Is low birth weight an additional risk factor for hypertension in paediatric patients after kidney transplantation?
Larissa Badim SantosLuana Meireles BorgesLivia Victorino SouzaClaudia Rosso FelipeJosé Osmar Medina-PestanaMaria do Carmo Pinho FrancoPublished in: Journal of developmental origins of health and disease (2019)
Hypertension (HTN) remains a common complication after kidney transplantation among paediatric patients. Although low birth weight (LBW) has been implicated as an important risk factor for cardiovascular diseases, its effect on transplantation patients has not yet been addressed. It is essential to determine whether children with LBW who undergo transplantation are more likely to develop post-transplantation HTN. For this study, the medical records of 96 kidney recipients were retrospectively examined. A total of 83 patients fulfilled the inclusion criteria. Overall, post-transplantation HTN was observed in 54% of the recipients. Multivariate logistic regression revealed that time from transplantation >14 months (odds ratio (OR) 3.6; 95% confidence interval (CI) 1.31-10.06; P = 0.013), current CKD (OR 2.6; 95% CI 1.01-7.20; P = 0.045), presence of LBW (OR 3.6; 95% CI 1.04-12.32; P = 0.044) and current overweight/obesity (OR 3.7; 95% CI 1.02-13.91; P = 0.047) were associated with post-transplantation HTN. In conclusion, our data provide evidence for the first time that LBW is a significant predictive factor in the development of post-transplantation HTN. This finding has important clinical implications as it serves to alert clinicians about this additional risk factor in paediatric patients undergoing kidney transplant.
Keyphrases
- end stage renal disease
- low birth weight
- chronic kidney disease
- ejection fraction
- patients undergoing
- emergency department
- preterm infants
- peritoneal dialysis
- cardiovascular disease
- prognostic factors
- weight loss
- healthcare
- cell therapy
- type diabetes
- stem cells
- mesenchymal stem cells
- patient reported outcomes
- palliative care
- adipose tissue
- human milk
- machine learning
- single cell
- patient reported
- deep learning
- kidney transplantation
- cardiovascular events