Association between aerobic exercise and vascular endothelial growth factor (VEGF) concentration in adults: a systematic review and meta-analysis of randomized controlled trials

Abstract

Purpose

This systematic review and meta-analysis aimed to assess the effect of aerobic exercise on circulating vascular endothelial growth factor (VEGF) levels in adults, given the inconsistent results in randomized controlled trials (RCTs), which is the basis for our investigation.

Methods

A comprehensive search of ISI Web of Science, PubMed/MEDLINE, and Scopus was conducted up to May 2025. Thirteen RCTs satisfied eligibility criteria. We performed a random-effects meta-analysis to estimate the overall Standrad mean difference (SMD) in VEGF between aerobic exercise group and control group. We conducted subgroup analyses dated on exercise intensity, duration, and biological sample (serum versus plasma).

Results

The results of the pooled analysis demonstrated no significant overall effect of aerobic exercise on circulating VEGF levels ) SMD: − 0.075; 95% CI: − 0.246 to 0.096; p = 0.390; I² = 32.9%; τ² = 0.030; PI = -0.5 to 0.35(. Observed reduction in VEGF levels occurred in the studies utilizing interventions with a duration of ≤ 8 weeks. Evidence certainty was rated as very low.

Conclusions

It appears that aerobic exercise does not have significant overall influence on circulating VEGF levels. However, VEGF reductions may subsequently occur after short-duration interventions. Further research is needed with larger high-quality RCTs to verify these associations and further explore the mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-026-01565-4.

Introduction

The importance of engaging in physical activity has been established through research, suggesting a potential relation to the development of new blood vessels, and growth of new nerve cells [1, 2]. Since angiogenesis cannot happen until vascular endothelial growth factor (VEGF) completes its functions, VEGF displays a very important connection between both processes of angiogenesis and neurogenesis [3, 4]. Lower amounts of neurotrophic factors, which provide growth support to neurons and reduce neurodegeneration, are correlated with brain neuropathy and cognitive decline. However, VEGF is associated with numerous indirect neuroprotective functions such as stock of the blood supply, supporting synaptic activity and cognition through brain plasticity [5]. However, many angiogenic factors shared by some adipogenesis or carcinogenesis include VEGF, the much more significant stimulator of angiogenesis [6]. In addition, VEGF can increase the motility, invasion, proliferation, and survival of cancerous cells [7].

It is still not completely clear how exercise positively affects cognitive capacity and other higher-level functions of the brain. Several possibilities exist, however, where angiogenic and neurotrophic factors, like VEGF, are a key factor [8, 9]. Angiogenesis, the process of new capillary formation from pre-existing blood vessels has been hypothesized as a potential mechanism but is yet to be explored that obesity can affect cancer development. Angiogenesis is determined by the balance of pro-angiogenic/anti-angiogenic factors and is required for tissue expansion. This is particularly important in obesity, due to the plasticity of adipose tissue, that remains dependent on vascularity for tissue expansion [10].

Aerobic exercise affects neurogenesis by stimulating secretion of VEGF from skeletal muscle cells, which is then released into circulation. The angiogenic expansion aided by physical exercise increases capillary surface area for oxygen (O₂) diffusion, facilitated by minimizing the distance between capillary expansion and potential targets, such as mitochondria, and therefore increasing aerobic capacity [11]. In addition to aerobic capacity, long-term aerobic exercise has been shown to lessen the effect of cognitive decline associated with aging [12, 13].

Given the conflicting evidence regarding the effects of aerobic exercise on vascular endothelial growth factor (VEGF), a comprehensive synthesis of the literature is required. Meta-analysis provides a systematic approach to summarize and evaluate all available findings, thereby offering greater clarity on this relationship. Accordingly, the present study conducted a meta-analysis to examine the effects of aerobic exercise on VEGF.

Method

This systematic review was performed according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach [14] and the recommendations of the Cochrane Handbook for Systematic Reviews of Interventions [15]. The study protocol was prospectively registered with the PROSPERO database (CRD42024533650). The review was conducted following the PRISMA guidelines, and the completed PRISMA checklist is provided in Table S1.

