The Comparative Effects of Different Types of Oral Vitamin Supplements on Arterial Stiffness: A Network Meta-Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Search Strategy
2.2. Eligibility
2.3. Study Selection and Data Extraction
2.4. Risk of Bias Assessment
2.5. Grading the Quality of Evidence
2.6. Data Synthesis and Statistical Analysis
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- First, we used a network geometry graph to depict the trials in the network. In this graph, the size of the nodes was relative to the number of participants in trials receiving the intervention identified in the node, and the width of the solid line connecting the nodes was relative to the number of participants in trials directly comparing the two interventions. Dashed lines depict indirect comparisons between two interventions [28].
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- Second, the consistency assessment tested whether the intervention effect calculated from direct comparisons was robust with those calculated by indirect comparisons. For this purpose, we used the Wald test, and we evaluated local inconsistency using the side-splitting method.
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- Third, we performed a comparative assessment of the intervention effect by performing a standard pairwise meta-analysis for comparisons between interventions and placebo/other interventions. For this purpose, we used the DerSimonian–Laird random-effects method [29] to calculate a pooled effect size (ES) estimate and the respective 95% confidence intervals (CIs), and we estimated the pooled percentage change in m/s for oral vitamin supplement interventions. We examined statistical heterogeneity by calculating the I2 statistic, ranging from 0% to 100%. Depending on the I2values, heterogeneity was classified as unimportant (0% to 30%), moderate (30% to 50%), substantial (50% to 75%), or considerable (75% to 100%) [25]. In addition, we considered the corresponding p values. Finally, we calculated the statistic τ2 to establish the size and clinical relevance of heterogeneity. A τ2 estimate of 0.04 can be considered as low, 0.14 as moderate, and 0.40 as a substantial degree of the clinical relevance of heterogeneity [30]. We created both forest plots and a league table to depict these results.
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- Fourth, we calculated the effect of each intervention using NMA with a frequentist perspective [31]. Frequentist perspective draws a conclusion based on the level of statistical significance and the acceptance or rejection of a hypothesis.
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- Fifth, we used sensitivity, subgroup, and meta-regression analyses for the transitivity evaluation, and we verified that all study participants included in the NMA had, on average, a similar baseline effect distribution. We conducted a sensitivity analysis (systematic reanalysis while eliminating studies one at a time) to evaluate the strength of the summary estimates. We used subgroup analyses based on the mean population age (<65 years or >65 years), intervention length (<12 weeks or >12 weeks), vitamin type (water-soluble (vitamin B9 and vitamin C) or fat-soluble (vitamin D, vitamin D2, vitamin D3, and vitamin E)), and PWv type (central PWv (a-PWv and cf.-PWv) or peripheral PWv (ba-PWv, br-PWv, and cr-PWv)). We performed meta-regression analyses to address whether the mean age and intervention length, as continuous variables, modified the effect of oral vitamin supplementation interventions on PWv.
