Scientists develop self-assessment tool to predict chronic kidney disease risk

December 23rd, 2008 - 2:04 pm ICT by ANI  

Washington, Dec 23 (ANI): Researchers have developed a simple self-assessment tool that can accurately predict those at an increased risk of developing chronic kidney disease.
Scientists from NewYork-Presbyterian Hospital/Weill Cornell Medical Center and the University of North Carolina at Chapel Hill have developed a eight-point risk factor checklist that can accurately stratify middle-aged and older patients at high risk for newly diagnosed CKD, which involves a gradual, even fatal loss of kidney function over time.
The eight key risk factors are older age, anaemia, female sex, hypertension, diabetes, peripheral vascular disease, and any history of congestive heart failure or cardiovascular disease,
“Each of the eight components that make up the score is also easy to identify or quickly assess during any doctor-patient interview,” said Dr. Abhijit V. Kshirsagar of the University of North Carolina Kidney Center, Chapel Hill, and the study’’s lead author.
“Patients themselves can even self-assess using the tool, and bring their concerns to their doctor, if need be,” he added.
“These patients are often battling concurrent conditions such as diabetes or heart disease, so anything we can do to predict and then lower their risk for kidney disease will be invaluable,” said study senior author Dr. Phyllis A. August, the Ralph A. Baer Professor of Medical Research at Weill Cornell Medical College, and an internist and nephrologist at NewYork-Presbyterian Hospital/Weill Cornell Medical Centre.
During the study, the researchers combined data from two major studies, which included a total 14,155 men and women aged 45 years or older.
All of the participants had a glomerular filtration rate exceeding 60 mL/min/1.73m2 at the beginning of the study - indicating their kidneys were functioning at a normal healthy level at that time.
The researchers then tracked the health of the participants during a follow-up of up to nine years, recording those participants whose filtration rate fell below the healthy 60 mL/min/1.73 m2 threshold.
They also tracked a wide variety of risk factors thought important to the onset of CKD.
Overall, a total of 1,605 participants from the two cohorts went on to develop CKD over the course of follow-up.
“We discovered that a scoring system that included eight key risk factors - older age, anaemia, female sex, hypertension, diabetes, peripheral vascular disease and any history of congestive heart failure or cardiovascular disease - accurately predicted which of the older patients would proceed to CKD and which would not,” said study co-author Dr. Heejung Bang, assistant professor in the Division of Biostatistics and Epidemiology in the Department of Public Health at Weill Cornell Medical College.
Older age, at or over 70, was of highest predictive significance. Scoring a total of just three points in the model captured 70 percent of those patients who would go on to develop CKD over the next 10 years. (ANI)
Washington, Dec 23 (ANI): Researchers have developed a simple self-assessment tool that can accurately predict those at an increased risk of developing chronic kidney disease.
Scientists from NewYork-Presbyterian Hospital/Weill Cornell Medical Center and the University of North Carolina at Chapel Hill have developed a eight-point risk factor checklist that can accurately stratify middle-aged and older patients at high risk for newly diagnosed CKD, which involves a gradual, even fatal loss of kidney function over time.
The eight key risk factors are older age, anaemia, female sex, hypertension, diabetes, peripheral vascular disease, and any history of congestive heart failure or cardiovascular disease,
“Each of the eight components that make up the score is also easy to identify or quickly assess during any doctor-patient interview,” said Dr. Abhijit V. Kshirsagar of the University of North Carolina Kidney Center, Chapel Hill, and the study’’s lead author.
“Patients themselves can even self-assess using the tool, and bring their concerns to their doctor, if need be,” he added.
“These patients are often battling concurrent conditions such as diabetes or heart disease, so anything we can do to predict and then lower their risk for kidney disease will be invaluable,” said study senior author Dr. Phyllis A. August, the Ralph A. Baer Professor of Medical Research at Weill Cornell Medical College, and an internist and nephrologist at NewYork-Presbyterian Hospital/Weill Cornell Medical Centre.
During the study, the researchers combined data from two major studies, which included a total 14,155 men and women aged 45 years or older.
All of the participants had a glomerular filtration rate exceeding 60 mL/min/1.73m2 at the beginning of the study - indicating their kidneys were functioning at a normal healthy level at that time.
The researchers then tracked the health of the participants during a follow-up of up to nine years, recording those participants whose filtration rate fell below the healthy 60 mL/min/1.73 m2 threshold.
They also tracked a wide variety of risk factors thought important to the onset of CKD.
Overall, a total of 1,605 participants from the two cohorts went on to develop CKD over the course of follow-up.
“We discovered that a scoring system that included eight key risk factors - older age, anaemia, female sex, hypertension, diabetes, peripheral vascular disease and any history of congestive heart failure or cardiovascular disease - accurately predicted which of the older patients would proceed to CKD and which would not,” said study co-author Dr. Heejung Bang, assistant professor in the Division of Biostatistics and Epidemiology in the Department of Public Health at Weill Cornell Medical College.
Older age, at or over 70, was of highest predictive significance. Scoring a total of just three points in the model captured 70 percent of those patients who would go on to develop CKD over the next 10 years. (ANI)

Related Stories

Tags: , , , , , , , , , , , , , , , , , , ,

Posted in Health Science |

Subscribe