ArticleClinics (Sao Paulo, Brazil)2025
Analysis of risk factors for depression in peritoneal dialysis patients and establishment of a risk nomogram model.
Article in Clinics (Sao Paulo, Brazil), 2025. 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.
- Comparison and validation of machine learning-based screening models for elevated depressive symptoms in peritoneal dialysis patients.Frontiers in public health · 2026Article
- A narrative review of spatial multi-omics and organ-on-a-chip technologies for cardio-cerebral-renal crosstalk.Frontiers in bioengineering and biotechnology · 2026Review
- Comparison of Depression in Hemodialysis, Peritoneal Dialysis, and Kidney Transplant Patients: A Systematic Review with Meta-Analysis.Journal of personalized medicine · 2025Review
- The association between serum uric acid and depression among U.S. National Health and Nutrition Examination Survey.Frontiers in nutrition · 2025Article
- Development and validation of nursing-oriented risk prediction models for anxiety and depression in hospitalized patients with chronic kidney disease: a retrospective cross-sectional study in Southwest China.Frontiers in psychiatry · 2025Article
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Authors and funding
3 authors.
Funding
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Abstract
objectiveThis study aims to analyze the risk factors for depression in peritoneal dialysis patients and to develop a predictive nomogram model for assessing these risks.
methodsA total of 326 peritoneal dialysis patients treated between August 2021 and December 2023 were selected as the training set. These patients were categorized into a non-depression group (229 cases) and a depression group (97 cases) based on the presence of depression. Additionally, 104 peritoneal dialysis patients from the same period were selected as the validation set. Clinical data were collected from all patients for analysis.
resultsThe depression group had higher proportions of female patients, non-employed individuals, those with a per capita monthly income of <2000-yuan, cardiovascular complications, cerebrovascular complications, and sleep disorders compared to the non-depression group. Additionally, the levels of hemoglobin and blood uric acid were lower in the depression group than in the non-depression group (p < 0.05). Gender, work status, per capita monthly income, cardiovascular complications, cerebrovascular complications, and sleep disorders are risk factors for depression in peritoneal dialysis patients (p < 0.05), while hemoglobin and blood uric acid are protective factors for depression in peritoneal dialysis patients (p < 0.05). Calibration curve analysis results showed that the predicted probability was basically consistent with the actual incidence rate. The results of the Decision Curve Analysis (DCA) demonstrated that the nomogram model developed in this study has strong clinical applicability.
conclusionThe nomogram model for predicting depression in peritoneal dialysis patients, which incorporates factors such as gender, work status, per capita monthly income, cardiovascular complications, cerebrovascular complications, sleep disorders, hemoglobin levels, and blood uric acid levels, demonstrates excellent calibration and discrimination. Additionally, it has high clinical applicability.
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