Search strategy

A thorough literature search was conducted from database inception to May 2025 in three electronic databases (ISI Web of Science, PubMed/MEDLINE, and Scopus). The search strategy incorporated a combination of medical subject headings (MeSH) and free-text terms, utilizing the following keywords: (“Exercise Therapy” OR “Exercise” OR “physical activity” OR “training” OR “aerobic exercise” OR “endurance training” OR “Progressive aerobic” OR “interval training” OR “continuous training”) AND (“VEGF” OR “Vascular Endothelial Growth Factors” OR “angiogenic growth factors” OR “Angiogenesis” OR “Angiogenic factor”). In addition, the reference lists of all eligible studies were manually reviewed to identify any further relevant publications. The full search strategy is provided in Table S2.

Study selection and data abstraction

Two reviewers (R.G. and S.B.) independently screened titles and abstracts, and performed full-text assessments for studies that met potential eligibility. Any conflicts in these processes were discussed and resolved with a third reviewer (R.S.). Only articles published in English were included in all stages of the review process. Studies were eligible for inclusion if they met the following criteria: we only included randomized controlled clinical trials (RCTs) of adults aged ≥ 18 years; interventions that compared types of aerobic activity; a minimum of 4-week duration of intervention; and a control group that reported the mean and standard deviations (SD) of VEGF for each group or containing sufficient data to calculate effect sizes. We considered trials with more than one intervention arm as separate RCTs. We excluded from the analysis observational studies, such as cohort, cross-sectional, case-control, or ecological studies, and also review articles. We also excluded trials for children or adolescents, without a control group, and those that did have randomization.

Data extraction and study quality

Two reviewers (AH.Z. and P.D.) independently extracted important data from each trial after full-text screening. The last name of the first author, publication year, country of population, sex, age, total sample size, exercise intensity, exercise load, comparison group, type of sample, duration of exercise, frequency of exercise, means of changes from baseline for outcomes in each group, and standard deviations (SDs) of changes from baseline for outcomes for each group were the important data initially pulled. A third reviewer (R.S.) was brought in to resolve disagreements. The methodological quality of the included cohort studies was appraised utilizing the Cochrane Risk of Bias Tool (RoB 2.0) [16]. This tool evaluates seven domains. Each domain was classified as “high risk” if the study had methodological weaknesses, “low risk” if no such flaws were present, and “unclear risk” if there was insufficient evidence to determine the impact. The overall bias risk for a randomized controlled trial was categorized as [1] low for all domains [2], moderate for unclear domains, and [3] high for domains that were deemed high risk. The bias risk assessment was conducted independently by two evaluators.

Statistical analysis

Mean changes and standard deviations (SDs) of VEGF levels for both the intervention and control groups were used to calculate effect sizes. When mean changes were not reported, they were estimated across the intervention period. Instances where standard error (SE), 95% confidence intervals (CIs), or interquartile ranges (IQRs) were provided, they were converted to SDs using the methods outlined by Hozo et al. [17]. Overall effect sizes were calculated using random-effects models to account for between-study variation.

To detect heterogeneity, Cochrane’s Q and the I² statistic were used, with p < 0.05 for the Q test or I² > 50% considered indicative of substantial heterogeneity [18]. Studies were clustered for subgroup analyses according to predefined variables, including the duration of the intervention (≤ 8 weeks vs. >8 weeks); duration of exercise sessions (≤ 40 min vs. >40 min); number of sessions per week (≤ 3 vs. >3 sessions/week); exercise load (≤ 150 min/week vs. >150 min/week); type of blood sample (serum vs. plasma); and exercise intensity (light, moderate, vigorous). In addition, random-effects meta-regression (REML) with Knapp–Hartung modification was performed to explore whether prespecified study-level moderators (intervention duration, sample type, exercise intensity, and other categorical covariates) explained between-study variability. Meta-regression analyses were weighted by within-study standard errors.

Exercise intensity categories were defined according to standardized ACSM thresholds [1]: light intensity as < 40% V̇O₂max, < 40% HRR, < 57% HRₘₐₓ, or RPE ≤ 11; moderate intensity as 40–59% V̇O₂max, 40–59% HRR, ~ 57–74% HRₘₐₓ, or RPE 12–13; and vigorous intensity as ≥ 60% V̇O₂max, ≥ 60% HRR, ≥ 75% HRₘₐₓ, or RPE ≥ 14. When trials reported more than one metric of intensity, the primary metric specified by the authors was used for classification.

Sensitivity analyses were conducted to examine the influence of individual studies on the pooled effect sizes. Publication bias was assessed using funnel plot symmetry and Egger’s regression [18]. All analyses were performed with StataCorp (version 17). A p-value of < 0.05 was considered statistically significant.

