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Introduction: Inflammation is highly prevalent among patients with end-stage kidney disease and is associated with adverse outcomes. We aimed to investigate longitudinal changes in inflammatory markers in a diverse international incident hemodialysis patient population. Methods: The MONitoring Dialysis Outcomes (MONDO) Consortium encompasses hemodialysis databases from 31 countries in Europe, North America, South America, and Asia. The MONDO database was queried for inflammatory markers (total white blood cell count [WBC], neutrophil count, lymphocyte count, serum albumin, and C-reactive protein [CRP]) and hemoglobin levels in incident hemodialysis patients. Laboratory parameters were measured every month. Patients were stratified by survival time (≤6 months, >6 to 12 months, >12 to 18 months, >18 to 24 months, >24 to 30 months, >30 to 36 months, and >36 months) following dialysis initiation. We used cubic B-spline basis function to evaluate temporal changes in inflammatory parameters in relationship with patient survival. Results: We studied 18,726 incident hemodialysis patients. Their age at dialysis initiation was 71.3 ± 11.9 years; 10,802 (58%) were males. Within the first 6 months, 2068 (11%) patients died, and 12,295 patients (67%) survived >36 months (survivor cohort). Hemodialysis patients who died showed a distinct biphasic pattern of change in inflammatory markers where an initial decline of inflammation was followed by a rapid rise that was consistently evident approximately 6 months before death. This pattern was similar in all patients who died and was consistent across the survival time intervals. In contrast, in the survivor cohort, we observed initial decline of inflammation followed by sustained low levels of inflammatory biomarkers. Conclusion: Our international study of incident hemodialysis patients highlights a temporal relationship between serial measurements of inflammatory markers and patient survival. This finding may inform the development of prognostic models, such as the integration of dynamic changes in inflammatory markers for individual risk profiling and guiding preventive and therapeutic interventions.
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BACKGROUND: We developed machine learning models to understand the predictors of shorter-, intermediate-, and longer-term mortality among hemodialysis (HD) patients affected by COVID-19 in four countries in the Americas. METHODS: We used data from adult HD patients treated at regional institutions of a global provider in Latin America (LatAm) and North America who contracted COVID-19 in 2020 before SARS-CoV-2 vaccines were available. Using 93 commonly captured variables, we developed machine learning models that predicted the likelihood of death overall, as well as during 0-14, 15-30, > 30 days after COVID-19 presentation and identified the importance of predictors. XGBoost models were built in parallel using the same programming with a 60%:20%:20% random split for training, validation, & testing data for the datasets from LatAm (Argentina, Columbia, Ecuador) and North America (United States) countries. RESULTS: Among HD patients with COVID-19, 28.8% (1,001/3,473) died in LatAm and 20.5% (4,426/21,624) died in North America. Mortality occurred earlier in LatAm versus North America; 15.0% and 7.3% of patients died within 0-14 days, 7.9% and 4.6% of patients died within 15-30 days, and 5.9% and 8.6% of patients died > 30 days after COVID-19 presentation, respectively. Area under curve ranged from 0.73 to 0.83 across prediction models in both regions. Top predictors of death after COVID-19 consistently included older age, longer vintage, markers of poor nutrition and more inflammation in both regions at all timepoints. Unique patient attributes (higher BMI, male sex) were top predictors of mortality during 0-14 and 15-30 days after COVID-19, yet not mortality > 30 days after presentation. CONCLUSIONS: Findings showed distinct profiles of mortality in COVID-19 in LatAm and North America throughout 2020. Mortality rate was higher within 0-14 and 15-30 days after COVID-19 in LatAm, while mortality rate was higher in North America > 30 days after presentation. Nonetheless, a remarkable proportion of HD patients died > 30 days after COVID-19 presentation in both regions. We were able to develop a series of suitable prognostic prediction models and establish the top predictors of death in COVID-19 during shorter-, intermediate-, and longer-term follow up periods.
