Effects of vitamin D supplementation on inflammatory markers in heart failure: a systematic review and meta-analysis of randomized controlled trials

Vitamin D is reported to have anti-inflammatory properties; however the effects of vitamin D supplementation on inflammation in patients with heart failure (HF) have not been established. We performed a systematic review and meta-analysis examining effects of vitamin D supplementation on inflammatory markers in patients with HF. MEDLINE, CINAHL, EMBASE, All EBM, and Clinical Trials registries were systematically searched for RCTs from inception to 25 January 2017. Two independent reviewers screened all full text articles (no date or language limits) for RCTs reporting effects of vitamin D supplementation (any form, route, duration, and co-supplementation) compared with placebo or usual care on inflammatory markers in patients with heart failure. Two reviewers assessed risk of bias and quality using the grading of recommendations, assessment, development, and evaluation approach. Seven studies met inclusion criteria and six had data available for pooling (n = 1012). In meta-analyses, vitamin D-supplemented groups had lower concentrations of tumor necrosis factor-alpha (TNF-α) at follow-up compared with controls (n = 380; p = 0.04). There were no differences in C-reactive protein (n = 231), interleukin (IL)-10 (n = 247) or IL-6 (n = 154) between vitamin D and control groups (all p > 0.05). Our findings suggest that vitamin D supplementation may have specific, but modest effects on inflammatory markers in HF.


Strength of Evidence Interpretation
High quality Very confident in the estimate of the effect and further research is very unlikely to change our confidence.

Moderate quality
Moderately confident in the estimate of the effect, but further research may have an important impact on our confidence and may change the estimate.

Low quality
Somewhat confident in the estimate of the effect, but further research is very likely to have an important impact on our confidence and will likely change the estimate.

Very low quality
Very little confidence in the estimate of the effect as it is very uncertain.

Supplementary Table 4. Baseline participant characteristics and follow up biochemical analyses:
Data presented as mean ± standard deviation or median (interquartile range), unless otherwise specified.
Data not reported in published papers were obtained directly from corresponding authors. a data represents months and b weight (g) instead of years or BMI, respectively, for study in infants. Abbreviations: HF, heart failure; BMI, body mass index; I, intervention group; P, placebo/control group; NR, not reported; N/A, not applicable; 25(OH)D, 25-hydroxyvitamin D; CRP, C-reactive protein; IL, interleukin; TNF-α, tumor necrosis factor-alpha; FGF-23, fibroblast growth factor-23.

METHODS
Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.

[CRD:42016047753]
Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale. Table 1 Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

4
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

(Appendix 2)
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).

4
Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

5
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made. Table 1 Risk of bias in individual studies 12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

5
Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means). 5 Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I 2 ) for each meta-analysis.

Section/topic # Checklist item Reported on page #
Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).

5
Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.

RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
6 + Figure 1 Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations. 6-7 + Table 1 Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). 7, [9][10] Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.

DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).

10
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).

12-13
Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research.

11, 13
FUNDING Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review. For more information, visit: www.prisma-statement.org.