A COVID-19 pandemic-specific, structured care process for peritoneal dialysis patients facilitated by telemedicine: Therapy continuity, prevention, and complications management.
Elianny PolancoMercedes AqueyJhanna ColladoErwin CamposJanny GuzmanMiguel Angel Cuevas-BudhartJosé Carolino Divino-FilhoAlfonso Ramos-SanchezPublished in: Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy (2021)
Coronavirus disease 2019 (COVID-19) has been declared a pandemic. Peritoneal dialysis (PD), being a home therapy, allows for physical distancing measures and movement restrictions. In order to prevent COVID-19 contagioun among the Dominican Republic National Health System PD program patients, a follow-up virtual protocol for this group was developed. The aim of this study is to outline the protocol established by the PD program's healthcare team using telemedicine in order to avoid COVID-19 transmission and to report initial results and outcomes of this initiative. This is an observational prospective longitudinal study with 946 patients being treated in seven centers distributed throughout the country between April 1 and June 30. The protocol was implemented focusing on the patient follow-up; risk mitigation data were registered and collected from electronic records. During the follow-up period, 95 catheters were implanted, 64 patients initiated PD, and the remaining were in training. A total of 9532 consultations were given by the different team specialists, with 8720 (91%) virtual and 812 (9%) face-to-face consultations. The transfer rate to hemodialysis was 0.29%, whereas the peritonitis rate was 0.11 episode per patient/year. Eighteen adults tested positive for COVID-19. The implementation of the protocol and telemedicine utilization have ensured follow-up and monitoring, preserved therapy, controlled complications, and PD lives protected.
Keyphrases
- end stage renal disease
- peritoneal dialysis
- coronavirus disease
- chronic kidney disease
- healthcare
- quality improvement
- sars cov
- newly diagnosed
- randomized controlled trial
- ejection fraction
- prognostic factors
- physical activity
- primary care
- machine learning
- case report
- patient reported
- cross sectional
- cell therapy
- deep learning
- skeletal muscle
- artificial intelligence
- social media
- health information
- smoking cessation
- breast cancer risk