Interactive exploration of adverse events and multimorbidity in CKD

Abstract

Background: Persons with chronic kidney disease (CKD) are at increased risk of adverse events, early mortality and multimorbidity. A detailed overview of adverse event types and rates from a large CKD cohort under regular nephrological care is missing. We generated an interactive tool to enable exploration of adverse events and their combinations in the prospective, observational German CKD (GCKD) study.

Methods: The GCKD study enrolled 5217 participants under regular nephrological care with an estimated glomerular filtration rate of 30-60 or >60 mL/min/1.73 m2 and an overt proteinuria. Cardiovascular, cerebrovascular and peripheral vascular, kidney, infection, and cancer events, as well as deaths were adjudicated following a standard operation procedure. We summarized these time-to-event data points for exploration in interactive graphs within an R shiny app. Multivariable adjusted Cox models for time to first event were fitted. Cumulative incidence functions, Kaplan-Meier curves and intersection plots were used to display main adverse events and their combinations by sex and CKD etiology.

Results: Over a median of 6.5 years, 10 271 events occurred in 2947 participants (56.5%), of which 680 participants (13.0%) died. The new publicly available interactive platform enables readers to scrutinize adverse events and their combinations as well as mortality trends as a gateway to better understand multimorbidity in CKD: incident rates per 1000 patient-years varied by event type, CKD etiology and baseline characteristics. Incidence rates for the most frequent events and their recurrence were 113.6 (cardiovascular), 75.0 (kidney) and 66.0 (infection). Participants with presumed diabetic kidney disease and men were more prone to experiencing events.

Conclusion: This comprehensive explorative tool to visualize adverse events (https://www.gckd.org/studienhintergrund/previous-study-results/event-analysis/), their combination, mortality and multimorbidity among persons with CKD may serve as a valuable resourec for patient care, identification of high-risk groups, health services and public health policy planning.

Keywords: adverse events; chronic kidney disease; epidemiology; interactive visualization; multimorbidity.

Figure 1:

Kaplan–Meier survival curve for all-cause mortality by sex and primary cause of kidney disease. Solid lines represent male (m) participants, dashed lines female (f) participants. Green: DKD as presumed primary cause of kidney disease; blue: HKD as presumed primary cause of kidney disease; red: PGD as presumed primary kidney disease; black: MISC = any other primary cause of kidney disease. Men diagnosed with DKD had the highest risk of death; women with DKD had a similar risk of death as men with HKD. Men with PGD were at similar risk of death as women with either HKD or MISC. Women with PGD had the lowest risk of death.

Figure 2:

Intersection plot of main adverse event categories and their combinations after 6.5 years of follow-up. Main event categories: cardiovascular (“A”), cerebrovascular (“B”), peripheral arterial occlusive disease (PAOD, “C”), kidney (“E”), death (“F”), cancer (“G”), infection (“H”). Plots include recurrent events. Colored intersection plot: indicates intersection of event combinations in main event categories, e.g. 176 participants experienced a combination of adverse kidney events and infection events until the end of the follow-up period, while a total of 787 participants experienced adverse events in two event categories overall. Stacked barplot: number of participants in each intersection by sex. Colored barplot: number of participants with events of a main event category is plotted. *Total number of participants with events in one to five event categories. Intersections with fewer than 11 participants are not shown here. In total, 11 participants had events in six event categories.

Figure 3:

Cumulative incidence function for kidney failure by sex for KDIGO eGFR and/or UACR categories. Panel (A) by eGFR categories (G1–5), panel (B) by UACR categories (A1–3), (C) combined eGFR and UACR categories. Green: low-risk categories (G1/2A1), yellow: medium-risk categories (G3aA1, G1/2A2, orange: medium-high risk (G3bA1, G3aA2, G1/2A3) and red: high risk categories (G3aA3, G3bA2/3, G4A1–3, G5A1–3). m = men, solid lines; f = women, dashed lines.

Figure 4:

Cumulative incidence function for myocardial infarction by sex for KDIGO eGFR and/or UACR categories. Panel (A) by eGFR categories (G1–5), (B) by UACR categories (A1–3), (C) combined eGFR and UACR categories. Green: low-risk categories, yellow: medium-risk categories, orange: medium-high risk and red: high risk categories. m = men, solid lines; f = women, dashed lines.