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Reno-Metabolic Multimorbidity and Psychiatric Comorbidity: Development of a Renal–Psychiatric/Psychosomatic Burden Score in a Real-World Cohort

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Background and Objectives: Renal and metabolic disorders frequently coexist with psychiatric and psychosomatic conditions, forming complex multimorbidity clusters that challenge traditional models of care. Anxiety, depression, and stress-related disorders may amplify the clinical trajectory of chronic kidney disease (CKD) and metabolic dysfunction. This study aimed to characterize the renal–psychiatric/psychosomatic burden profile of a real-world clinical cohort and to introduce a novel integrative multimorbidity score (RePsy-Risk) quantifying the combined renal, metabolic, and psychiatric burden. Materials and Methods: We conducted a cross-sectional analysis of 148 adult patients stratified into a reno-metabolic group (group 1) and a comparison group with other comorbidities (group 2). Clinical, biochemical, and psychiatric data were extracted from routine medical records. RePsy-Risk was constructed from three domains: renal impairment (eGFR, UACR), metabolic load (TyG index, diabetes/metabolic diagnosis), and psychiatric/psychosomatic involvement (diagnostic text-mining, psychotropic treatment). Group differences were assessed using Mann–Whitney U and t-tests, and associations were explored via Spearman correlation and heatmap visualization. Results: The reno-metabolic group exhibited significantly higher serum creatinine (1.07 vs. 0.86 mg/dL, p = 0.0027), a greater medication burden (7.07 vs. 5.70 drugs, p = 0.0007), and a higher RePsy-Risk score (mean 4.11 vs. 3.20, p = 0.00028). Overall, 52.0% of patients were classified as low risk, 45.3% as moderate risk, and 2.7% as high risk. RePsy-Risk correlated strongly with renal dysfunction (eGFR: ρ = –0.62; UACR: ρ = 0.38) and with metabolic load (TyG: ρ = 0.53), while psychiatric factors contributed independently (RePsy_C: ρ = 0.48). Heatmap analysis confirmed clustering of renal and metabolic domains, with psychosomatic features forming a distinct but additive dimension. Conclusions: Reno-metabolic disease is associated with a significantly elevated renal–psychiatric/psychosomatic burden, shaped by the interplay between impaired renal function, metabolic stress, and psychiatric comorbidity. The RePsy-Risk score offers a practical tool for capturing this multidimensional vulnerability, highlighting the need for integrated clinical strategies that simultaneously address renal, metabolic, and mental health pathways. Further validation in larger cohorts is warranted.
Title: Reno-Metabolic Multimorbidity and Psychiatric Comorbidity: Development of a Renal–Psychiatric/Psychosomatic Burden Score in a Real-World Cohort
Description:
Background and Objectives: Renal and metabolic disorders frequently coexist with psychiatric and psychosomatic conditions, forming complex multimorbidity clusters that challenge traditional models of care.
Anxiety, depression, and stress-related disorders may amplify the clinical trajectory of chronic kidney disease (CKD) and metabolic dysfunction.
This study aimed to characterize the renal–psychiatric/psychosomatic burden profile of a real-world clinical cohort and to introduce a novel integrative multimorbidity score (RePsy-Risk) quantifying the combined renal, metabolic, and psychiatric burden.
Materials and Methods: We conducted a cross-sectional analysis of 148 adult patients stratified into a reno-metabolic group (group 1) and a comparison group with other comorbidities (group 2).
Clinical, biochemical, and psychiatric data were extracted from routine medical records.
RePsy-Risk was constructed from three domains: renal impairment (eGFR, UACR), metabolic load (TyG index, diabetes/metabolic diagnosis), and psychiatric/psychosomatic involvement (diagnostic text-mining, psychotropic treatment).
Group differences were assessed using Mann–Whitney U and t-tests, and associations were explored via Spearman correlation and heatmap visualization.
Results: The reno-metabolic group exhibited significantly higher serum creatinine (1.
07 vs.
0.
86 mg/dL, p = 0.
0027), a greater medication burden (7.
07 vs.
5.
70 drugs, p = 0.
0007), and a higher RePsy-Risk score (mean 4.
11 vs.
3.
20, p = 0.
00028).
Overall, 52.
0% of patients were classified as low risk, 45.
3% as moderate risk, and 2.
7% as high risk.
RePsy-Risk correlated strongly with renal dysfunction (eGFR: ρ = –0.
62; UACR: ρ = 0.
38) and with metabolic load (TyG: ρ = 0.
53), while psychiatric factors contributed independently (RePsy_C: ρ = 0.
48).
Heatmap analysis confirmed clustering of renal and metabolic domains, with psychosomatic features forming a distinct but additive dimension.
Conclusions: Reno-metabolic disease is associated with a significantly elevated renal–psychiatric/psychosomatic burden, shaped by the interplay between impaired renal function, metabolic stress, and psychiatric comorbidity.
The RePsy-Risk score offers a practical tool for capturing this multidimensional vulnerability, highlighting the need for integrated clinical strategies that simultaneously address renal, metabolic, and mental health pathways.
Further validation in larger cohorts is warranted.

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