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Development and validation of a prediction model for loss of physical function in elderly hemodialysis patients
- Source :
- Nephrology Dialysis Transplantation
- Publication Year :
- 2017
- Publisher :
- Oxford University Press, 2017.
-
Abstract
- Background Among aging hemodialysis patients, loss of physical function has become a major issue. We developed and validated a model of predicting loss of physical function among elderly hemodialysis patients. Methods We conducted a cohort study involving maintenance hemodialysis patients ≥65 years of age from the Dialysis Outcomes and Practice Pattern Study in Japan. The derivation cohort included 593 early phase (1996–2004) patients and the temporal validation cohort included 447 late-phase (2005–12) patients. The main outcome was the incidence of loss of physical function, defined as the 12-item Short Form Health Survey physical function score decreasing to 0 within a year. Using backward stepwise logistic regression by Akaike’s Information Criteria, six predictors (age, gender, dementia, mental health, moderate activity and ascending stairs) were selected for the final model. Points were assigned based on the regression coefficients and the total score was calculated by summing the points for each predictor. Results In total, 65 (11.0%) and 53 (11.9%) hemodialysis patients lost their physical function within 1 year in the derivation and validation cohorts, respectively. This model has good predictive performance quantified by both discrimination and calibration. The proportion of the loss of physical function increased sequentially through low-, middle-, and high-score categories based on the model (2.5%, 11.7% and 22.3% in the validation cohort, respectively). The loss of physical function was strongly associated with 1-year mortality [adjusted odds ratio 2.48 (95% confidence interval 1.26–4.91)]. Conclusions We developed and validated a risk prediction model with good predictive performance for loss of physical function in elderly hemodialysis patients. Our simple prediction model may help physicians and patients make more informed decisions for healthy longevity.
- Subjects :
- Male
medicine.medical_specialty
medicine.medical_treatment
030232 urology & nephrology
Motor Activity
elderly
Risk Assessment
03 medical and health sciences
risk prediction
0302 clinical medicine
physical function
Japan
Renal Dialysis
Risk Factors
Internal medicine
Linear regression
Outcome Assessment, Health Care
medicine
Humans
030212 general & internal medicine
Prospective Studies
Prospective cohort study
Dialysis
Aged
Aged, 80 and over
Transplantation
business.industry
Incidence
Odds ratio
Original Articles
Stepwise regression
Middle Aged
Confidence interval
Nephrology
Cardiovascular Diseases
Female
Hemodialysis
business
Cohort study
Subjects
Details
- Language :
- English
- ISSN :
- 14602385 and 09310509
- Volume :
- 33
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- Nephrology Dialysis Transplantation
- Accession number :
- edsair.doi.dedup.....6520575e75adcda6a966bbf6c0d3c666