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- Finally, publication bias was assessed through visual inspection of the funnel plots, and Egger’s test [33].
Reference | Country | Population Characteristics | Intervention Characteristics | Outcome: Arterial Stiffness | |||||||
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Sample Size (% Female) | Mean Age (Years) | Type of Population | Type of Vitamins | Oral Supplement dose (Frequency) | Length (Weeks) | Type of PWv | PWv Device | Basal PWv Levels (m/s) | % Change (m/s) | ||
Mangoni et al., 2002 [34] | United Kingdom | IG: 12 (66.7) CG: 12 (58.3) | IG: 39.7 ± 11.9 CG: 36.0 ± 12.6 | Healthy | Folic acid (vit. B9) | 5 mg (daily) | 4 | cf-PWv | Complior | IG: 8.4 ± 1.8 CG: 8.3 ± 1.1 | IG: −7.1% CG: −6.0% |
Mangoni et al., 2005 [35] | United Kingdom | IG: 13 (38.5) CG: 13 (53.8) | IG: 55. 3 ± 4.3 CG: 57.6 ± 4.7 | DM2 | Folic acid (vit. B9) | 5 mg (daily) | 4 | cf-PWv | Complior | IG: 10.8 ± 2.5 CG: 10.9 ± 2.9 | IG: −1.0% CG: 2.8% |
Nightingale et al., 2003 [36] | United Kingdom | IG: 23 (26.1) CG: 15 (26.7) | IG: 57.8 ± 9.9 CG: 60.9 ± 6.3 | CHF | Ascorbic acid (vit. C) | 4 g (daily) | 4 | br-PWv | QVLP84 | IG: 7.8 ± 1.9 CG: 7.6 ± 0.9 | IG: 6.8% CG: 5.4% |
Nightingale et al., 2007 [37] | United Kingdom | IG: 19 (15.8) CG: 18 (16.7) | IG: 64.0 ± 8.7 CG: 63.0 ± 8.5 | CHF | Ascorbic acid (vit. C) | 4 g (daily) | 4 | ba-PWv | QVLP84 | IG: 9.8 ± 2.6 CG: 9.7 ± 3.8 | IG: 92.0% CG: −27.0% |
Dreyer et al., 2014 [38] | United Kingdom | IG: 20 (39.1) CG: 18 (26.3) | IG: 45.8 ± 10.0 CG: 48.8 ± 12.2 | CKD | Ergocalciferol (vit. D2) | 50,000 IU (weekly for one month) + 50,000 IU (monthly) | 16 | a-PWv | Vicorder | IG: 8.5 ± 1.1 CG: 8.5 ± 1.5 | IG: −1.2% CG: 0.0% |
Kovesdy et al., 2012 [39] | United States | IG1: 40 (0.0) IG2: 40 (2.0) | IG1: 67.6 ± 9.3 IG2: 69.3 ± 10.6 | CKD | IG1: Ergocalciferol (vit. D2) IG2: Cholecalciferol (vit. D3) | IG1: 50,000 IU (single dose) IG2: 1 or 2 µg (daily) | 16 | a-PWv | Sphygmocor | IG1: 12.8 ± 3.5 IG2: 13.5 ± 3.9 | IG1: 1.6% IG2: −1.5% |
Forouhi et al., 2016 [40] | United Kingdom | IG1: 112 (43.8) IG2: 114 (43.0) CG: 114 (42.1) | IG1: 53.5 ± 8.7 IG2: 52.5 ± 8.2 CG: 52.4 ± 8.5 | Pre-DM2 | IG1: Ergocalciferol (vit. D2) IG2: Cholecalciferol (vit. D3) | IG1: 3300 IU (daily) IG2: 3300 IU (daily) | 16 | cf-PWv | Doppler MDII | IG1: 7.3 ± 2.7 IG2: 7.9 ± 2.0 CG: 7.4 ± 2.0 | IG1: −2.3% IG2: −9.5% CG: 4.9% |
Larsen et al., 2012 [41] | Denmark | IG: 55 (70.0) CG: 57 (68.0) | IG: 60.0 ± 12.0 CG: 61.9 ± 9.0 | HT | Cholecalciferol (vit. D3) | 3000 IU (daily) | 20 | cf-PWv | SphygmoCor | IG: 8.5 ± 2.3 CG: 8.7 ± 2.1 | IG: 5.9% CG: 3.5% |
