Identifying key predictors of mortality in young patients on chronic haemodialysis-a machine learning approach
Verena Gotta1, Georgi Tancev2, Olivera Marsenic3
1Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland.
Insights
Mortality in children and adults on chronic haemodialysis is linked to nutrition, inflammation, and anaemia markers. Elevated lactate dehydrogenase (LDH) is a newly identified predictor, suggesting broader health issues beyond dialysis adequacy.
Area of Science:
- Nephrology
- Paediatric Nephrology
- Clinical Medicine
Background:
- Chronic haemodialysis (HD) treatment presents significant mortality risks for both paediatric and adult patients.
- Identifying factors predicting mortality is crucial for improving outcomes in this vulnerable population.
Purpose of the Study:
- To identify factors associated with 5-year mortality in patients who initiated chronic haemodialysis (HD) in childhood and continued into adulthood.
- To explore the predictive value of various demographic, treatment, and laboratory variables on mortality risk.
Main Methods:
- A cohort of 363 patients who started HD before age 30 (≤19 years) between 2004-2016 was analyzed.
- Machine learning (random forest) was used to evaluate 105 variables for predicting 5-year mortality.
- Patients with at least 5 years of follow-up or death within 5 years were included.
Main Results:
- Low serum albumin and elevated lactate dehydrogenase (LDH) were the strongest predictors of 5-year mortality.
- Other significant predictors included elevated red blood cell distribution width, blood pressure, and decreased red blood cell count, haemoglobin, albumin:globulin ratio, ultrafiltration rate, z-score weight for age, or single-pool Kt/V.
- The model achieved an 81% accuracy in predicting mortality.
Conclusions:
- Mortality in young HD patients is multifactorial, involving nutrition, inflammation, anaemia, and dialysis dose.
- Elevated LDH is a novel predictor, potentially indicating blood-membrane interactions or organ malperfusion.
- Multimodal interventions beyond dialysis adequacy (Kt/V) are essential for improving survival in this population.
Background:
The mortality risk remains significant in paediatric and adult patients on chronic haemodialysis (HD) treatment. We aimed to identify factors associated with mortality in patients who started HD as children and continued HD as adults.
Methods:
The data originated from a cohort of patients <30 years of age who started HD in childhood (≤19 years) on thrice-weekly HD in outpatient DaVita dialysis centres between 2004 and 2016. Patients with at least 5 years of follow-up since the initiation of HD or death within 5 years were included; 105 variables relating to demographics, HD treatment and laboratory measurements were evaluated as predictors of 5-year mortality utilizing a machine learning approach (random forest).
Results:
A total of 363 patients were included in the analysis, with 84 patients having started HD at <12 years of age. Low albumin and elevated lactate dehydrogenase (LDH) were the two most important predictors of 5-year mortality. Other predictors included elevated red blood cell distribution width or blood pressure and decreased red blood cell count, haemoglobin, albumin:globulin ratio, ultrafiltration rate, z-score weight for age or single-pool Kt/V (below target). Mortality was predicted with an accuracy of 81%.
Conclusions:
Mortality in paediatric and young adult patients on chronic HD is associated with multifactorial markers of nutrition, inflammation, anaemia and dialysis dose. This highlights the importance of multimodal intervention strategies besides adequate HD treatment as determined by Kt/V alone. The association with elevated LDH was not previously reported and may indicate the relevance of blood-membrane interactions, organ malperfusion or haematologic and metabolic changes during maintenance HD in this population.
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