Translate this page into:
Impact of automated peritoneal dialysis remote monitoring on hospitalization events

*Corresponding author: Nadia Al Rahbi, Department of Internal Medicine and Nephrology, Royal Hospital, Muscat, Oman. alrahbi2000@hotmail.com
-
Received: ,
Accepted: ,
How to cite this article: Al Rahbi N, Al Salmi I, AlSahow AE, Abusara S. Impact of automated peritoneal dialysis remote monitoring on hospitalization events. World Adv Renal Med. 2025;1:80-7. doi: 10.25259/WARM_10_2025
Abstract
Objectives :
The objective of this study is to evaluate the effect of automated peritoneal dialysis (PD) automated remote monitoring (ARM) on hospitalization rate and length of stay.
Material and
Methods: This longitudinal observational study was carried out on 92 adult participants on automated PD (APD). It involved four hospitals from two Arab Gulf Countries. All participants were connected to the Sharesource Platform and observed for 6 months from January 2022 to June 2022 . Patients were monitored for adherence to APD therapy and troubleshooting during therapy, and the early detection and management of PD complications and their role in the reduction of hospitalization rate. Findings were then compared to the status a year before connection to ARM.
Results:
Females accounted for 58% of patients, and the participants’ mean age was 51.2 (standard deviation ±17.8) years. Diabetes was the most common cause of kidney failure. Infectious complications were reported in ten patients, non-infectious complications in 13 patients, and admission for PD complications in 13 patients, compared with 20, 23, and 17 patients before ARM application, respectively. Non-infectious complications such as altered ultrafiltration (UF) status, fluid management, and catheter-related issues were detected early by ARM and managed at the PD Clinic without hospitalization. However, PD-related peritonitis required admission.
Conclusion:
ARM allows early detection and outpatient management of problems, in particular, non-infectious complications. It also detects adherence to prescribed therapy and offers safer and better-quality treatment. It also lowers hospitalization rates and length of hospital stay. However, the incidence of peritonitis-related hospitalization remains as same as before the ARM application.
Keywords
Automated remote monitoring
Chronic kidney disease
Early detection and management of complications
Hospitalization rate
Peritoneal dialysis
INTRODUCTION
Despite peritoneal dialysis (PD), it is very difficult to monitor PD patients at home for adherence and troubleshooting of problems. This may delay any necessary intervention affecting the patient’s quality of life and PD survival rate. PD has improved significantly to reduce the risk of complications and improve the quality of care, such as the introduction of advanced laparoscopic placement techniques,[1] PD machines have also evolved resulting in significant improvements in PD connectology. Modern automated PD (APD) machines enable direct communication between the clinic and the patient’s home through a cloud-based platform. This real-time monitoring is an important component of telemedicine in PD and enables remote patient management (RPM) of out-of-hospital populations where medical surveillance is still required.[2] This application transmits therapy and patient biometric data to clinicians, allowing patient monitoring in real-time, early detection of clinically relevant issues such as catheter dysfunction and non-adherence to prescribed therapy, and the reduction of travel for patients who have social, geographical, or physical difficulties.[2-4] In most Gulf Cooperation Council (GCC) Countries, RPM started in 2018.
This paper aims to evaluate the impact of automated remote monitoring (ARM) on the early detection of PD complications to reduce hospitalization rate and length of hospital stay in two GCC countries, Oman and Kuwait.
MATERIAL AND METHODS
This longitudinal observational study was carried out to evaluate the impact of early detection of PD complications and reduce the hospitalization rate and hospital stay in patients on remote monitoring (Sharesource). Figure 1 summarizes the methodology. The study recruited 92 adult PD patients from two Arab Gulf Countries; the Sultanate of Oman (the Royal Hospital) and Kuwait (Mubarak Hospital, Farwaniya Hospital, and Jahra Hospital), and excluded patients on continuous ambulatory PD or not connected to the platform. We compared the incidence and management of PD complications (infectious and non-infectious), a year pre-ARM connection and six months post-connection, and their relation to early management and hospitalization events. Data pre-ARM connected were collected from the hospitals’ information technology (IT) system. The study included the demographics and clinical data collected from hospitals’ electronic systems, as shown in Table 1. In Oman, clinical and laboratory data were collected using the Al-Shifa medical information system, and in Kuwait, data were collected using the Hospital Information System.

