Monitoring Risk Factors and Improving Adherence to Therapy in Patients With Chronic Kidney Disease (Smit-CKD Project): Pilot Observational Study
Chronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an ad...
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Published in | JMIR bioinformatics and biotechnology Vol. 3; no. 1; p. e36766 |
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Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Canada
JMIR Publications
15.11.2022
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Online Access | Get full text |
ISSN | 2563-3570 2563-3570 |
DOI | 10.2196/36766 |
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Abstract | Chronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an additional risk factor for cardiovascular morbidity and mortality. Considering the increased penetration of mobile phones, a mobile app could educate patients to autonomously monitor cardiorenal risk factors.
With this background in mind, we developed an integrated system of a server and app with the aim of improving self-monitoring of cardiovascular and renal risk factors and adherence to therapy.
The software infrastructure for both the Smit-CKD server and Smit-CKD app was developed using standard web-oriented development methodologies preferring open source tools when available. To make the Smit-CKD app suitable for Android and iOS, platforms that allow the development of a multiplatform app starting from a single source code were used. The integrated system was field tested with the help of 22 participants. User satisfaction and adherence to therapy were measured by questionnaires specifically designed for this study; regular use of the app was measured using the daily reports available on the platform.
The Smit-CKD app allows the monitoring of cardiorenal risk factors, such as blood pressure, weight, and blood glucose. Collected data are transmitted in real time to the referring general practitioner. In addition, special reminders improve adherence to the medication regimen. Via the Smit-CKD server, general practitioners can monitor the clinical status of their patients and their adherence to therapy. During the test phase, 73% (16/22) of subjects entered all the required data regularly and sent feedback on drug intake. After 6 months of use, the percentage of regular intake of medications rose from 64% (14/22) to 82% (18/22). Analysis of the evaluation questionnaires showed that both the app and server components were well accepted by the users.
Our study demonstrated that a simple mobile app, created to self-monitor modifiable cardiorenal risk factors and adherence to therapy, is well tolerated by patients affected by chronic kidney disease. Further studies are required to clarify if the use of this integrated system will have long-term effects on therapy adherence and if self-monitoring of risk factors will improve clinical outcomes in this population. |
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AbstractList | Chronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an additional risk factor for cardiovascular morbidity and mortality. Considering the increased penetration of mobile phones, a mobile app could educate patients to autonomously monitor cardiorenal risk factors.
With this background in mind, we developed an integrated system of a server and app with the aim of improving self-monitoring of cardiovascular and renal risk factors and adherence to therapy.
The software infrastructure for both the Smit-CKD server and Smit-CKD app was developed using standard web-oriented development methodologies preferring open source tools when available. To make the Smit-CKD app suitable for Android and iOS, platforms that allow the development of a multiplatform app starting from a single source code were used. The integrated system was field tested with the help of 22 participants. User satisfaction and adherence to therapy were measured by questionnaires specifically designed for this study; regular use of the app was measured using the daily reports available on the platform.
The Smit-CKD app allows the monitoring of cardiorenal risk factors, such as blood pressure, weight, and blood glucose. Collected data are transmitted in real time to the referring general practitioner. In addition, special reminders improve adherence to the medication regimen. Via the Smit-CKD server, general practitioners can monitor the clinical status of their patients and their adherence to therapy. During the test phase, 73% (16/22) of subjects entered all the required data regularly and sent feedback on drug intake. After 6 months of use, the percentage of regular intake of medications rose from 64% (14/22) to 82% (18/22). Analysis of the evaluation questionnaires showed that both the app and server components were well accepted by the users.
