noteworthy as it reflects cough effectiveness, crucial for preventing respiratory complications like pneumonia, a leading cause of rehospitalization (3, 41).

In contrast to expiratory measures, this meta-analysis, based on two studies (8, 18), did not find a significant effect of FES on MIP. This lack of effect might be attributed to the primary mechanism of abdominal FES, which directly targets expiratory musculature. Any impact on inspiration is likely indirect, resulting from changes in resting lung volume or diaphragm positioning, rather than direct strengthening of inspiratory muscles like the diaphragm or pectoralis major (unless specifically targeted). The conflicting findings between the included studies [Euan et al. (8) showing no effect with abdominal FES vs. Pao et al. (18) showing improvement with pectoral and abdominal FES] further underscore the uncertainty. Differences in patient populations (critically ill vs. stable tetraplegia) and FES protocols (abdominal only vs. combined pectoral/abdominal) likely contributed to this heterogeneity. Given that MIP reflects inspiratory muscle strength (42), a key indicator for pneumonia risk (10), the precise role of FES, particularly different FES configurations, in modulating MIP warrants further dedicated investigation with standardized protocols.

Our analysis of FES combined with exercise therapies revealed promising, albeit varied, results. Specifically, FES combined with rowing (seven studies) significantly improved VO2peak, suggesting an enhancement in aerobic capacity. This is a clinically important finding, as improved aerobic capacity can translate to greater independence in daily activities and reduced cardiovascular risk in the SCI population (6). The mechanism likely involves FES-induced activation of paralyzed lower limb muscles, augmenting the overall muscle mass contributing to exercise, thereby increasing metabolic demand and central cardiovascular responses (39). However, significant heterogeneity was observed for this outcome, partially attributable to variations in training protocols and stimulation parameters across studies, as exemplified by the Laskin et al. (33) study. When FES was combined with cycling (two studies), a significant improvement in VO2peak was also noted, though based on a smaller evidence base.

The effect of FES-exercise on VEpeak was not statistically significant for either rowing or cycling combinations in this meta-analysis. While positive SMDs were observed, the limited number of studies and wide confidence intervals prevent definitive conclusions. This highlights a need for more research with larger sample sizes to clarify the impact of combined FES-exercise on ventilatory responses during peak exertion.

The choice between FES-rowing and FES-cycling as adjunctive therapies involves several practical considerations, informed by the characteristics of participants in the studies included in this meta-analysis.

Injury Level: Observations from the included literature suggest different suitability based on the level of injury. FES-cycling training was predominantly studied in individuals with spinal cord injury at or below the T1 level. Conversely, FES-rowing training has been investigated in participant cohorts that included individuals with injuries at higher thoracic levels reported in studies such as (34, 36, 40, 43). This suggests that FES-cycling may be more frequently applied or considered for individuals with lower-level injuries, while FES-rowing has demonstrated feasibility in populations with higher injury levels. Careful patient selection and protocol adaptation remain crucial regardless of the modality.

This meta-analysis has several limitations that should be acknowledged. The number of studies included for some outcomes, particularly FES combined with cycling and the MIP analysis, was small, limiting the statistical power and robustness of these specific findings. Heterogeneity was present in some analyses, particularly for VO2peak with FES-rowing, likely due to variations in FES parameters, exercise protocols, intervention durations, and patient characteristics across studies. While we addressed this where possible, residual heterogeneity warrants cautious interpretation. Furthermore, as noted in our results, potential publication bias cannot be ruled out for certain outcomes.

In summary, this meta-analysis provides quantitative evidence supporting the use of FES to improve crucial expiratory respiratory functions in individuals with SCI. The combination of FES with exercise, particularly rowing and cycling, also shows promise for enhancing aerobic capacity. However, the evidence base for some outcomes is still developing, and further research is essential.