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AI may predict dangerous blood pressure drops 30 minutes early

NCT ID NCT07627607

Knowledge-focused Sponsor: Kutahya Health Sciences University Source: ClinicalTrials.gov ↗

What the study statuses mean

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 27, 2026 · Last updated Jul 10, 2026 · Updated 2 times

Summary

This study will collect routine data from 100 adult ICU patients to build a machine learning model that predicts low blood pressure (hypotension) up to 30 minutes before it happens. The model uses non-invasive vital signs, heart rate, medication records, and fluid balance. No treatments or alarms are tested; the goal is to see if the model can accurately forecast hypotension.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this could lead to a tool that warns doctors about impending low blood pressure, potentially allowing earlier intervention.
What could go wrong
This is a small, early observational study with only 100 participants. The model may not work well in other hospitals or with different patients.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

107 people

The number who actually took part.

Started

Mar 2026

Finished

Jun 2026

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

The study population will consist of consecutive adult patients monitored in the adult intensive care unit of Kutahya Health Sciences University during the study period. Routine clinical monitoring data, including non-invasive blood pressure, heart rate, medication-dose records, and fluid-balance data, will be used for machine learning model development and internal validation. No treatment or intervention will be assigned by the study protocol.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Age 18 years or older * Admission to the adult intensive care unit during the study period * Length of stay in the intensive care unit of at least 24 hours * Availability of routine intensive care unit monitoring data * Availability of non-invasive blood pressure and heart rate measurements recorded during ICU monitoring * Availability of medication-dose and/or fluid-balance records during ICU monitoring Exclusion Criteria: * Age younger than 18 years * Length of stay in the intensive care unit of less than 24 hours * Absence of usable blood pressure monitoring data * Records with irrecoverable timestamp inconsistencies * Insufficient monitoring duration for feature construction and future outcome labeling

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Conditions

The condition(s) this trial relates to.

hypotensive disorder

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Hypotension

Contacts and locations

Locations

  • Kutahya City Hospital

    Kütahya, Kütahya, 43100, Turkey (Türkiye)

More trials for these conditions

Other studies related to the condition(s) this trial covers.