Development of a risk prediction model for infection-related mortality in patients undergoing peritoneal dialysis

Hiroaki Tsujikawa, Shigeru Tanaka, Yuta Matsukuma, Hidetoshi Kanai, Kumiko Torisu, Toshiaki Nakano, Kazuhiko Tsuruya, Takanari Kitazono

研究成果: ジャーナルへの寄稿記事

1 引用 (Scopus)


Background Assessment of infection-related mortality remains inadequate in patients undergoing peritoneal dialysis. This study was performed to develop a risk model for predicting the 2-year infection-related mortality risk in patients undergoing peritoneal dialysis. Methods The study cohort comprised 606 patients who started and continued peritoneal dialysis for 90 at least days and was drawn from the Fukuoka Peritoneal Dialysis Database Registry Study in Japan. The patients were registered from 1 January 2006 to 31 December 2016 and followed up until 31 December 2017. To generate a prediction rule, the score for each variable was weighted by the regression coefficients calculated using a Cox proportional hazard model adjusted by risk factors for infection-related mortality, including patient characteristics, comorbidities, and laboratory data. Results During the follow-up period (median, 2.2 years), 138 patients died; 58 of them of infectious disease. The final model for infection-related mortality comprises six factors: age, sex, serum albumin, serum creatinine, total cholesterol, and weekly renal Kt/V. The incidence of infection-related mortality increased linearly with increasing total risk score (P for trend <0.001). Furthermore, the prediction model showed adequate discrimination (c-statistic = 0.79 [0.72–0.86]) and calibration (Hosmer–Lemeshow test, P = 0.47). Conclusion In this study, we developed a new model using clinical measures for predicting infection-related mortality in patients undergoing peritoneal dialysis.

ジャーナルPloS one
出版物ステータス出版済み - 3 2019


All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General