Associations of Anxiety during the COVID-19 Pandemic with Patient Characteristics and Behaviors in CKD Patients: Findings from the Chronic Renal Insufficiency Cohort (CRIC) Study.

Background: Chronic kidney disease (CKD) is associated with anxiety and depression. Although the coronavirus disease 2019 (COVID-19) pandemic has increased stressors on patients with CKD, assessments of anxiety and its predictors and consequences on behaviors, specifically virus mitigation behaviors, are lacking. Methods: From June to October 2020, we administered a survey to 1873 patients in the Chronic Renal Insufficiency Cohort (CRIC) Study, asking participants about anxiety related to the COVID-19 pandemic. We examined associations between anxiety and participant demographics, clinical indexes, and health literacy and whether anxiety was associated with health-related behaviors and COVID-19 mitigation behaviors. Results: The mean age of the study population was 70 years (SD=9.6 years), 47% were women, 39% were Black non-Hispanic, 14% were Hispanic, and 38% had a history of cardiovascular disease. In adjusted analyses, younger age, being a woman, Hispanic ethnicity, cardiovascular disease, household income <$20,000, and marginal or inadequate health literacy predicted higher anxiety. Higher global COVID-19-related anxiety scores were associated with higher odds of reporting always wearing a mask in public (OR=1.3 [95% CI, 1.14 to 1.48], P<0.001) and of eating less healthy foods (OR=1.29 [95% CI, 1.13 to 1.46], P<0.001), reduced physical activity (OR=1.32 [95% CI, 1.2 to 1.45], P<0.001), and weight gain (OR=1.23 [95% CI, 1.11 to 1.38], P=0.001). Conclusions: Higher anxiety levels related to the COVID-19 pandemic were associated not only with higher self-reported adherence to mask wearing but also with higher weight gain and less adherence to healthy lifestyle behaviors. Interventions are needed to support continuation of healthy lifestyle behaviors in patients with CKD experiencing increased anxiety related to the pandemic.

Subtyping CKD Patients by Consensus Clustering: The Chronic Renal Insufficiency Cohort (CRIC) Study.

BACKGROUND: CKD is a heterogeneous condition with multiple underlying causes, risk factors, and outcomes. Subtyping CKD with multidimensional patient data holds the key to precision medicine. Consensus clustering may reveal CKD subgroups with different risk profiles of adverse outcomes. METHODS: We used unsupervised consensus clustering on 72 baseline characteristics among 2696 participants in the prospective Chronic Renal Insufficiency Cohort (CRIC) study to identify novel CKD subgroups that best represent the data pattern. Calculation of the standardized difference of each parameter used the cutoff of ±0.3 to show subgroup features. CKD subgroup associations were examined with the clinical end points of kidney failure, the composite outcome of cardiovascular diseases, and death. RESULTS: The algorithm revealed three unique CKD subgroups that best represented patients' baseline characteristics. Patients with relatively favorable levels of bone density and cardiac and kidney function markers, with lower prevalence of diabetes and obesity, and who used fewer medications formed cluster 1 (n=1203). Patients with higher prevalence of diabetes and obesity and who used more medications formed cluster 2 (n=1098). Patients with less favorable levels of bone mineral density, poor cardiac and kidney function markers, and inflammation delineated cluster 3 (n=395). These three subgroups, when linked with future clinical end points, were associated with different risks of CKD progression, cardiovascular disease, and death. Furthermore, patient heterogeneity among predefined subgroups with similar baseline kidney function emerged. CONCLUSIONS: Consensus clustering synthesized the patterns of baseline clinical and laboratory measures and revealed distinct CKD subgroups, which were associated with markedly different risks of important clinical outcomes. Further examination of patient subgroups and associated biomarkers may provide next steps toward precision medicine.