- Summarization of study methodology process. PD: Peritoneal dialysis.
| Variables | Result |
|---|---|
| Male sex, n(%) | 38 (41.3%) |
| Kuwaiti nationality, n(%) | 50 (54.8%) |
| Mobility | 67 (72.8%) |
| Mobile, n(%) | 17 (18.5%) |
| Mobile+minimal assistance, n(%) | 5 (5.4%) |
| Mobile with assistance, n(%) | 3 (3.3%) |
| Bed bound, n(%) | |
| Marital status | 69 (75%) |
| Married, n(%) | 23 (25%) |
| Unmarried, n(%) (Single, Divorced, Widowed) |
|
| Employment Status | 32 (34.8) |
| Employed, n(%) | 60 (65.2) |
| Not employed, n(%) | 22 (36.7%) |
| Retired, n(%) | 8 (13.3%) |
| Student, n(%) | |
| PD done (primarily) by: | 44 (47.8%) |
| Patient, n(%) | 40 (43.5%) |
| Caregiver, n(%) | 8 (8.7%) |
| Both, n(%) |
Values are given as mean±SD for continuous variables and as number (percentage) for categorical variables. PD: Peritoneal dialysis.
We classified PD complications and hospitalization rates, and length that occurred in our participants into two groups: pre-remote monitoring (group A) and post-remote monitoring (group B). Infectious complications include exit site infection (ESI), tunnel infection, and peritonitis. Non-infectious complications include catheter blockage, catheter migration, constipation, hernia, and fluid overload. Moreover, we evaluated the impact of early detection of these complications on the reduction of admission rate.
During six months of observations, from January 1, 2022, to June 30, 2022, participants were connected to the Sharesource Platform, and the PD nurses monitored PD performance daily. PD nurses monitored daily PD achievement; pre-dialysis blood pressure (BP) reading, pre-dialysis body weight reading, PD ultrafiltration rate, and status of APD therapy (completed full session, not completed, or not done). Furthermore, they monitored alarms and troubleshooting during PD exchanges. We evaluated the early management for that troubleshooting by recording different types of alarms, causes of alarms, methods of management used to solve causes, and mentioning cases that required admission.
RESULTS
Chronic kidney disease (CKD) and GCC countries epidemiology
In this study, the PD population was more female, and the mean age of all participants was 51.2 years; Kuwaiti mean age was 58.4 years, while Omani patients’ mean age was 47 years. Diabetes mellitus (DM), followed by hypertension (HTN), was the major cause of CKD as shown in Table 2.
| Variables | Result |
|---|---|
| Mean age, mean±SD 13-25, n(%) 26-40, n(%) 41-65, n(%) > 65, n(%) |
51.2±17.8 9 20 38 25 |
| Mean BMI, mean±SD <18.5, n(%) 18.5-24.9, n(%) >25, n(%) |
26 kg/m2±9 (9.8%) 37 (40.2%) 46 (50%) |
| L2Cause of CKD Diabetes, n(%) Hypertension, n(%) Glomerulopathies, n(%) Others, n(%) |
36 (39%) 33 (36%) 11 (12%) 12 (13%) |
| Comorbidities: Diabetes, n(%) Hypertension, n(%) CAD, n(%) Smoking, n(%) |
44 (47.8%) 81 (88%) 29 (31.5%) 16 (17%) |
| H/O kidney transplantation | 19 (20.7%) |
| Transfer from hemodialysis | 46 (50%) |
| Urine output (ml/day) >500, n(%) 100-500, n(%) < 100, n(%) |
22 (27%) 41 (50%) 19 (23%) |
| PD vintage >5 years, n(%) 1-5 years, n(%) < 1 year, n(%) |
15 (16.3%) 56 (21.7%) 21 (22.8%) |
Values are given as mean±SD for continuous variables and as number (percentage) for categorical variables. SD: Standard deviation, BMI: Body mass index; CKD: Chronic Kidney disease, CAD: Coronary artery disease, H/O: History of, PD: Peritoneal dialysis.
