Validation of the CONUT Software Tool for Screening Clinical Malnutrition in the University Hospital La Paz

Nutrition Department of University Hospital La Paz decided to implement some method of screening in our centre which allowed us to detect as many patients with malnutrition risk as possible. Due to the large size of our centre, with about 1,500 beds and the few human resources in our unit, we chose to use the CONUT system (Nutritional Control), a 100% automatic method based on analytical parameters, very easy to use, low cost and whose validity is confirmed, characteristics that fulfilled our needs. The implementation of this nutritional screening method has led to a change in the ìnutritionafi culture of our centre respect to DRM in most of our professionals: doctors and nurses and even in the management team, so all of them understand the importance of the process and know about the available tools and knowledge to indicate an adequate and early nutritional support.

Completed

Looking for future studies?

Notify Me

Key information

Conditions

Malnutrition Nutrition Disorders Nutritional and Metabolic Diseases

Age range

15 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Institute for Health Research IdiPAZ

Madrid, Spain

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Patients of both sexes
Patients older than 15 years
Patients admitted to the General Hospital or Traumatology area
Patients who have signed the informed consent to participate in the study
Patients who do not meet any exclusion criteria.

Exclusion criteria

Pregnant women.
Patients whose physical and / or psychic capacity prevents them from providing all the data collected by the evaluated methods or who do not have a caregiver.
Non-collaborating patients in data collection
Patients in whom a hospital stay of less than 48 hours is expected.
Patients who at the time of performing the analyzes are in the ICU and OER

Treatment and study plan

CONUT screening system

Other

CONUT has been working from june of 2010 and it has detected risk of malnutrition in 32% of the evaluated patients. The method collects information from databases of Admission Service (affiliation, age, date) and Laboratory (albumin, cholesterol, total lymphocytes) and generates, in the report of analytical results, "alert" information about each patient's nutritional risk and also nutritional recommendations based on the risk identified.

Primary outcomes

To detect as many patients with malnutrition risk as possible

Time frame: Three months

The method collects information from databases of Admission Service (affiliation, age, date) and Laboratory (albumin, cholesterol, total lymphocytes) and generates, in the report of analytical results, "alert" information about each patient's nutritional risk and also nutritional recommendations based on the risk identified. Prior to its implantation several evaluations were performed in order to allow us to better know the extra workload, as it was the main factor that could limit our ability to assume that screening method and also many training activities for doctors and hospital health professionals who were increasingly assuming responsibilities in the nutritional treatment of their patients.

Sponsors and collaborators

Lead sponsor

Instituto de Investigación Hospital Universitario La Paz

Other

Registry information

Important dates

Study start: 2012
Primary completion: 2012
Study completion: 2012
First posted: Sep 13, 2019
Registry last updated: Sep 13, 2019

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed