Sickle cell disease treatment and management in India: a systematic review of interventional studies.
Parikipandla SrideviYogita SharmaLokeswara Bala Krishna SunnamBontha Veerraju BabuPublished in: Transactions of the Royal Society of Tropical Medicine and Hygiene (2022)
Sickle cell disease (SCD) affects approximately 5% of the world's population, and India has been the second highest country in the numbers of predicted SCD births. Despite the high burden in India, there is no state-led public health programme, and very few interventions dealing with the treatment and management of SCD are available. This review highlights the dearth of SCD-related interventions, and demonstrates that these interventions effectively improve patients' conditions and are feasible to implement in India. We systematically searched three databases-PubMed/Medline, Google Scholar and Web of Science-for articles from India on SCD-related interventions. The PRISMA guidelines were followed during this review. We included 22 studies, of which 19 dealt with specific therapeutic interventions, and 3 with comprehensive SCD care. Hydroxyurea therapy was the main therapy in 15 studies and is efficacious. Three studies demonstrated the feasibility of comprehensive care in resource-limited settings. The low number of SCD-related intervention studies does not match the huge burden of SCD in India. Governments of endemic countries should consider the findings of available interventions and include them in their countries' programmes. Comprehensive care is feasible in India and other low-resource settings, from screening to treatment and psychosocial support.
Keyphrases
- sickle cell disease
- public health
- physical activity
- healthcare
- case control
- palliative care
- end stage renal disease
- randomized controlled trial
- quality improvement
- chronic kidney disease
- stem cells
- newly diagnosed
- mental health
- risk factors
- bone marrow
- mesenchymal stem cells
- peritoneal dialysis
- replacement therapy
- affordable care act
- artificial intelligence
- machine learning
- prognostic factors
- clinical practice