GCC faces complex challenges in managing and mitigating the record-high prevalence of lifestyle-related noncommunicable diseases.[4,5] In 2018, the prevalence of end-stage kidney disease (ESKD) in GCC was 551 per million population (pmp), with Oman having the highest (1000/pmp) and Qatar having the lowest prevalence (347), and the median age of ESKD patients is 53.5 years for men and 51.0 years for women.[6] By contrast, in the US, CKD is more common in women (15%) than men (12%).[7] The age of ESKD patients in the GCC countries ranged from 33 to 61.9 years.[8] To be specific, the median age of ESKD patients in Kuwait was 45 years[9,10] and in Oman was 53 years.[11] CKD in the US is more common in people aged 65 years or older (38%) than in people aged 45–64 years.[7]
DM and HTN are the major causes of CKD in adults.[7] Likewise, in all GCC countries, DM and HTN emerged as the most common etiologies, followed by chronic glomerulonephritis (66.7%) and unknown etiology (33.3%).[6-9,11] According to a meta-analysis, the most common comorbidities associated with ESKD in GCC countries are DM (47.85%), HTN (77.88%), cardiovascular disease (14.51%), and vascular disease (11.7%).[8]
PD complications pre- and post-implementation of Sharesource
Table 3 shows rates of PD complications and hospitalization before ARM compared to their rates after ARM initiation. Twenty-two percentages of group A patients had infectious complications, and peritonitis represented 50% of the infectious complications. In group B, 10% of patients had infectious complications, and peritonitis remained the most common complication. Non-infectious complications occurred in 25% of group A patients and declined to 13% in group B. Figure 2 demonstrates the causes of admission in both groups. Hospitalization rates and length were higher pre-remote monitoring; 17 cases were admitted due to PD complications. They were admitted for a period between 5 and 7 days for management of non-infectious complications compared with 11 patients post ARM initiation admitted for 3–5 days [Figure 3]. Most of the admissions in both groups were due to peritonitis, with an average admission of 10 days during pre- and post-application of ARM.
| Pre-ARM | On-ARM | p-value | |
|---|---|---|---|
| Infectious complication | 20 (22%) | 10 (11%) | 0.001 |
| Exit site infection Tunnel infection Peritonitis |
6 (30%) 2 (10%) 12 (60%) |
1 (10%) 1 (10%) 8 (80%) |
|
| Non-infectious complication | 23 25%) | 13 (15%) | 0.014 |
| Catheter blockage Catheter migration Constipation Hernia Fluid overload |
4 (17.4%) 4 (17.4%) 6 (26.1%) 4 (17.4%) 5 (21.8%) |
4 (30.8%) 1 (7.7%) 6 (45.2%) 1 (7.7%) 1 (7.7%) |
|
| Admission due to PD complications | 17 (18.5%) | 11 (12%) | 0.001 |
PD: Peritoneal dialysis, Pre-ARM: Pre automated remote monitoring (ARM), On-ARM: remote monitoring.

- Information about the reasons for admission in our participants and comparing the findings during the two periods, pre- and post-remote monitoring (group A and B).

- Comparing the average length of admission days during the two periods, pre and post remote monitoring (group A and B).
List of alarms, skipping, and incomplete PD therapy recorded from the platform
Over 6 months of monitoring through the Sharesource platform, we observed several alarms, which usually vary by cause and type of treatment. Some alarms were simple and managed through phone calls easily. However, other alarms indicated serious PD complications that required management in the hospital. Figure 4 lists names and the average number of alarms per month. The number of alarms during one APD exchange depends on the patient’s response to correct the problem (act or ignore) and the severity of the problem (the patient could not manage the issue without visiting the hospital).

- Listed number of alarms per one month observed through the Sharesource platform.
Table 4 and Figure 5 illustrate the number of skipped APD therapy and uncompleted therapy from January to June. The number of dialysis exchanges is calculated by multiplying the number of patients (92) by the number of days per month. For example, April has 30 days, therefore, the total exchanges is 2760. The percentage of skipped therapy varies between 7.1% and 12.8%. This percentage is not all related to patient adherence but also includes dialysis off days given by the PD team and temporary withholding of PD due to surgical or other medical reasons. There was an average of 6–10 APD therapies/month disconnected before completing full therapy. Patients were asked verbally for reasons behind this action, and they reported one or more of three main reasons: Disturbance due to continuous machine alarm (LOW DRAIN VOLUME), intolerable abdominal pain during the draining phase, or personal reasons.