Marckmann et al., 2012 [42] | Denmark | IG: 26 (26.9) CG: 26 (23.1) | IG: 71 (62–78) CG: 68 (59–76) | CKD | Cholecalciferol (vit. D3) | 40,000 IU (weekly) | 8 | a-PWv | Millar SPT-301B | IG: 12. 0 (9.0–13.9) CG: 10.0 (7.8–13.2) | IG: 5.8% CG: −3.0% |
Hewitt et al., 2013 [43] | Australia | IG: 30 (47) CG: 30 (57) | IG: 60 (53–71) CG: 67 (54–72) | CKD | Cholecalciferol (vit. D3) | 50,000 IU (weekly for two months) + 50,000 IU (monthly) | 24 | cf-PWv | SphygmoCor | IG: 10.3 ± 4.0 CG: 10.3 ± 4.0 | IG: −9.7% CG: 1.9% |
Witham et al., 2013 [44] | United Kingdom | IG: 24 (100.0) CG: 25 (100.0) | IG: 41.7 ± 13.4 CG: 39.4 ± 11.8 | Healthy | Cholecalciferol (vit. D3) | 100,000 IU (single dose) | 8 | cr-PWv | SphygmoCor | IG: 8.0 ± 1.2 CG: 7.7 ± 1.7 | IG: 6.3% CG: −3.9% |
Mose et al., 2014 [45] | Denmark | IG: 25 (32.0) CG: 25 (40.0) | IG: 68.0 ± 9.0 CG: 67.0 ± 13.0 | CKD | Cholecalciferol (vit. D3) | 3000 IU (daily) | 24 | cf-PWv | SphygmoCor | IG: 9.7 ± 2.5 CG: 10.0 ± 2.0 | IG: 8.2% CG: 1.0% |
Pilz et al., 2015 [46] | Germany | IG: 100 (46.0) CG: 199 (48.0) | IG: 60.5 ± 10.9 CG: 59.7 ± 11.4 | HT | Cholecalciferol (vit. D3) | 2800 IU (daily) | 8 | NA | NA | IG: 8.4 ± 2.0 CG: 8.3 ± 2.1 | IG: 1.0% CG: 4.1% |
Witham et al., 2015 [47] | United Kingdom | IG: 25 (72.0) CG: 25 (80.0) | IG: 48.1 ± 12.0 CG: 50.7 ± 13.1 | Chronic fatigue syndrome | Cholecalciferol (vit. D3) | 100,000 IU (single dose) | 24 | cf-PWv | SphygmoCor | IG: 7.3 ± 2.6 CG: 8.3 ± 1.9 | IG: −5.5% CG: −2.4% |
Bressendorff et al., 2016 [48] | Denmark | IG: 22 (50) CG: 18 (34) | IG: 41.0 ± 9.1 CG: 44.5 ± 8.5 | Healthy | Cholecalciferol (vit. D3) | 3000 IU (daily) | 16 | cf-PWv | SphygmoCor | IG: 6.4 ± 1.4 CG: 6.7 ± 0.9 | IG: 0.0% CG: −1.5% |
Kumar et al., 2017 [49] | United Kingdom | IG: 58 (29.3) CG: 59 (32.2) | IG: 43.2 ± 11.8 CG: 45.2 ± 11.6 | CKD | Cholecalciferol (vit. D3) | 300,000 IU (two doses: baseline and 8weeks) | 16 | cf-PWv | SphygmoCor | IG: 8.0 ± 1.6 CG: 8.0 ± 1.7 | IG: −11.8% CG: 3.8% |
Sluyter et al., 2017 [50] | New Zealand | IG: 256 (40.0) CG: 261 (48.0) | IG: 64.5 ± 8.3 CG: 65.5 ± 8.8 | HT, DM | Cholecalciferol (vit. D3) | 200,000 IU (single dose) + 100,000 IU (monthly) | 48 | a-PWv | Mobil-O-Graph | IG: 9.3 ± 1.7 CG: 9.3 ± 1.7 | IG: −1.1% CG: 0.0% |
Gepner et al., 2012 [51] | United States | IG: 57 (100) CG: 57 (100) | IG: 64.1 ± 3.0 CG: 63.6 ± 3.1 | Postmenopausal | Cholecalciferol (vit. D3) | 2500 IU (daily) | 16 | cf-PWv | SphygmoCor | IG: 7.8 ± 0.9 CG: 8.0 ± 1.4 | IG: -1.0% CG: 0.0% |
Levin et al., 2017 [52] | Canada | IG1: 39 (28.0) IG2: 40 (30.0) CG: 40 (27.0) | IG1: 66.9 ± 11.7 IG2: 65.9 ± 15.3 CG: 64.5 ± 12.2 | CKD | IG1: Calcitriol (vit. D) IG2: Cholecalciferol (vit. D3) | IG1: 0.5 µg (thrice weekly) IG2: 5000 IU (thrice weekly) | 24 | cf-PWv | SphygmoCor | IG1: 11.6 ± 3.8 IG2: 12.2 ± 4.2 CG: 10.7 ± 3.7 | IG1: 5.2% IG2: 1.6% CG: −1.0% |
Tomson et al., 2017 [53] | United Kingdom | IG1: 102 (49.0) IG2: 102 (50.0) CG: 101 (49.0) | IG1: 71.0 ± 6.0 IG2: 72.0 ± 6.0 CG: 72.0 ± 6.0 | HT, heart disease, DM, stroke | Cholecalciferol (vit. D3) | IG1: 4000 IU (daily) IG2: 2000 IU (daily) | 24 | a-PWv | Arteriograph | IG1: 10.0 ± 1.9 IG2: 9.6 ± 1.6 CG: 9.7 ± 1.8 | IG1: −2.0% IG2: 3.1% CG: 2.1% |