Certainty of evidence

The certainty of evidence for each outcome was evaluated using the GRADE methodology. The assessment considered key domains, including risk of bias, inconsistency, imprecision, indirectness, and potential publication bias [19]. The quality of evidence was categorized as high, moderate, low, or very low.

Results

Search results

The first search yielded 1,468 articles. After deleting 367 duplicates, 1,098 records remained for screening. Following the review of the titles and abstracts, 1,072 records were excluded for not meeting the criteria, leaving 26 articles for review of the full text. Of these studies, 10 trials were excluded for not having a control group, one study was excluded for measuring VEGF mRNA rather than VEGF protein, and two of the studies were excluded for being less than four weeks of intervention. Table S3 shows the excluded studies. A total 13 RCTs [20–32] met the eligibility criteria, and were included in the present systematic review and meta-analysis. Figure 1 provides an overview of the study selection process.

Fig. 1.

Literature search and study selection process

Study characteristics

The research studies included in this review consisted of 13 RCTs published between 2006 and 2020. The RCTs were performed in the United States [22, 23, 25], Europe [24, 26–30, 32], Asia [20, 21], and Australia [31]. In total, there were 997 participants from the studies and included 208 males and 789 female participants aged from 19 to 73 years old. Four trials included solely males [26, 28, 29, 32], four trials only included female participants [20–22, 25] and five studies included skeletal muscle, chronic disease, and female skeletal muscle with both sexes [23, 24, 27, 30, 31].

The length of intervention was a median of 12 weeks (range: 4–48 weeks). In total, twelve studies employed a parallel study design [20–29, 31, 32] and one study utilized a crossover study design [30]. One individual paper [22] applied aerobic exercise in combination with caloric restriction and aerobic exercise alone. Twelve trials examined aerobic exercise interventions alone [20, 21, 23–32] while one trial studied aerobic exercise in combination with caloric restriction [22].

The exercise sessions occurred during the RCTs and ranged from 20 to 67 min (median: 45 min), with bouts occurring three to seven times per week (median: four sessions per week). VEGF samples were taken from serum in eight trials [20–24, 26–28] and were taken from plasma in five trials [25, 29–32]. The trials were performed in healthy populations [20–22, 24, 25, 27, 32], patients with cardiovascular disease [26, 28–31], and patients with solid tumors [23]. The characteristics of the included studies are summarized in Table 1.

Table 1.

Characteristics of studies included in the meta-analysis of the effect of aerobic exercise on VEGF concentration