- Illustration of the number of skipped APD therapy and incomplete treatment by our participants during a six-month period. APD: Automated peritoneal dialysis.
| Months (number of sessions=days X 92) | Skipped sessions | Incomplete sessions |
|---|---|---|
| January (2852) February (2576) March (2852) April (2760) May (2852) June (2760) |
212 (7.4%) 331 (12.8%) 273 (9.6%) 246 (8.9%) 207 (7.3%) 196 (7.1%) |
6 (0.21%) 9 (0.35%) 9 (0.32%) 7 (0.25%) 10 (0.35%) 7 (0.25%) |
Relationship between early detection of complications through remote monitoring and reduced admission rate
Table 5 details issues that happened during APD exchanges and were managed early. Some of these problems were managed only by advice over the phone, such as low drain volume alarms caused by the patient’s sleeping position and skipping or disconnecting of APD therapy before completion. On the other hand, other problems required examination and management at the PD clinic, such as low drain volume and low UF due to constipation, catheter blockage, and uncontrolled BP due to non-adherence to medication, salt and/or fluid intake, and APD therapy regimen, and due to inadequate PD prescription. Some issues require both a PD clinic assessment and admission. Early detection of such issues facilitated early management and reduced admission days. For example, low UF due to volume depletion required admission for 1–3 days for correction of volume status and adjustment of APD prescription. Figures 6 and 7, taken from the Sharesource system, compare UF status with volume depletion and after 1 month of treatment for an old patient suffering from poor fluid intake.
| Causes of alarm | Management method | PD clinic visits | Hospital admissions |
|---|---|---|---|
| Patient related factors | |||
| Sleeping position | Instruction via phone call | 0 | 0 |
| Patient adherence (treatment skipping or disconnection) | Instruction via phone call | 0 | 0 |
| Volume depletion | Clinic visit for evaluation | One day visit | Admission for 1-3 days for correction of volume depletion and adjustment of PD prescription |
| Constipation | Clinic visit for evaluation | 1-3 visits | 0 |
| PD catheter-related factors: Catheter blockage | Clinic visit for evaluation Catheter flushing IP heparin infusion IP thrombolytics | 1-3 visits | Two admissions for 1-3 days |
PD: Peritoneal dialysis.

- Taken from platform screen for one of elderly patient suffered from dehydration and poor oral intake. It showed UF status when patient was dehydrated. UF: Ultrafiltration.

- Taken from platform, showed the status of UF of the elderly patient post treatment. UF: Ultrafiltration.
Similarly, patients presented with frequent alarms of low drain volume and poor UF due to catheter migration required hospitalization between 3 and 5 days for surgical correction of catheter position using a laparoscopic technique and evaluation of therapy after adjustment, as illustrated in Photo 1a and 1b.

- Compares two abdomen X-ray images pre and post catheter reposition for patient presented with continues alarm of low drain and low UF. It showed catheter migration and patient required surgical intervention for correction of PD Catheter position. (a) The red arrow in photo 1a shows that the PD catheter has migrated to the left upper quadrant of the abdomen and requires reposition. (b) The red arrow in photo 1b shows the PD catheter shadow in the pelvic region and it indicates that the catheter is back to the correct position after surgical intervention. UF: Ultrafiltration, PD: Peritoneal dialysis.
Unfortunately, most infectious complications could not be detected early through Sharesource, but the patient attended the emergency department (ED) and was then admitted. It could be explained by patient awareness about the signs and symptoms of peritonitis and having to attend the ED for treatment, as they were instructed during PD training, or due to intolerable abdominal pain.
