Applying Artificial Intelligence to Identify Subphenotypes of Acute Kidney Injury in Mexican Patients With Severe COVID-19

NCT06471101 | Completed DMC

• 1 other identifier: C38-23
• Study Type: observational
• Target: 2,934
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

COVID-19; Acute Kidney Injury

Keywords

machine learning; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Subphenotypes of acute kidney injury in patients

  Number of acute kidney injury subphenotypes in patients with COVID-19

  Through study completion, an average of one month

Secondary Outcomes (5)

• Mortality of acute kidney injury patients

  Through study completion, an average of one month

• Severity of acute kidney injury patients

  Through study completion, an average of one month

• Non-recovery in acute kidney injury patients

  Through study completion, an average of one month

• Renal replacement therapy requirement in acute kidney injury patients

  Through study completion, an average of one month

• Length of stay of acute kidney injury patients

  Through study completion, an average of one month

Interventions

clusters DIAGNOSTIC_TEST

clustering

Eligibility Criteria

• Age: 15 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with acute kidney injury and COVID-19

You may qualify if:

• Patients older than 15 years old, hospitalized, and with severe acute respiratory syndrome (SARS-CoV-2) positive confirmation.

You may not qualify if:

• Patients who did not have at least 1 creatinine measurement.

Sponsors & Collaborators

• Instituto Nacional de Enfermedades Respiratorias: lead

Study Sites (1)

Instituto Nacional de Enfermedades Respiratorias

Mexico City, 14080, Mexico

Location

MeSH Terms

Conditions

COVID-19; Acute Kidney Injury

Condition Hierarchy (Ancestors)

Pneumonia, Viral; Pneumonia; Respiratory Tract Infections; Infections; Virus Diseases; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Lung Diseases; Respiratory Tract Diseases; Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Ph D. in computer science

Study Record Dates

• First Submitted: June 18, 2024
• First Posted: June 24, 2024
• Study Start: June 18, 2024
• Primary Completion: June 18, 2024
• Study Completion: June 18, 2024
• Last Updated: June 24, 2024

Record last verified: 2024-06

Locations

ME (1)