The search strategy will be designed and conducted in collaboration with an experienced reference librarian of the HES-University of Applied Sciences and Arts Western Switzerland, Geneva (MP) in consultation with the authors. To guide the electronic literature search strategies we will use the Peer Review of Electronic Search Strategies (PRESS) 2015 Guideline Statement (17). To construct a comprehensive set of possible search terms, we will apply controlled vocabulary (eg. Medical Subject Headings terms) with key words both in full and in various truncations (see Table 1). Additionally we will use Boolean operators and proximity operators, including wildcards, AND, OR, parentheses, and quotations for each data base. The initial search strategy was designed and piloted on September 2nd 2020 and tested for possible study volume on September 7th 2020. We will run the searches firstly with research design filters and then with extensive qualitative filters applied. Table 2 summarizes the search strategy applied for Medline and CINAHL electronic data bases.
Table 2
Date
|
Data base
|
Search
|
Filters or limits
|
Number of studies
|
07.09.2020
|
Medline (PubMed)
|
("venous leg ulcer*"[Title/Abstract] OR ("varicose ulcer"[MeSH Terms] AND "leg ulcer"[MeSH Terms])) AND ("prevalence"[Title] OR "incidence"[Title] OR "occurrence"[Title] OR "epidemiolog*"[Title])
|
none
|
54
|
07.09.2020
|
Cinahl
|
(TI "venous leg ulcer*" OR AB "venous leg ulcer*" OR ((MH "Venous Ulcer") AND (MH "Leg ulcer"))) AND (TI prevalence OR TI incidence OR TI occurrence OR TI epidemiolog*)
|
none
|
21
|
Study records
Data management:
We will import all references into one single EndNote library version X8. Titles will be de-duplicated once entered into EndNote library. We then will export the references from the EndNote Library into the software Rayyan. This software will support the screening process.
Selection process:
Two reviewers (SP, PB) being experts in VLU and conducting reviews in this field will independently screen titles and abstracts for those matching the eligibility criteria. We will retrieve the full-texts of the relevant eligible studies. Two reviewers will independently assess the full texts for study characteristics. The excluded studies will be listed in a table including the reason for exclusion. We will resolve any discrepancies between the reviewers involving a third reviewer. Finally, we will prepare a PRISMA-flowchart to document the final selection process.
Two independent reviewers will conduct a risk of bias assessment; any disagreements will be resolved through discussion or consultation with a third reviewer if needed. To assess the methodological quality of the included studies the quality appraisal tool for systematic reviews of prevalence data will be used (18). The quality of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methods (19).
Data extraction
Included study data will be extracted and managed independently by two reviewers using an electronic data collection form developed by SP, PB and MP. The information will include Study details (e.g., study ID, author, year, journal), study method (e.g., aims of study, setting, study design, outcomes method of data analysis), results (eg. prevalence n/N (%), proportion and 95% confidence intervals (CI), incidence n/N (%), proportion and 95% CI and duration of recruitment or the study). Studies in which wounds of various aetiologies are reported will only be included if data specific to VLU can be extracted. If data is unclear or missing, we will contact the authors. We will resolve any disagreements between the reviewers through discussion and if needed by involving a third reviewer.
Data synthesis
We will summarise the study characteristics and findings descriptively and will present these in tabular format. Prevalence, incidence and the characteristics of the study population will be summarized and synthesized narratively as well as in tables. If possible, odds ratios (for categorical outcome data) or weighted mean differences (for continuous data) and 95% confidence intervals will be calculated for each included study. To assess the heterogeneity between the studies we will use the chi squared test (20). In the case of a heterogeneity, we will carry out a subgroup analysis (e.g. age, sex and setting) and univariate meta-regression in order to estimate the effect of study-level covariates on the estimates of prevalence and incidence. If we find a high number of sufficiently homogeneous studies (in terms of study design, population, and outcome characteristics) we will perform a meta-analysis. When pooling proportions for meta-analysis, we will use the Logit transformation to calculate the weighted summary proportion under fixed and random effects models (21). We will then list the proportions, with their 95% CI, found in the individual studies included in the meta-analysis. We will then present the results graphically in a forest plot. If a meta-analysis is deemed inappropriate, we will present a narrative summary of results as well as in tables/figures, considering the strengths of the studies.