Early onset peritonitis (EOP) increases the risk of clinical complications in patients initializing peritoneal dialysis (PD). This study aimed to develop and validate a risk prediction model for EOP among patients initializing PD. Methods: 3772 patients registered with the Henan Peritoneal Dialysis Registry (HPDR) between 2007 and 2015 were included. The main outcome, EOP, was defined as incident peritonitis occurring within 6 months of the initialization of PD. Multivariable logistic regression modeling was applied to derive the risk score. All accessible clinical measurements were screened as potential predictors. Assessment of the developed model in terms of model discrimination and calibration was performed using C statistics and a calibration slope, respectively, and validated internally through a bootstrapping (1000-fold) method to adjust for over-fitting. Results: The absolute risk of EOP was 14.5%. Age, cardiac function measurements, serum electrolyte test items, lipid profiles, liver function test items, blood urea nitrogen, and white cell count were significant predictors of EOP in the final risk score. Good model discrimination, with C statistics above 0.70, and calibration of agreed observed and predicted risks were identified in the model.
Conclusion:A prediction model that quantifies risks of EOP has been developed and validated. It is based on a small number of clinical metabolic measurements that are available for patients initializing PD in many developing countries, and could serve as a tool to screen the population at high risk of EOP.