Carlos Fernández Llatas, a researcher from the SABIEN group at the ITACA-UPV Institute, has participated in an international study aimed at identifying new patterns in chronic diseases. To achieve this, the team developed an innovative methodology that applies process mining in epidemiological studies to detect patterns in pathologies such as chronic kidney disease (CKD).
Published in the journal Scientific Reports of the Nature group, the study offers a novel approach to analyzing the evolution of diseases and their risk factors using real-world data, overcoming the limitations of traditional methods.
«Process mining is an incredibly useful tool for understanding epidemiological patterns. This technique allows us to delve deeper into the progression of diseases and obtain information that conventional methods are unable to capture», says Carlos Fernández Llatas, a researcher at the ITACA Institute of the Polytechnic University of Valencia (UPV) and co-author of the study.
This study is the first at the international level to successfully use process mining to provide evidence in the field of epidemiology, enabling the discovery of dynamic behavioral patterns that cannot be detected with other techniques.
Research details
The paper proposes an innovative model combining process mining techniques with epidemiological models to analyze large datasets. This model consists of eight phases, ranging from event log generation to the statistical validation of hypotheses.
The methodology was applied to a group of patients in Stockholm to compare the effects of two common treatments used to reduce gastric acid production: proton pump inhibitors (PPIs) and H2 blockers. In total, data from 110,577 patients were analyzed, including 100,803 who began treatment with PPIs and 9,774 with H2 blockers.
«The use of proton pump inhibitors (PPIs), compared with H2 blockers, is associated with an increased risk of impaired renal function and higher all-cause mortality», the study notes.
Additionally, the relationship between certain comorbidities—such as cardiovascular disease, diabetes, and COPD—and kidney disease progression was assessed, providing a more comprehensive picture of kidney disease progression.
Impact and future applications
The research underscores the importance of reconsidering the widespread use of PPIs, particularly among patients at risk of renal impairment.
Furthermore, the study’s methodology can be extended to research other diseases, opening up new opportunities for personalized medicine.
«This methodology not only enables a more precise assessment of the impact of certain treatments, such as PPIs, but also provides tools to design more effective clinical interventions tailored to the individual characteristics of patients«, adds Fernández Llatas.
In conclusion, this work represents a significant step forward in understanding the progression of diseases through real-world data and «reinforces the usefulness of process mining in epidemiological research», concludes the ITACA researcher.
