Nomogram to Estimate the Risk of Chronic Kidney Disease-associated Pruritus in Patients with End-Stage Renal Disease Undergoing Peritoneal Dialysis: Model Development and Validation Study.

INTRODUCTION: Chronic kidney disease associated pruritus (CKD-aP) frequently occurs in patients with end-stage renal disease (ESRD) undergoing peritoneal dialysis (PD) and presents a therapeutic challenge to physicians owing to the diversity of its pathogenesis. Herein, we developed and validated a nomogram model for individualized risk estimation of CKD-aP and investigate the possible causes of CKD-aP in PD patients. METHODS: We retrospectively screened patients with CKD-aP who underwent PD between 2021 and 2023 at the First Affiliated Hospital of Xi'an Jiaotong University Peritoneal Dialysis Center. Nomograms for each outcome were computed from multivariate logistic regression models with the least absolute shrinkage and selection operator regression and univariate logistic regression for variable selection. The discriminative ability was estimated by Harrell's C-index, and the accuracy was assessed graphically with a calibration curve plot. Models were validated internally using bootstrapping and externally by calculating their performance on a validation cohort. Decision curve analysis was used to assess the model's clinical usefulness. RESULTS: In all, a total of 487 patients were entered in the analysis, including 325 in the development cohort and 162 in the validation cohort. The final nomogram incorporated four variables: age, interleukin-6, hemoglobin, residual urine volume, and renal Kt/V. The C-index of the model was 0.733 (95% CI 0.679-0.787), and the calibration curve was a straight line with a slope close to 1. Both internal and external validations confirmed the model's good performance, with C-index of 0.725 (95% CI 0.662-0.774) and 0.706 (95% CI 0.623-0.789), respectively. Decision curve analysis showed that the nomogram had good clinical benefits. CONCLUSION: Our study proposes a nomogram model for CKD-aP risk assessment in ESRD patients with PD. This nomogram might help in clinical decision-making and evidence-based selection of therapy.

The Long COVID Symptoms and Severity Score: Development, Validation, and Application.

OBJECTIVES: The primary focus of this research is the proposition of a methodological framework for the clinical application of the long COVID symptoms and severity score (LC-SSS). This tool is not just a self-reported assessment instrument developed and validated but serves as a standardized, quantifiable means to monitor the diverse and persistent symptoms frequently observed in individuals with long COVID. METHODS: A 3-stage process was used to develop, validate, and establish scoring standards for the LC-SSS. Validation measures included correlations with other patient-reported measures, confirmatory factor analysis, Cronbach's α for internal consistency, and test-retest reliability. Scoring standards were determined using K-means clustering, with comparative assessments made against hierarchical clustering and the Gaussian Mixture Model. RESULTS: The LC-SSS showed correlations with EuroQol 5-Dimension 5-Level (rs = -0.55), EuroQol visual analog scale (rs = -0.368), Patient Health Questionnaire-9 (rs = 0.538), Beck Anxiety Inventory (rs = 0.689), and Insomnia Severity Index (rs = 0.516), confirming its construct validity. Structural validity was good with a comparative fit index of 0.969, with Cronbach's α of 0.93 indicating excellent internal consistency. Test-retest reliability was also satisfactory (intraclass correlation coefficient 0.732). K-means clustering identified 3 distinct severity categories in individuals living with long COVID, providing a basis for personalized treatment strategies. CONCLUSIONS: The LC-SSS provides a robust and valid tool for assessing long COVID. The severity categories established via K-means clustering demonstrate significant variation in symptom severity, informing personalized treatment and improving care quality for patients with long COVID.

Abnormal grey matter structural changes in patients with end-stage kidney disease and mild cognitive impairment: correlations with clinical features.

End-stage kidney disease and mild cognitive impairment (ESKD-MCI) affect the quality of life and long-term treatment outcomes of patients affected by these diseases. Clarifying the morphological changes from brain injuries in ESKD-MCI and their relationship with clinical features is helpful for the early identification and intervention of MCI before it progresses to irreversible dementia. This study gathered data from 23 patients with ESKD-MCI, 24 patients with ESKD and non-cognitive impairment (NCI), and 27 health controls (HCs). Structural magnetic resonance studies, cognitive assessments, and general clinical data were collected from all participants. Voxel-based morphometry analysis was performed to compare grey matter (GM) volume differences between the groups. The patients' GM maps and clinical features were subjected to univariate regression to check for possible correlations. Patients with ESKD-MCI displayed significantly more impairments in multiple cognitive domains, including global cognition, visuospatial and executive function, and memory, compared to patients with ESKD-NCI. Using a more liberal threshold (P < 0.001, uncorrected), we found that compared to patients with ESKD-NCI, patients with ESKD-MCI exhibited clusters of regions with lower GM volumes, including the right hippocampus (HIP), parahippocampal gyrus (PHG), Rolandic operculum, and supramarginal gyrus. The volumes of the right HIP and PHG were negatively correlated with serum calcium levels. ESKD-MCI was associated with a subtle volume reduction of GM in several brain areas known to be involved in memory, language, and auditory information processing. We speculate that these slight morphometric impairments may be associated with disturbed calcium metabolism.