The Prevalence and Incidence of Atypical Hemolytic Uremic Syndrome in Iran: A Systematic Review and Meta-Analysis Protocol Study

Context: Hemolytic uremic syndrome (HUS), being more prevalent in infants and children, is recognized by a triad of acute kidney injury, microangiopathic hemolytic anemia, and thrombocytopenia. It is classified according to the underlying disorders, such as infection, systemic, metabolic disorder, or complement dysregulation. It has a high rate of morbidity and mortality. Many types of treatment, such as conservative management, plasma exchange, regular plasma infusion, and even a new expensive medication, “Ecluzimab”, have been suggested. The aim of this systematic review is to estimate the incidence and prevalence of HUS (according to diarrhea positive or negative samples). In addition, the study will investigate the clinical presentation and the outcome of Iranian patients.
Evidence Acquisition: The following data bases will be explored for articles published between years 1985 and 2016, PubMed, EMBASE, OVID, SCOPUS, Web of Sciences, Google Scholar, Google, barakatkns.com, MagIran, SID, dociran, PDFiran, and ganj.irandoc. Besides, all online university databases will be searched for theses and abstracts of local or international congresses; a manual search will be performed to identify pertinent cross references. Systematic review or meta-analysis, longitudinal and cohort studies, cross-sectional, case-control, and epidemiological studies will be included in this review. Relevant conference proceedings, theses or unpublished data will also be considered. The retrieved data should comprise of proportions, incidence, prevalence, geographical distribution, mortality and morbidity rates (i.e. dialysis and central nervous system involvement). A meta-analysis will be performed if 3 similar studies are found. If sufficient data is extracted, subgroup analysis will be performed for age, gender, acute kidney injury, dialysis, and death.
The results of the current study could have implications for health policies, practice, research, and medical education: The data could improve clinical and health care decisions, allow estimation of the number of patients that require new medication, and could direct future research design in this field.