Author, year	Country	n(female)	Age, years	Health, status	Intervention	frequency	Duration	Intensity and volume	Outcome
Duggan et al., (2016) [22]	USA	IG: 116 (116) CG: 118 (118)	IG: 58 ± 4.5 CG: 58.1 ± 6	Healthy	IG: aerobic (NR) + diet CG: diet	5 days/ week	48 weeks	45 min, 70%-85% of MHR	VEGF (Serum)
Duggan et al., (2014) [25]	USA	IG: 85 (85) CG: 84 (84)	IG: 60.7 ± 6.7 CG: 60.6 ± 6.8	Healthy	IG: aerobic (NR) CG: sedentary	5 days/ week	48 weeks	45 min, 60%-75% of MHR	VEGF (Plasma)
Thijssen et al., (2006) [32]	Netherlands	IG: 8 (0) CG: 8 (0)	IG: (19–28) ± (NR) CG: (19–28) ± (NR)	Healthy	IG: aerobic (cycling) CG: sedentary	3 days/ week	8 weeks	20 min, 65% of HRR	VEGF (Plasma)
Kang et al., (2020) [20]	Korea	IG: 10 (10) CG: 10 (10)	IG: 73.83 ± 3.95 CG: 73.37 ± 4.19	Healthy	IG: aerobic (NR) CG: sedentary	3 days/ week	16 weeks	40 min, 40%-70% of MHR	VEGF (Serum)
Beck et al., (2012) [28]	Germany	IG: 20 (0) CG: 19 (0)	IG: 62 ± 8.94 CG: 63 ± 8.71	CAD	IG: aerobic (ergometer bike and ergometer row ) CG: sedentary	7 days/ week	4 weeks	30 min + 30 min, NR	VEGF (Serum)
Eleuteri et al., (2013) [26]	Italy	IG: 11 (0) CG: 10 (0)	IG: 66 ± 6.63 CG: 63 ± 6.32	CHF	IG: aerobic (ergometer bike) CG: sedentary	5 days/ week	6 weeks	30 min, 60 rev/min	VEGF (Serum)
Krogh et al., (2014) [24]	Denmark	IG: 41 (30) CG: 38 (23)	IG: 39 ± 11.7 CG: 43.8 ± 12.2	Healthy	IG: aerobic (stationary bike) CG: sedentary	3 days/ week	12 weeks	45 min, 80% of MHR	VEGF (Serum)
Cullberg et al., (2013) [27]	Denmark	IG: 21 (10) CG: 19 (10)	IG: 37.5 ± 7.6 CG: 35.6 ± 6.87	Healthy	IG: aerobic (NR) + diet CG: diet	3 days/ week	12 weeks	60–75 min, 70% of MHR	VEGF (Serum)
Glass et al., (2015) [23]	USA	IG: 23 (18) CG: 21 (18)	IG: 58 ± 10 CG: 54 ± 11	ST	IG: aerobic (ergometer bike) CG: sedentary	3 days/ week	12 weeks	20–45 min, 55%-65% of VO2 Peak	VEGF (Serum)
Sarto et al., (2007) [30]	Italy	IG: 22 (6) CG: 22 (6)	IG: 61.4 ± 7.5 CG: 61.4 ± 7.5	CHF	IG: aerobic (ergometer bike) CG: sedentary	3 days/ week	8 weeks	55 min, 60% of HRR	VEGF (Plasma)
Wood et al., (2006) [31]	Australia	IG: 7 (2) CG: 6 (2)	IG: 64 ± 6 CG: 56 ± 9	PAD	IG: aerobic (treadmill walking) CG: sedentary	3 days/ week	6 weeks	90 min, 80%-100% of VO2 Peak	VEGF (Plasma)
Erbs et al., (2010) [29]	Germany	IG: 18 (0) CG: 19 (0)	IG: 60 ± 11 CG: 62 ± 10	CHF	IG: aerobic (ergometer bike) CG: sedentary	7 days/ week	12 weeks	20–30 min, 60% of VO2 Max	VEGF (Plasma)
Cho et al., (2019) [21]	Korea	IG: 19 (19) CG: 18 (18)	IG: 68.89 ± 4.16 CG: 69 ± 4.41	Healthy	IG: aerobic (Taekwondo) CG: sedentary	5 days/ week	16 weeks	50 min, 50%-70% of MHR	VEGF (Serum)

Abbreviations: VEGF Vascular endothelial growth factor, IG Intervention group, CG Control group, CAD Coronary artery disease, PAD Peripheral artery disease, CHF Congestive heart failure, ST Solid tumors, MHR Maximum heart rate, HRR, Heart rate reserve.

Risk of bias assessment

Regarding the assessment of risk of bias, among the selected studies, a total of 11 studies were assessed as high risk of bias [20, 21, 23, 25–32], and two [22, 24] were assessed as low risk of bias. The domains most affected were Bias due to deviations from intended interventions, and Bias in measurement of the outcome. The risk of bias assessment summary is shown in Table S4. Based on the GRADE criteria, the confidence in the evidence was rated as very low (Table S5).

Meta-analysis, sensitivity Analysis, and publication bias

Pooled analysis of the included trials indicated that aerobic exercise did not statistically reduce VEGF levels compared to controls )Standard mean difference (SMD): − 0.075; 95% CI: − 0.246 to 0.096; p = 0.390; I² = 32.9%; τ² = 0.030; PI = -0.5 to 0.35( (Fig. 2).

Fig. 2.

Standard mean difference in VEGF concentration following aerobic exercise using a Random-effects model. Effect sizes are expressed as SMD (95% CI)

Subgroup analyses revealed statistically significant reductions in VEGF levels in the interventions lasting ≤ 8 weeks )SMD: -0.518 ; 95% CI: -1.033 to -0.003; P = 00.48; I² = 48.4%(. No significant differences were observed with respect to exercise load, exercise session duration, high-intensity exercise subgroup, plasma-derived VEGF subgroup, or frequency. The overall and subgroup analyses are reported in Table 2. Meta-regression analyses showed that intervention duration category was significantly associated with the effect size in the univariable model (β = −0.469, p = 0.039), indicating a decrease in effect size with increasing duration category. No significant associations were observed for sample type, intensity category, or other covariates (all p > 0.05). In the multivariable meta-regression model including all prespecified moderators, the joint test was not significant (p = 0.407), and none of the individual coefficients reached statistical significance.