DISCUSSION
PD before and after ARM
The present study reports several complications detected in the early stage through Sharesource that prevented hospitalization or shortened the length of stay. One of the issues dealt with at PD Clinics was alterations in the Ultrafiltration pattern. This could have been the result of patient-related factors such as patient adherence, sleeping position, volume depletion, and/or constipation, and PD catheter-related factors such as catheter blockage and/or catheter migration.[12-16] Another issue that was managed in PD Clinics was uncontrolled BP related to patient non-adherence to antihypertensive drugs, diet, and fluid restriction, and APD therapy regimen. Other issues that did not require admission in most instances included constipation, inadequate PD prescription, and PD catheter malfunction. However, a few cases required admission and surgical intervention, like catheter migration. On the other hand, infectious complications could not be detected through Sharesource, and patients required admission. In fact, hospitalization due to infectious complications, in particular, peritonitis, remained the same as it was before ARM initiation. Home-based dialysis may lead to patients’ inability to receive adequate care if they are not regularly monitored, as in-center dialysis. Patients with PD are usually seen once every 1–3 months to evaluate PD performance. This evaluation includes physical assessment and achievement of PD, such as UF and dialysis clearance. Nevertheless, patients cannot be monitored during other days at home for adherence, fluid management, and early detection of complications, which usually increases the risk of late management and hospitalization.[17-19]
Baxter Company in the United Kingdom introduced a new system called Claria Sharesource for people on APD in 2016. The program automates the transmission of dialysis data to PD units and enables clinicians to remotely modify dialysis therapy cycler programs.[3] In 2018, Sharesource was implemented in most (GCC) countries including Oman and Kuwait.
APD patients on remote monitoring reported long-term advantages such as treatment adherence improvement, early problem detection and resolution, fewer hospital admissions for technical and clinical issues, which saves money, and improved patient quality of life.[20-22] Published literature also showed that remote monitoring improves ultrafiltration profile, BP control, and early catheter dysfunction detection rate, and allows timely treatment modification.[13,16-18] For example, RPM allows medical professionals to monitor and analyze short-term ultrafiltration failures while regularly reviewing the record base and looking for trends in long-term follow-up changes.[23]
Several studies support our findings.[17-29] Sanabria et al.[17] conducted a retrospective cohort study that included 360 adult PD patients from Colombia, with APD-RPM accounting for 18%, and 82% were managed with APD without RPM. Authors found APD therapy with RPM associated with significant reductions in hospitalization rate and fewer hospitalization days per patient-year compared with APD without RPM.[17] Likewise, in 2020, Manani et al.[27] conducted a retrospective cohort study to compare the outcomes of two groups of APD patients who were followed up with either standard care or ARM for 6 months. After analyzing ED visits, hospitalizations, peritonitis, volume depletion, and dropout rates, it was determined that ARM enhanced clinical outcomes for PD patients by lowering admission rates related to volume overload and ESI. However, no difference was observed in hospitalization rates related to peritonitis and other causes, particularly for those with higher comorbidity scores.[27] Bubieńczyk et al.[18] presented cases that showed RPM helped spot changes in ultrafiltration in various clinical situations. Peritonitis and some cases caused a decline in the UF pattern a few days before reporting to the hospital and admission, when the Sharesource platform was checked.[18] The study by Yeter et al.,[25] analyzed the effect of ARM-APD on treatment adherence, dialysis adequacy, and change in BP control, sleep quality, and health-related quality of life during the 6 months of follow-up. It found a significant increase in ultrafiltration amounts with ARM-APD and the daily antihypertensive pill needed, and alarms received from the device decreased at the 6th month of the switch. Moreover, there was no significant change in sleep quality and health-related quality of life within 6 months.[24]
CONCLUSION
The present study showed the effectiveness of remote monitoring in detecting many PD complications that enhanced early treatment and reduced hospitalization rates and hospital stays. As a result, it will improve the patient’s quality of life, prolong the stay on PD therapy, and reduce the cost of hospitalization. We recommend that other PD centers start ARM implementation for their APD patients. This study highlights the importance of patient adherence to success in PD therapy. Finding the factors that contribute to non-adherence should be considered. Indeed, the interventions for this patient group can be informed by the role of psychosocial, interpersonal, and PD factors, all of which are guided by related theoretical frameworks and can contribute to our understanding of non-adherence.