Our study demonstrated that a simple mobile app, created to self-monitor modifiable cardiorenal risk factors and adherence to therapy, is well tolerated by patients affected by chronic kidney disease. Further studies are required to clarify if the use of this integrated system will have long-term effects on therapy adherence and if self-monitoring of risk factors will improve clinical outcomes in this population. Chronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an additional risk factor for cardiovascular morbidity and mortality. Considering the increased penetration of mobile phones, a mobile app could educate patients to autonomously monitor cardiorenal risk factors.BACKGROUNDChronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an additional risk factor for cardiovascular morbidity and mortality. Considering the increased penetration of mobile phones, a mobile app could educate patients to autonomously monitor cardiorenal risk factors.With this background in mind, we developed an integrated system of a server and app with the aim of improving self-monitoring of cardiovascular and renal risk factors and adherence to therapy.OBJECTIVEWith this background in mind, we developed an integrated system of a server and app with the aim of improving self-monitoring of cardiovascular and renal risk factors and adherence to therapy.The software infrastructure for both the Smit-CKD server and Smit-CKD app was developed using standard web-oriented development methodologies preferring open source tools when available. To make the Smit-CKD app suitable for Android and iOS, platforms that allow the development of a multiplatform app starting from a single source code were used. The integrated system was field tested with the help of 22 participants. User satisfaction and adherence to therapy were measured by questionnaires specifically designed for this study; regular use of the app was measured using the daily reports available on the platform.METHODSThe software infrastructure for both the Smit-CKD server and Smit-CKD app was developed using standard web-oriented development methodologies preferring open source tools when available. To make the Smit-CKD app suitable for Android and iOS, platforms that allow the development of a multiplatform app starting from a single source code were used. The integrated system was field tested with the help of 22 participants. User satisfaction and adherence to therapy were measured by questionnaires specifically designed for this study; regular use of the app was measured using the daily reports available on the platform.The Smit-CKD app allows the monitoring of cardiorenal risk factors, such as blood pressure, weight, and blood glucose. Collected data are transmitted in real time to the referring general practitioner. In addition, special reminders improve adherence to the medication regimen. Via the Smit-CKD server, general practitioners can monitor the clinical status of their patients and their adherence to therapy. During the test phase, 73% (16/22) of subjects entered all the required data regularly and sent feedback on drug intake. After 6 months of use, the percentage of regular intake of medications rose from 64% (14/22) to 82% (18/22). Analysis of the evaluation questionnaires showed that both the app and server components were well accepted by the users.RESULTSThe Smit-CKD app allows the monitoring of cardiorenal risk factors, such as blood pressure, weight, and blood glucose. Collected data are transmitted in real time to the referring general practitioner. In addition, special reminders improve adherence to the medication regimen. Via the Smit-CKD server, general practitioners can monitor the clinical status of their patients and their adherence to therapy. During the test phase, 73% (16/22) of subjects entered all the required data regularly and sent feedback on drug intake. After 6 months of use, the percentage of regular intake of medications rose from 64% (14/22) to 82% (18/22). Analysis of the evaluation questionnaires showed that both the app and server components were well accepted by the users.Our study demonstrated that a simple mobile app, created to self-monitor modifiable cardiorenal risk factors and adherence to therapy, is well tolerated by patients affected by chronic kidney disease. Further studies are required to clarify if the use of this integrated system will have long-term effects on therapy adherence and if self-monitoring of risk factors will improve clinical outcomes in this population.CONCLUSIONSOur study demonstrated that a simple mobile app, created to self-monitor modifiable cardiorenal risk factors and adherence to therapy, is well tolerated by patients affected by chronic kidney disease. Further studies are required to clarify if the use of this integrated system will have long-term effects on therapy adherence and if self-monitoring of risk factors will improve clinical outcomes in this population. |
