Appropriate Use of Blood Cultures in the Emergency Department Through Machine Learning

NCT06163781 | Recruiting DMC

• 1 other identifier: NL81971.000.22
• Study Type: interventional
• Target: 7,584
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this clinical trial is to study whether the use of our blood culture prediction tool is non-inferior to current practice and if it can improve certain outcomes in all adult patients presenting to the emergency department with a clinical indication for a blood culture analysis (according to the treating physician). The primary endpoint is 30-day mortality. Key secondary outcomes are:

• hospital admission rates
• in-hospital mortality
• hospital length-of-stay. In the intervention group, the physician will follow the advice of our blood culture prediction tool. In the comparison group all patients will undergo a blood culture analysis.

Conditions

Artificial Intelligence; Machine Learning; Microbiology; Emergency Service, Hospital; Randomized Controlled Trial

Outcome Measures

Primary Outcomes (1)

• 30-day mortality

  30 days

Secondary Outcomes (3)

• hospital admission rates

  1 day

• in-hospital mortality

  90 days

• hospital length-of-stay

  90 days

Other Outcomes (14)

• 30-day readmission rates

  30 days

• Length of stay in the ED in hours

  2 days

• Percentage of blood cultures avoided in the intervention group

  90 days

Study Arms (2)

Blood culture taken based on machine learning tool

EXPERIMENTAL

Device: Blood culture prediction tool

Blood culture taken based on the treating physician

NO INTERVENTION

Interventions

Blood culture prediction tool DEVICE

Machine learning based predicition tool

Blood culture taken based on machine learning tool

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age \>= 18 years
• Have a clinical indication for a blood culture analysis (according to the treating physician)
• Have sufficient data recorded (laboratory results and vital sign measurements) for a prediction to be made (at least 20% of the needed parameters)

You may not qualify if:

• Central Venous Line (CVL) or Peripherally Inserted Central Catheter (PICC) in situ
• Neutrophil count \< 0.5 \* 109/L
• Candidemia or S. aureus bacteraemia in the past 3 months.
• Most likely diagnosis of endocarditis/spondylodiscitis/infected prosthetic material
• Pregnant or breastfeeding patients
• Not capable of giving informed consent

Sponsors & Collaborators

• Amsterdam UMC, location VUmc: lead

Study Sites (1)

Amsterdam UMC - location AMC

Amsterdam, Netherlands

RECRUITING

Related Publications (3)

• Boerman AW, Schinkel M, Meijerink L, van den Ende ES, Pladet LC, Scholtemeijer MG, Zeeuw J, van der Zaag AY, Minderhoud TC, Elbers PWG, Wiersinga WJ, de Jonge R, Kramer MH, Nanayakkara PWB. Using machine learning to predict blood culture outcomes in the emergency department: a single-centre, retrospective, observational study. BMJ Open. 2022 Jan 4;12(1):e053332. doi: 10.1136/bmjopen-2021-053332.

  PMID: 34983764 RESULT

• Schinkel M, Boerman AW, Bennis FC, Minderhoud TC, Lie M, Peters-Sengers H, Holleman F, Schade RP, de Jonge R, Wiersinga WJ, Nanayakkara PWB. Diagnostic stewardship for blood cultures in the emergency department: A multicenter validation and prospective evaluation of a machine learning prediction tool. EBioMedicine. 2022 Aug;82:104176. doi: 10.1016/j.ebiom.2022.104176. Epub 2022 Jul 16.

  PMID: 35853298 RESULT

• van der Zaag AY, Bhagirath SC, Boerman AW, Schinkel M, Paranjape K, Azijli K, Ridderikhof ML, Lie M, Lissenberg-Witte B, Schade R, Wiersinga J, de Jonge R, Nanayakkara PWB. Appropriate use of blood cultures in the emergency department through machine learning (ABC): study protocol for a randomised controlled non-inferiority trial. BMJ Open. 2024 May 31;14(5):e084053. doi: 10.1136/bmjopen-2024-084053.

  PMID: 38821574 DERIVED

MeSH Terms

Conditions

Emergencies

Condition Hierarchy (Ancestors)

Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Prabath WB Nanayakkara, MD, PhD

CONTACT

+31204444444; p.nanayakkara@amsterdamumc.nl

Sheena C Bhagirath, MD

CONTACT

+31204444444; s.bhagirath@amsterdamumc.nl

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: MD, PhD

Study Record Dates

• First Submitted: October 12, 2023
• First Posted: December 11, 2023
• Study Start: February 19, 2024
• Primary Completion (Estimated): January 1, 2027
• Study Completion (Estimated): July 1, 2027
• Last Updated: May 7, 2024

Record last verified: 2024-05

Data Sharing

• IPD Sharing: Will share

Locations

NL (1)