Regarding infectious complications, the PD team must focus on different points to reduce the infection rate among PD patients. First, a proper selection of PD patients and follow the international guidelines of PD eligibility. Important patient factors to consider include DM, large and small body sizes, peritoneal membrane transport status, elderly age group, and low socioeconomic status. It is crucial to provide PD patients with quality clinical and psychosocial care in addition to paying close attention to their adherence. Second, effective PD training and retraining are important factors in preventing and reducing accidents or infections. The recommendation for PD training programs should last from 5 to 8 days, with 1 to 3-h sessions, a nurse-to-patient ratio of 1:1, and a cumulative training time of 15 h or more recommended to enhance patient independence and reduce peritonitis rates. Finally, implementing continuous quality improvement (CQI) principles in PD practice is essential to the technique’s ongoing success with patients. CQI can lead to better patient outcomes, which can result in more successful PD programs across the globe.
Study limitation
A six-month duration may not be long enough to wholly evaluate the effectiveness of remote monitoring and judge its role in detecting different types of PD complications and reducing hospitalization rates. We also did not have a concurrent group without remote monitoring for comparison. We instead compared the pre-application of Sharesource period to the post-application period for the same group of patients. It is recommended in the future to conduct studies that take into consideration the two limitations. However, our study recruited participants with different backgrounds from four big public hospitals in two different GCC countries, Oman and Kuwait. Data from the platform were collected by dedicated and qualified PD nurses, which can make a difference in the accuracy of study results. Finally, the number of participants is quite good to make a clear judgment on the effectiveness of this application in reducing hospitalization rates, even with 6 months of monitoring.
ARM has an interactive interface that allows the PD team to make prescription changes via a remote connection and reduces the need for frequent patient visits to the PD clinic. Daily monitoring makes it possible to detect problems early and correct potential situations of inadequate dialysis. Moreover, it detects patients’ adherence to prescribed therapy and offers safer and better-quality treatment. It is also associated with lower hospitalization rates and length of hospital stay.
Acknowledgment:
We would like to thank our patients for their participation and cooperation in conducting the study. Furthermore, we would like to thank the research committees in Oman and Kuwait, as well as all our colleagues, including nurses, doctors, and the information technology department, for their assistance in collecting the data.
Author contributions:
All authors have contributed equally.
Ethical approval:
The study was approved by the Ministry of Health, Kuwait University Joint Committee on Medical and Scientific Research number 2021/1833 issued on 12th December 2021, and by Center of Studies and Research, Ministry of Health Oman number 2020 /24026 issued on 18th October 2020.
Declaration of patient consent:
Patient’s consent was not required as patients identity is not disclosed or compromised.
Conflicts of interest:
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation:
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.
Financial support and sponsorship: Nil.
References
- A systematic review and meta-analysis of the influence of peritoneal dialysis catheter type on complication rate and catheter survival. Kidney Int. 2014;85:920-32.
- [CrossRef] [PubMed] [Google Scholar]
- Evolution of automated peritoneal dialysis machines In: Remote patient management in peritoneal dialysis. Vol 197. Basel: Karger Publishers; 2019. p. :9-16.
- [CrossRef] [PubMed] [Google Scholar]
- Remote monitoring of peritoneal dialysis: evaluating the impact of the Claria Sharesource system. J Kidney Care. 2019;4:16-24.
- [CrossRef] [Google Scholar]
- Noncommunicable diseases and hospital utilization in Kuwait: A generalizable approach using the world health survey. Med Princ Pract. 2022;31:445-53.
- [CrossRef] [PubMed] [Google Scholar]
- A systematic analysis of worldwide population-based data on the global burden of chronic kidney disease in 2010. Kidney Int. 2015;88:950-7.
- [CrossRef] [PubMed] [Google Scholar]
- Current status and future of end-stage kidney disease in gulf cooperation council countries: Challenges and opportunities. Saudi J Kidney Dis Transpl. 2021;32:1073-88.
- [CrossRef] [PubMed] [Google Scholar]
- Chronic kidney disease in the United States, 2019. 2019. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention. Avaliable from https://fluoridealert.org/studytracker/chronic-kidney-disease-in-the-united-states-2019/ [Last accessed 2025 June17]
- [Google Scholar]
- Epidemiology of end-stage renal disease in the countries of the Gulf Cooperation Council: a systematic review. JRSM Short Rep. 2012;3:38.