Author | Cutrupi, Demetrio Aiello, Giuseppe Panuccio, Vincenzo Antonio Inguanta, Rosalinda Torino, Claudia Versace, Maria Carmela Li Vigni, Maurizio Tripepi, Giovanni Mezzatesta, Sabrina Villa, Antonino Puglisi, Rossella Vilasi, Antonio Capria, Salvatore Mercuri, Sergio Morante, Salvatore |
AuthorAffiliation | 4 Mercuri Informatica Reggio Calabria Italy 5 Department of Engineering University of Palermo Palermo Italy 2 Nephrology Unit Grande Ospedale Metropolitano Bianchi Melacrino Morelli Reggio Calabria Italy 3 Immedia Società per Azioni Reggio Calabria Italy 1 Institute of Clinical Physiology National Research Council Reggio Calabria Italy |
AuthorAffiliation_xml | – name: 2 Nephrology Unit Grande Ospedale Metropolitano Bianchi Melacrino Morelli Reggio Calabria Italy – name: 4 Mercuri Informatica Reggio Calabria Italy – name: 5 Department of Engineering University of Palermo Palermo Italy – name: 1 Institute of Clinical Physiology National Research Council Reggio Calabria Italy – name: 3 Immedia Società per Azioni Reggio Calabria Italy |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38935948$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.1001/jama.2015.13766 10.1161/circulationaha.109.904003 10.2196/13608 10.2105/ajph.84.6.932 10.2196/27202 10.1371/journal.pone.0158765 10.1016/s0140-6736(14)61774-8 10.1161/01.CIR.0000161956.75255.7B 10.1590/s0100-879x2011007500013 10.2196/29197 10.2196/12442 10.1053/j.ajkd.2004.11.010 10.2196/12604 10.1097/00005650-198601000-00007 10.2196/24030 10.1093/pubmed/fdy088 10.1111/cea.13333 10.1016/S0140-6736(13)61752-3 10.1016/j.maturitas.2012.08.007 10.1161/CIRCULATIONAHA.106.171016 10.2196/14221 10.1007/s00228-013-1639-9 10.1136/jech-2017-209815 10.1002/sim.2832 10.1002/sim.4116 10.2196/25384 10.1038/sj.ki.5000417 10.1371/journal.pone.0177440 10.2196/jmir.5692 10.1111/j.1523-1755.2005.09907.x 10.1016/j.phrs.2017.11.003 10.1007/s11096-018-0756-z 10.1161/01.cir.100.10.1134 10.2196/17342 10.2196/22957 10.2196/18901 10.1093/ije/dyv337 10.1371/journal.pone.0237868 10.1111/j.1753-4887.1958.tb00605.x 10.2196/37291 10.1111/ajag.12606 10.1002/pbc.27278 |
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Copyright | Antonio Vilasi, Vincenzo Antonio Panuccio, Salvatore Morante, Antonino Villa, Maria Carmela Versace, Sabrina Mezzatesta, Sergio Mercuri, Rosalinda Inguanta, Giuseppe Aiello, Demetrio Cutrupi, Rossella Puglisi, Salvatore Capria, Maurizio Li Vigni, Giovanni Tripepi, Claudia Torino. Originally published in JMIR Bioinformatics and Biotechnology (https://bioinform.jmir.org), 15.11.2022. Antonio Vilasi, Vincenzo Antonio Panuccio, Salvatore Morante, Antonino Villa, Maria Carmela Versace, Sabrina Mezzatesta, Sergio Mercuri, Rosalinda Inguanta, Giuseppe Aiello, Demetrio Cutrupi, Rossella Puglisi, Salvatore Capria, Maurizio Li Vigni, Giovanni Tripepi, Claudia Torino. Originally published in JMIR Bioinformatics and Biotechnology (https://bioinform.jmir.org), 15.11.2022. 2022 |
Copyright_xml | – notice: Antonio Vilasi, Vincenzo Antonio Panuccio, Salvatore Morante, Antonino Villa, Maria Carmela Versace, Sabrina Mezzatesta, Sergio Mercuri, Rosalinda Inguanta, Giuseppe Aiello, Demetrio Cutrupi, Rossella Puglisi, Salvatore Capria, Maurizio Li Vigni, Giovanni Tripepi, Claudia Torino. Originally published in JMIR Bioinformatics and Biotechnology (https://bioinform.jmir.org), 15.11.2022. – notice: Antonio Vilasi, Vincenzo Antonio Panuccio, Salvatore Morante, Antonino Villa, Maria Carmela Versace, Sabrina Mezzatesta, Sergio Mercuri, Rosalinda Inguanta, Giuseppe Aiello, Demetrio Cutrupi, Rossella Puglisi, Salvatore Capria, Maurizio Li Vigni, Giovanni Tripepi, Claudia Torino. Originally published in JMIR Bioinformatics and Biotechnology (https://bioinform.jmir.org), 15.11.2022. 2022 |
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Keywords | chronic kidney disease adherence mHealth therapy adherence cardiovascular monitoring risk factor cardiology eHealth renal kidney mobile health health app SMIT-CKD CKD integrated system mobile app cardiac |
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Title | Monitoring Risk Factors and Improving Adherence to Therapy in Patients With Chronic Kidney Disease (Smit-CKD Project): Pilot Observational Study |
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