Rasool et al., 2006 [54] | Malaysia | IG1: 9 (0.0) IG2: 9 (0.0) IG3: 9 (0.0) CG: 9 (0.0) | IG1: 21–30 IG2: 21–30 IG3: 21–30 CG: 21–30 | Healthy | Tocotrienol (vit. E) | IG1: 80 mg (daily) IG2: 160 mg (daily) IG3: 320 mg (daily) | 8 | cf-PWv | SphygmoCor | IG1: 7.4 ± 0.7 IG2: 7.8 ± 0.7 IG3: 7.5 ± 0.6 CG: 7.8 ± 0.8 | IG1: 1.3% IG2: −2.6% IG3: −4.0% CG: −1.3% |
Stonehouse et al., 2016 [55] | Australia | IG: 28 (35.7) CG: 29 (37.9) | IG: 60.5 (56.5–65.8) CG: 61.0 (56.0–64.0) | DM2 | Tocotrienol (vit. E) | 420 mg (daily) | 8 | cf-PWv | Millar SPT-301 | IG: 6.8 (5.9–7.6) CG: 7.2 (6.3–8.1) | IG: −7.0% CG: −13.3% |
3. Results
3.1. Study Characteristics
3.2. Risk of Bias and GRADE
3.3. Effect of Oral Vitamin Supplementation on Arterial Stiffness
3.4. Probabilities
3.5. Sensitivity Analysis, Subgroup Analyses, Meta-Regression Models, and Publication Bias
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Placebo | −0.14 (−0.69, 0.42) | 0.17 (−0.29, 0.63) | −0.04 (−0.56, 0.47) | −0.24 (−0.50, 0.01) | −0.08 (−0.24, 0.08) | 0.20 (−0.17, 0.58) |
−0.13 (−1.02, 0.77) | Folic acid (vit. B9) | NA | NA | NA | NA | NA |
0.36 (−0.52, 1.24) | 0.49 (−0.77, 1.74) | Ascorbic acid (vit. C) | NA | NA | NA | NA |
−0.01 (−0.63, 0.61) | 0.12 (−0.97, 1.21) | −0.37 (−1.44, 0.71) | Calcitriol (vit. D) | NA | −0.32 (−0.84, 0.20) | NA |
−0.10 (−0.73, 0.54) | 0.03 (−1.07, 1.13) | −0.45 (−1.54, 0.63) | −0.09 (−0.96, 0.79) | Ergocalciferol (vit. D2) | −0.25 (−0.48, −0.02) | NA |
−0.21 (−0.54, 0.11) | −0.09 (−1.04, 0.86) | −0.57 (−1.51, 0.36) | −0.21 (−0.87, 0.45) | −0.12 (−0.76, 0.52) | Cholecalciferol (vit. D3) | NA |
0.28 (−0.36, 0.92) | 0.41 (−0.69, 1.51) | −0.08 (−1.17, 1.01) | 0.29 (−0.60, 1.18) | 0.38 (−0.53, 1.28) | 0.50 (−0.22, 1.22) | Tocotrienol (vit. E) |
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Saz-Lara, A.; Cavero-Redondo, I.; Martínez-Vizcaíno, V.; Martínez-Ortega, I.A.; Notario-Pacheco, B.; Pascual-Morena, C. The Comparative Effects of Different Types of Oral Vitamin Supplements on Arterial Stiffness: A Network Meta-Analysis. Nutrients 2022, 14, 1009. https://doi.org/10.3390/nu14051009
Saz-Lara A, Cavero-Redondo I, Martínez-Vizcaíno V, Martínez-Ortega IA, Notario-Pacheco B, Pascual-Morena C. The Comparative Effects of Different Types of Oral Vitamin Supplements on Arterial Stiffness: A Network Meta-Analysis. Nutrients. 2022; 14(5):1009. https://doi.org/10.3390/nu14051009
Chicago/Turabian StyleSaz-Lara, Alicia, Iván Cavero-Redondo, Vicente Martínez-Vizcaíno, Isabel Antonia Martínez-Ortega, Blanca Notario-Pacheco, and Carlos Pascual-Morena. 2022. "The Comparative Effects of Different Types of Oral Vitamin Supplements on Arterial Stiffness: A Network Meta-Analysis" Nutrients 14, no. 5: 1009. https://doi.org/10.3390/nu14051009
APA StyleSaz-Lara, A., Cavero-Redondo, I., Martínez-Vizcaíno, V., Martínez-Ortega, I. A., Notario-Pacheco, B., & Pascual-Morena, C. (2022). The Comparative Effects of Different Types of Oral Vitamin Supplements on Arterial Stiffness: A Network Meta-Analysis. Nutrients, 14(5), 1009. https://doi.org/10.3390/nu14051009