- [CrossRef] [PubMed] [Google Scholar]
- Renal data dialysis from the Arab world dialysis in Kuwait: 2013-2019. Saudi J Kidney Dis Transpl. 2020;31:826-830.
- [CrossRef] [PubMed] [Google Scholar]
- End-stage kidney failure in Oman: An analysis of registry data with an emphasis on congenital and inherited renal diseases. Int J Nephrol. 2017;2017:6403985.
- [CrossRef] [PubMed] [Google Scholar]
- Demographics and key clinical characteristics of hemodialysis patients from the Gulf Cooperation Council countries enrolled in the dialysis outcomes and practice patterns study phase 5 (2012-2015) Saudi J Kidney Dis Transpl. 2016;27:S12-23.
- [CrossRef] [PubMed] [Google Scholar]
- Longitudinal experience with remote monitoring for automated peritoneal dialysis patients. Nephron. 2019;142:1-9.
- [CrossRef] [PubMed] [Google Scholar]
- Through the storm: Automated peritoneal dialysis with remote patient monitoring during COVID-19 pandemic. Blood Purif. 2021;50:279-82.
- [CrossRef] [PubMed] [Google Scholar]
- A remote management program in automated peritoneal dialysis patients in Colombia. Nefro Latinoam. 2018;15:47-51.
- [CrossRef] [Google Scholar]
- Remote patient management in automated peritoneal dialysis: A promising new tool. Perit Dial Int. 2018;38:76-8.
- [CrossRef] [PubMed] [Google Scholar]
- Remote monitoring of automated peritoneal dialysis improves personalization of dialytic prescription and patient's independence. Blood Purif. 2018;46:111-7.
- [CrossRef] [PubMed] [Google Scholar]
- Remote patient monitoring program in automated peritoneal dialysis: Impact on hospitalizations. Perit Dial Int. 2019;39:472-8.
- [CrossRef] [PubMed] [Google Scholar]
- The use of remote patient management in early diagnosis of ultrafiltration failure in peritoneal dialysis. Renal Dis Transplant Forum. 2022;15:87-94.
- [Google Scholar]
- Impact of continuous quality improvement initiatives on clinical outcomes in peritoneal dialysis. Perit Dial Int. 2014;34(Suppl 2):S43-8.
- [CrossRef] [PubMed] [Google Scholar]
- Peritoneal dialysis patient selection: Characteristics for success. Adv Chronic Kidney Dis. 2009;16:160-8.
- [CrossRef] [PubMed] [Google Scholar]
- Peritoneal dialysis and the process of modality selection. Perit Dial Int. 2013;33:233-41.
- [CrossRef] [PubMed] [Google Scholar]
- Non-adherence in patients on peritoneal dialysis: A systematic review. PLoS One. 2014;9:e89001.
- [CrossRef] [PubMed] [Google Scholar]
- Automated remote monitoring for peritoneal dialysis and its impact on blood pressure. Cardiorenal Med. 2020;10:198-208.
- [CrossRef] [PubMed] [Google Scholar]
- Remote automated peritoneal dialysis management in Colombia. Kidney Int Rep. 2019;4:873-6.
- [CrossRef] [PubMed] [Google Scholar]
- Effect of remote patient management in peritoneal dialysis on haemodynamic and volume control. Nephrology (Carlton). 2020;25:856-64.
- [CrossRef] [PubMed] [Google Scholar]
- The utility of remote patient management in peritoneal dialysis. Clin Kidney J. 2021;14:2483-9.
- [CrossRef] [PubMed] [Google Scholar]
- Remote monitoring in peritoneal dialysis: Benefits on clinical outcomes and on quality of life. J Nephrol. 2020;33:1301-8.
- [CrossRef] [PubMed] [Google Scholar]
- Peritoneal dialysis patient training program to enhance independence and prevent complications: A scoping review. Int J Nephrol Renovasc Dis. 2023;16:207-22.
- [CrossRef] [PubMed] [Google Scholar]
- Continuous quality improvement in peritoneal dialysis: Your questions answered. Perit Dial Int. 2023;43:292-300.
- [CrossRef] [PubMed] [Google Scholar]

