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Unravelling impact of comorbidities on mortality risks in CKD patients during the COVID-19 pandemic: An explainable
Zeinab Abdollahi1, Lin Huo2, Donald Fraser3
1School of Engineering, Computing, and Mathematics, University of Plymouth, Plymouth PL4 8AA, United Kingdom.
Insights
Chronic kidney disease (CKD) patients face high COVID-19 risks. Managing comorbidities like diabetes, hypertension, and obesity, alongside respiratory infections, is key to reducing mortality in these vulnerable individuals.
Area of Science:
- Nephrology
- Infectious Diseases
- Public Health
- Artificial Intelligence in Healthcare
Background:
- Chronic kidney disease (CKD) patients are a high-risk population for severe complications during pandemics like COVID-19.
- Understanding comorbidity prevalence and mortality predictors is crucial for effective public health strategies.
Purpose of the Study:
- To evaluate comorbidity prevalence in CKD patients during the COVID-19 pandemic.
- To predict mortality risks and identify key health factors influencing outcomes in CKD patients.
- To inform targeted prevention strategies for CKD patients during health crises.
Main Methods:
- Analysis of a large cohort (186,396) of CKD patients in Mexico from January 2020 to May 2023.
- Utilized explainable artificial intelligence (XAI) with extreme gradient boosting (XGBoost) and Shapley Additive Explanations (SHAP) for mortality prediction and interpretation.
- Employed comprehensive metrics to evaluate model generalization performance.
Main Results:
- Prevalent comorbidities include hypertension (64.39%), diabetes (49.79%), and obesity (16.46%).
- Overall mortality was 19.33%, significantly higher in COVID-19 positive patients (33.9%) versus negative (10.1%).
- Diabetes, hypertension, obesity, and pneumonia were major mortality predictors, especially in COVID-19 positive CKD patients. Machine learning models achieved AUC=0.76 and F1-score=0.75.
Conclusions:
- Targeted management of comorbidities, particularly diabetes, hypertension, and obesity, is essential for improving outcomes in CKD patients during pandemics.
- Addressing respiratory infections like pneumonia is critical for reducing mortality in this population.
- XAI models provide valuable insights for risk stratification and prevention in CKD patients during health crises.
Objectives:
The chronic kidney disease (CKD) patients were at high risk for severe clinical complications during the COVID-19 pandemic. Our objectives were to evaluate comorbidity prevalence; predict mortality risks for CKD patients during the pandemic; assess how various health factors interact to influence mortality; and provide insights for targeted prevention strategies.
Method:
We analysed data from 186,396 CKD patients in Mexico during the entire pandemic (Jan 2020- May 2023). Explainable artificial intelligence (XAI) methods with extreme gradient boosting (XGBoost) models and Shapley Additive Explanations (SHAP) were developed to predict mortality for CKD patients with model interpretations. Different metrics were used to comprehensively evaluate model's generalisation performances.
Results:
The most prevalent comorbidities were hypertension (64.39 %), diabetes (49.79 %), and obesity (16.46 %). Male patients and older individuals showed higher risk for adverse outcomes. The overall mortality rate was 19.33 %, with significantly higher mortality in COVID-19 positive patients (33.9 %) compared to COVID-19 negative patients (10.1 %). Comorbidities with the most significant impact on the mortality included diabetes, hypertension, and obesity, which were more frequent in the COVID-19 positive group and associated with higher rates of intubation, and ICU admission. Pneumonia was identified as a major predictor of negative outcomes in CKD patients with COVID-19. CVD was more common in the COVID-19 negative group. Our machine learning models achieved performances of AUC= 0.76 and F1-score= 0.75 for predicting mortality during the pandemic.
Conclusion:
Targeted management of comorbid conditions, especially respiratory infections, is crucial in CKD patients during pandemics.
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