The goal of this observational study was to identify subphenotypes of acute kidney injury patients with COVID-19, and the investigators analyzed their impact on mortality. The study included demographic and clinical variables of the participants. The implementation of Machine Learning algorithms and Artificial Intelligence methods are used, and some specific implementations were designed for the analysis, where each group was characterized by traditional statistical methods.
Study Type
OBSERVATIONAL
Enrollment
2,934
clustering
Instituto Nacional de Enfermedades Respiratorias
Mexico City, Mexico
Subphenotypes of acute kidney injury in patients
Number of acute kidney injury subphenotypes in patients with COVID-19
Time frame: Through study completion, an average of one month
Mortality of acute kidney injury patients
Differences between mortality rates in acute kidney injury subphenotypes of patients with COVID-19
Time frame: Through study completion, an average of one month
Severity of acute kidney injury patients
Differences between severity stages in acute kidney injury subphenotypes of patients with COVID-19
Time frame: Through study completion, an average of one month
Non-recovery in acute kidney injury patients
Differences between non recovery rates in acute kidney injury subphenotypes of patients with COVID-19
Time frame: Through study completion, an average of one month
Renal replacement therapy requirement in acute kidney injury patients
Differences between renal replacement therapy requirement rates in acute kidney injury subphenotypes of patients with COVID-19
Time frame: Through study completion, an average of one month
Length of stay of acute kidney injury patients
Differences in-hospital length of stay in acute kidney injury subphenotypes of patients with COVID-19.
Time frame: Through study completion, an average of one month
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