Observational studyRenal failure2022
A nomogram predicts cardiovascular events in patients with peritoneal dialysis-associated peritonitis.
Observational study in Renal failure, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Increased dialysis symptom index burden in maintenance hemodialysis patients during the COVID-19 lockdown period.Annals of medicine · 2025Article
- Explainable machine learning algorithm to predict cardiovascular event in patients undergoing peritoneal dialysis.BMC medical informatics and decision making · 2025Article
- Analysis of risk factors for depression in peritoneal dialysis patients and establishment of a risk nomogram model.Clinics (Sao Paulo, Brazil) · 2025Article
- A predictive model based on serum bicarbonate for cardiovascular events after initiation of peritoneal dialysis.Renal failure · 2024Observational
- Random forest can accurately predict the technique failure of peritoneal dialysis associated peritonitis patients.Frontiers in medicine · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo predict the risk factors for cardiovascular events within 5 years in patients with peritoneal dialysis-associated peritonitis and establish a nomogram for clinical prediction.
methodsA prediction model was established by conducting an observational study in 150 patients with peritoneal dialysis-associated peritonitis obtained from the Information Database of AnHui Medical University Affiliated Hospital. The nomogram was constructed using the multivariate COX regression model. The C-index and the calibration plot were used to assess the discrimination and calibration of the prediction model.
resultsThe elderly [HR = 2.453 (1.071-5.619)], history of cardiovascular events [HR = 2.296 (1.220-4.321)], alkaline phosphatase [HR = 1.004 (1.002-1.005)] and culture-positive [HR= 2.173 (1.009-4.682)] were identified as risk predictors of cardiovascular events, while serum albumin [HR = 0.396(0.170-0.924)] was identified as protective predictors of cardiovascular events. Combined with clinical studies, we constructed a nomogram based on the minimum value of the Akaike Information Criterion or Bayesian Information Criterion. The C index of the nomogram is 0.732, revealing great discrimination and appropriate calibration. Through the total score of the nomogram and the result of ROC, we classify patients into high-risk groups (cardiovascular events group) and low-risk groups (no cardiovascular events group). Cardiovascular events were significantly different for patients in the high-risk group compared to the low-risk group (HR = 3.862(2.202-6.772;
conclusionsThe current novel nomogram can accurately predict cardiovascular events in patients with peritonitis associated with peritoneal dialysis. However, external validation is required before the model can be used in clinic settings.
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