CClinicalTrials.gg
CompletedNCT06582407Updated Oct 18, 2024

Machine Learning Models for Predicting Unforeseen Hospital Admissions or Discharges After Anesthesia

An observational study in Anesthesia Complication, Surgery-Complications and Pain, Postoperative, sponsored by HUmani. Completed at 1 site in Belgium. Per ClinicalTrials.gov, last updated 2024-10-18.

Sponsored by HUmani · Observational

Study type
Observational
Model
Cohort
Time perspective
Retrospective
Enrollment
68,683
Sex
All
01

Study summary

Unexpected hospital admissions after ambulatory surgery not only bring discomfort to patients but also causes a decrease in the efficiency of the healthcare system. In addition, unanticipated patient's orientation carry the risk of unsuitable post operative orders. The hypothesis of this project is that artificial intelligence models will outperform traditional models in predicting which patients will require hospital admission after ambulatory surgery or unforeseen hospital discharge after surgery.

02

Conditions studied

  • Anesthesia Complication
  • Surgery-Complications
  • Pain, Postoperative

Browse trials for

Keywords

  • anesthesiology
  • ambulatory surgery
  • artificial intelligence
  • machine learning
  • post operative complication
03

In context

Pain, Postoperative

5,093 studies on the registry are indexed under Pain, Postoperative; 1,140 are open to participants now.

This study's enrollment of 68,683 is above the median of 102 across 608 observational studies indexed under Pain, Postoperative.

Browse Pain, Postoperative studies →

Lead sponsor

This is the only study on the registry with HUmani as lead sponsor.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
Child (0–17), Adult (18–64), Older adult (65+)
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

All hospitalized or outpatient patients who have undergone anesthesia for a diagnostic or therapeutic procedure, in a scheduled or emergency condition, in the institution's hospitals.

Inclusion criteria

  • Patient undergoing anesthesia for a therapeutic or diagnostic procedure

Exclusion criteria

Exclusion Criteria:

  • Incomplete informatic data
  • Error in the encoding system
05

Study design

Observational model
Cohort
Time perspective
Retrospective
Enrollment
68,683 participants (actual)
Patient registry
No

Groups and cohorts

  • Ambulatory Patients

    Patient undergoing anesthesia in an ambulatory setting.

    Other: Mathematical Prediction of unforseen patient reorientation

  • Hospitalised Patients

    Patient undergoing anesthesia in a hospitalisation setting.

    Other: Mathematical Prediction of unforseen patient reorientation

Interventions

  • OtherMathematical Prediction of unforseen patient reorientation

    The goal of this project is to develop models to predict in the preoperative period which patients will require hospital admission after ambulatory surgery or unforeseen hospital discharge after surgery

06

What researchers measure

Primary outcomes

  1. Rate of patient reorientation

    Rate of unforeseen hospital admission after an ambulatory surgery and rate of discharge after an hospitalised surgery

    Time frame: On the day of the operation

07

Study locations

1 site
  • Université de Mons
    Mons, 7000, Belgium
08

References and documents

Individual participant data

Plan to share: No — The investigators are not authorized to publish sensitive data by decision of the ethics committee

No publications or documents are linked to this record.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Oct 18, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT06582407
Lead sponsor
HUmani
Responsible party
Rémi Florquin (Doctor, University of Mons) — Principal investigator
First posted
Sep 3, 2024
Start date
Jan 1, 2020
Primary completion
Jun 30, 2024
Completion
Jul 30, 2024
Last update
Oct 18, 2024

Study contacts

Rémi Florquin, MD
principal investigator · Université de Mons, Belgium

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is completed, as verified in Oct 2024. You cannot join it, but the record below documents what was studied.

Follow this study

Get an email when the registry record changes — status, dates, results — or when someone posts here.

Sign in to follow

Discussion

Questions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.

Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.

Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.

Start the discussion