Skip to main content
OpenTrials
Completed

NCT Number: NCT04688216

Developing a Risk Assessment System of Multidrug-resistant Organisms Infection

1. A retrospective analysis was performed to determine the prevalence of multidrug- resistant organisms infection in ICU from October 2017 to October 2019. 2. Non-MDRO patients were selected by random sampling in a ratio of 1:1 to the final MDRO group during the same period , and select the risk factors of infection with multi-drug resistant bacteria by comparing the two groups. 3. Randomly select 30% of the sample size as the validation set, and the remaining 70% for the training set to establish a model. Using multi-factor Logistic regression, decision tree classification, artificial neural network, support vector machine, Bayesian network Method to establish risk assessment system for multidrug-resistant organisms infection respectively.Using validation set data to calculate the area under the ROC curve (AUC) and sensitivity, specificity of models and comparing the prediction accuracy of several models. Finally, choose a more suitable risk assessment system for multidrug-resistant organisms infection. 4. Predict the patient's infection risk level according to the best risk assessment system and develop a low-to-high intervention plan.

Completed

Looking for future studies?

Notify Me

Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

2nd Affiliated Hospital, School of Medicine, Zhejiang University

Hangzhou, Zhejiang, 310009, China

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Duration of ICU admission ≥ 48h
  • no less than 18 years old

Exclusion criteria

  • Patients with MDRO infection at the time of admission
  • Lack of case data
  • MDRO colonized patients

Treatment and study plan

risk factors of infection with multidrug-resistant organisms

Other
  • General information: age, gender, length of stay in ICU, method of admission, tubes taken at the time of admission, APACHEⅡ score, surgery, laboratory tests (PCT, CRP, WBC), pressure sores, etc.
  • Iatrogenic factors: days of using ventilator, days of using antibacterial drugs, types of antibacterial drugs, use of glucocorticoids, use of immunosuppressants, days of central venous intubation, days of indwelling catheters, days of arterial catheterization, and other indwelling catheters.
  • The patient's own related factors: diagnosis, whether complicated with hypertension or diabetes; whether exist malignant tumor, primary lung infection, hypoproteinemia; whether antibiotic treatment before admission; fever and fever days, whether diarrhea occurs

Primary outcomes

  1. multidrug-resistant organisms infection

    Time frame: From date of ICU admissions until the date of ICU discharge or date of diagnosis of multidrug-resistant organisms infection , whichever came first, assessed up to 24 months

    Ratio of the number of multi-drug resistant bacterial infections to the total number of patients

Sponsors and collaborators

Lead sponsor

Second Affiliated Hospital, School of Medicine, Zhejiang University

Other

Registry information

Official study title

Developing the Best Risk Assessment System of Multidrug-resistant Organisms Infection in Critically Ill Patients Based on Big Data Analysis Technology

Important dates

Study start
2020
Primary completion
2022
Study completion
2022
First posted
Dec 29, 2020
Registry last updated
May 26, 2023

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.