Ma, S, Cai, Y, Wang, Z, Zhao, Z, Xiao, J and Yu, D (2020) Derivation and validation of a risk score predicting early-onset risk of peritonitis among patients initialising peritoneal dialysis: a cohort study. International Journal of Infectious Diseases, 99. pp. 301-306. ISSN 1201-9712

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Early onset peritonitis (EOP) increases risk of clinical complications in patients initialising peritoneal dialysis (PD). This study aimed to develop and validate a risk prediction model for EOP among patients initialising PD.

3,772 patients registered with the Henan Peritoneal Dialysis Registry (HPDR) between 2007-2015 were included. The main outcome, EOP was defined as the incident peritonitis occurred within 6 months since the initialisation of PD. Multivariable logistic regression modelling was applied to derive the risk score. All accessible clinical measurements were screened as potential predictors. Assessment of the developed model regarding model discrimination and calibration was performed by C statistics and calibration slope, respectively, and validated internally through bootstrapping (1000-fold)
method to adjust for over-fitting.

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.

The prediction model that quantify risks of EOP has been developed and validated. It is based on a small number of clinical metabolic measurements that are available for patients initialising PD in many developing countries and could serve as the tools to screen the population at high risk of EOP.

Item Type: Article
Additional Information: The final version of this article and all relevant information regarding this article can be found at;
Uncontrolled Keywords: Early-onset peritonitis, Peritoneal dialysis, Prognostic model, Cohort
Subjects: Q Science > Q Science (General)
R Medicine > R Medicine (General)
Divisions: Faculty of Medicine and Health Sciences > School of Primary, Community and Social Care
Depositing User: Symplectic
Date Deposited: 10 Aug 2020 15:07
Last Modified: 12 Nov 2020 10:46

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