Establishing Malnutrition Diagnosis System by Using Artificial-intelligence Technology

Establishing Malnutrition Diagnosis System by Using Artificial-intelligence Technology to Improve the Application of Clinical Pathway

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT04776070

Enrollment

500

Registered

2021-03-01

Start date

2021-08-13

Completion date

2022-05-21

Last updated

2023-03-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Disease-related Malnutrition

Brief summary

The prevalence of malnutrition is estimated at 30-50% of hospitalized patients in China. Disease-related malnutrition increases the risk of infection, mortality, length of hospitalization as well as the economic burden. National Nutrition Plan proposed to reduce malnutrition, but a clear, effective roadmap and protocol has not existed yet. Several factors impede to resolve the above challenges. They include :1) the low efficiency of current malnutrition diagnosis methods; 2) the lack of dynamic, standard method that can evaluate nutritional status in quantitative way. To this end, the investigators aim to establish an artificial-intelligence malnutrition diagnosis system to improve the application of malnutrition Clinical Pathway. Firstly, the investigators will establish a multidimensional malnutrition large data set, based on our previously built national hospital nutrition screening data set. It will contain deep 3D facial images, semi-structured and structured electronic medical record. Then, the investigators will use ensemble learning algorithm to establish a fully automatic, artificial-intelligence malnutrition diagnosis model that includes both etiological and phenotypic diagnosis.

Interventions

None listed

Study design

Observational model

CASE_ONLY

Time perspective

CROSS_SECTIONAL

Eligibility

Sex/Gender

ALL

Age

18 Years to 100 Years

Healthy volunteers

Inclusion criteria

* Adults (≥18 years old); * Within 48 hours of admission; * Inpatients at high risk of malnutrition, such as malignant tumors, chronic obstructive pulmonary disease, etc; * Han nationality; * Able to given informed consent.

Exclusion criteria

* Patients with artificial facial changes (such as plastic surgery , head and neck radiotherapy , head and neck trauma); * Diseases with special facial changes (such as acromegaly); * High dose glucocorticoid users; * Patients with facial edema; * Emergency admission with an expected length of stay of less than 3 days; * Other conditions researchers thought could not be included

Design outcomes

Primary

Measure	Time frame	Description
malnutrition diagnosis	Within 48 hours of admission	Using Global Leadership Initiative on Malnutrition(GLIM) to diagnose malnutrition among hospitalized patients

Countries

China

Outcome results