Table 2.

Overall and subgroup analyses of the effectiveness of aerobic exercise on VEGF concentration

VEGF (all trials)	Effect sizes			Sample Size (Int/Con)	SMD (95% CI)	P_Value	I2 (%), Pheterogeneity	P for subgroup difference1
	14			997 (518/479)	-0.075 (-0.246, 0.096)	0.390	32.9%, < 0.112
Exercise load								0.112
≤ 150 min/week	6			193 (100/93)	-0.257 (-0718, 0.205)	0.275	52.7%, < 0.060
> 150 min/week	8			804 (418/386)	-0.030 (-0.185, 0.125)	0.706	12.3%, < 0.334
Exercise frequency								0.112
≤ 3 times/week	7			256 (132/124)	-3.41 (-0.723, 0.042)	0.081	51.3%, < 0.055
> 3 times/week	7			741 (386/355)	0.014 (-0.130, 0.159)	0.845	0%, < 0.776
Duration of exercise session								0.772
≤ 40 min	6			151 (77/74)	-1.93 (-0.767, 0.381)	0.509	64.3%, < 0.016
> 40 min	8			846 (441/405)	-0.50 (-0.185, 0.085)	0.468	0%, < 0.623
Exercise intensity								0.645
Low	3			80 (41/39)	0.116 (-0.325, 0.556)	0.606	0%, < 0.557
Moderate	6			343 (174/169)	-0.055 (-0.386, 0.276)	0.746	47%, < 0.093
High	5			574 (303/271)	-0.186 (-0.435, 0.099)	0.218	49.7%, < 0.093
Duration of intervention								0.112
≤ 8 weeks	5			133 (68/65)	-0.518 (-1.033, -0.003)	0.048	48.4%, < 0.101
> 8 weeks	9			864 (450/414)	0.002 (-0.132, 0.136)	0.979	0%, < 0.685
Blood sample								0.314
Serum	9			718 (378/340)	-0.018 (-0.165, 0.129)	0.809	0%, < 0.894
Plasma	5			279 (140/139)	-0.397 (-0.973 , 0.179)	0.176	73%, < 0.005

Abbreviations: VEGF Vascular endothelial growth factor, CI Confidence interval, SMD Standard mean difference

c. The 95% CI includes non-significant value and the OIS isn't met.

d. The total of 14 effect sizes for VEGF includes two independent comparisons from Duggan et al. (2016); thus, although 13 RCTs are included, 14 effect sizes are meta-analyzed for this outcome.

Sensitivity analyses indicated that the overall effect of aerobic exercise on VEGF levels was robust, with the exclusion of any single study not substantially modifying the summary estimates (range: -0.2915 to 0.1233). Assessment of publication bias showed no evidence of bias, as determined by funnel plot symmetry and Egger’s test (P = 0.341) (Figure S1).

Discussion

This meta-analysis assessed the impact of aerobic exercise on VEGF levels. Although subgroup analyses revealed reductions when interventions lasted ≤ 8 weeks, the overall pooled effect did not reach statistical significance. This finding indicates that, despite certain pattern emerging in specific subgroup, aerobic exercise alone does not appear to meaningfully influence circulating VEGF concentrations at the population level. Importantly, given the lack of statistical significance in the main effect and the very low certainty of evidence, these results should be interpreted with considerable caution.

VEGF is a principal angiogenic factor that encourages the development of new blood vessels from existing vasculature [33], which is necessary for tissue development and repair, and has been linked to cognitive enhancement [34] and neuroprotection [3]. In contrast, increasing evidence has associated aberrant VEGF expression with diseases such as obesity and tumor progression [7]. These varied and sometimes contradictory functions highlight the need to study how lifestyle factors, especially a component of aerobic physical activity, affect VEGF levels.

In past research, the relationship between exercise and changes in VEGF has produced conflicting results. Some studies have indicated exercise interventions are associated with increases [21], decreases [32], or no difference [32] in VEGF. As the main outcome for circulating VEGF, the current meta-analysis indicated that aerobic exercise produce a non-significant decrease in VEGF, contrary to the findings of previous meta-analysis reporting increases in VEGF with exercise [35]. For example, Pourvaghar et al. (2023) reported an increase in levels of VEGF with acute exercise, particularly strength exercise, in their meta-analysis [36]. Although our meta-analysis investigated long-term exercise, Pourvaghar et al. (2023) primarily included trials that tested individual bouts of exercise [36]. While acute bouts of exercise might cause a faster and acute response of VEGF, adaptations after long-term aerobic exercise may induce different regulatory responses [37].

The differences in overall intervention durations may have also resulted in different outcomes. Additionally, the analysis by Pourvaghar et al. (2023) examined a wider range of modes of exercise such as concurrent exercises and strength training, which may have influenced their overall conclusions [36]. In order to provide a more precise evaluation regarding the effect of aerobic exercise on VEGF, the selection of only aerobic exercise to be included in the meta-analysis was intentional. This restriction of the mode of exercise may have contributed to differences in the results. Furthermore, Song et al. (2024) performed a meta-analysis investigating exercise training on VEGF levels in patients with chronic heart failure and demonstrated a significant increase in VEGF levels after training [38]. However, Song et al. (2024) included studies which had different exercise modes, intensities, and durations which may have created heterogeneity and altered the overall effect [38].

A critical methodological consideration emerging from this review concerns the biological differences between serum and plasma VEGF. Serum VEGF concentrations are typically higher because platelets release substantial amounts of VEGF during the coagulation process. In contrast, plasma, particularly when platelet-poor, more accurately reflects circulating VEGF levels without platelet-driven contamination. These matrix-dependent differences may explain inconsistencies across studies and limit the comparability and generalizability of pooled VEGF outcomes. This highlights the importance of standardized blood sampling procedures in future trials assessing VEGF responses to exercise.

Strengths and limitations

This systematic review and meta-analysis has several strengths. To our knowledge, it is the first review focusing exclusively on randomized controlled trials that examined the effect of aerobic exercise on circulating VEGF levels in adults. The study applied a comprehensive search strategy across multiple databases, predefined eligibility criteria, and subgroup analyses according to exercise intensity, duration, and measurement matrix, enhancing the robustness of the findings. The use of GRADE methodology allowed a transparent assessment of the certainty of evidence.

Nevertheless, some limitations should be considered. The number of included trials was relatively small, and most had modest sample sizes, which may have limited the statistical power to detect significant effects. Considerable heterogeneity existed in exercise protocols, blood sampling techniques, and populations, which may have influenced pooled estimates. Furthermore, the overall certainty of evidence was rated as very low due to risk of bias, inconsistency, and imprecision across studies. Therefore, any conclusions drawn from this meta-analysis cannot be considered definitive and should be interpreted with caution. Additionally, only studies published in English were included, which may introduce language bias and limit generalizability. Finally, the results are restricted to short- and medium-term interventions, as long-term effects of aerobic exercise on VEGF remain largely unexplored.

Conclusion

Despite significant finding in duration of intervention subgroup, the overall pooled effect of aerobic exercise on circulating VEGF was not statistically significant. Reduction was more pronounced in duration of intervention, highlighting that differences in the duration of the intervention may influence results and should be considered in interpretation. Given the very low certainty of evidence, these findings should be interpreted with caution, and firm conclusions regarding the effect of aerobic exercise on VEGF cannot yet be drawn. Future high-quality randomized trials with standardized measurement methods and clearly defined training protocols are needed to clarify the dose–response relationship and potential long-term effects of aerobic exercise on VEGF regulation.

Abbreviations

VEGF

Vascular Endothelial Growth Factor

RCT

Randomized Controlled Trial

MD

Mean Difference

SMD

Standard Mean Difference

CI

Confidence Interval

ISI

Institute for Scientific Information

MEDLINE

Medical Literature Analysis and Retrieval System Online

GRADE

Grading of Recommendations Assessment, Development, and Evaluation

SE

Standard Error

SD

Standard Deviation

IQR

Interquartile Range

PROSPERO

International Prospective Register of Systematic Reviews

Authors’ contributions

AH.Z., R.G., S.B., P.D., N.A., N.Z., and A.A. led the data collection and drafting of the manuscript. R.A. provided scientific insight and helped edit and review the text. R.S. reviewed and revised the tables and manuscript. All authors read and approved the final version.

Funding

There was no funding for this project.

Competing interests.

The authors declare no competing interests.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Ethics approval was not required for this study. All participants provided written informed consent prior to participation. The study was conducted in accordance with the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.