NCT06431412

Brief Summary

Objective: This study aims to use machine learning methods to establish an optimal model for predicting serum vancomycin trough concentrations in critically ill patients. Methods: This is a single-center, retrospective study. Data on serum vancomycin concentration in the Critical Care Database of Peking Union Medical College Hospital were screened and extracted to construct a prediction model using machine learning methods. The MIMIC-IV (Medical Information Mart for Intensive Care) database will be further used for external verification of the constructed model. The study has been approved by the Medical Ethics Committee of Peking Union Medical College Hospital (K24C1161).

Trial Health

55
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
401

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Mar 2024

Shorter than P25 for all trials

Geographic Reach
1 country

1 active site

Status
active not recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

March 1, 2024

Completed
2 months until next milestone

First Submitted

Initial submission to the registry

May 8, 2024

Completed
20 days until next milestone

First Posted

Study publicly available on registry

May 28, 2024

Completed
3 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

August 31, 2024

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

August 31, 2024

Completed
Last Updated

May 28, 2024

Status Verified

May 1, 2024

Enrollment Period

6 months

First QC Date

May 8, 2024

Last Update Submit

May 27, 2024

Conditions

Critical IllnessInfectionsDrug Use

Keywords

Serum vancomycin concentrationMachine learning

Outcome Measures

Primary Outcomes (1)

  • The predicted serum vancomycin concentration

    The serum vancomycin concentration predicted by the constructed model

    1 day

Interventions

no interventionOTHER

no intervention

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Adult ICU patients who receivied intravenous vancomycin treatment

You may qualify if:

  • Age ≥18 years;
  • Patients admitted to ICUs;
  • Patients were administered intravenous vancomycin;
  • Vancomycin TDM was performed at least two times.

You may not qualify if:

  • Vancomycin TDM was performed in a ward rather than in an ICU;
  • Patients with missing data.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Peking Union Medical College Hospita

Beijing, Beijing Municipality, 100730, China

Location

Related Publications (6)

  • Ye ZK, Li C, Zhai SD. Guidelines for therapeutic drug monitoring of vancomycin: a systematic review. PLoS One. 2014 Jun 16;9(6):e99044. doi: 10.1371/journal.pone.0099044. eCollection 2014.

    PMID: 24932495RESULT

  • Ingram PR, Lye DC, Tambyah PA, Goh WP, Tam VH, Fisher DA. Risk factors for nephrotoxicity associated with continuous vancomycin infusion in outpatient parenteral antibiotic therapy. J Antimicrob Chemother. 2008 Jul;62(1):168-71. doi: 10.1093/jac/dkn080. Epub 2008 Mar 10.

    PMID: 18334494RESULT

  • Rybak MJ, Le J, Lodise TP, Levine DP, Bradley JS, Liu C, Mueller BA, Pai MP, Wong-Beringer A, Rotschafer JC, Rodvold KA, Maples HD, Lomaestro B. Therapeutic Monitoring of Vancomycin for Serious Methicillin-resistant Staphylococcus aureus Infections: A Revised Consensus Guideline and Review by the American Society of Health-system Pharmacists, the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the Society of Infectious Diseases Pharmacists. Clin Infect Dis. 2020 Sep 12;71(6):1361-1364. doi: 10.1093/cid/ciaa303.

    PMID: 32658968RESULT

  • Yasuhara M, Iga T, Zenda H, Okumura K, Oguma T, Yano Y, Hori R. Population pharmacokinetics of vancomycin in Japanese adult patients. Ther Drug Monit. 1998 Apr;20(2):139-48. doi: 10.1097/00007691-199804000-00003.

    PMID: 9558127RESULT

  • Obermeyer Z, Emanuel EJ. Predicting the Future - Big Data, Machine Learning, and Clinical Medicine. N Engl J Med. 2016 Sep 29;375(13):1216-9. doi: 10.1056/NEJMp1606181. No abstract available.

    PMID: 27682033RESULT

  • Doupe P, Faghmous J, Basu S. Machine Learning for Health Services Researchers. Value Health. 2019 Jul;22(7):808-815. doi: 10.1016/j.jval.2019.02.012.

    PMID: 31277828RESULT

MeSH Terms

Conditions

Critical IllnessInfections

Condition Hierarchy (Ancestors)

Disease AttributesPathologic ProcessesPathological Conditions, Signs and Symptoms

Study Officials

  • Li Weng, MD

    Peking Union Medical College Hospital

    STUDY CHAIR

Study Design

Study Type
observational
Observational Model
CASE ONLY
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

May 8, 2024

First Posted

May 28, 2024

Study Start

March 1, 2024

Primary Completion

August 31, 2024

Study Completion

August 31, 2024

Last Updated

May 28, 2024

Record last verified: 2024-05

Data Sharing

IPD Sharing
Will not share

Locations

CN(1)