PrEventing PostoPERative Pulmonary Complications by Establishing a MachINe-learning assisTed Approach

Recruiting now

Conditions studied: Postoperative Pulmonary Complications

In brief

Postoperative pulmonary complications (POPC) are common after general anaesthesia and are a major cause of increased morbidity and mortality in surgical patients. However, prevention and treatment methods for POPC that are considered effective, tie up human and technical resources. The aim of the planned research project is therefore to enable reliable identification of high-risk patients on the basis of a tailored machine learning algorithm using perioperative clinical routine data and sonographic imaging data collected in the recovery room. The randomized clinical trial will include 512 patients undergoing elective surgery in general anaesthesia. The primary outcome will be the development of POPC. The goal of the study is to detect postoperative pulmonary complications before they become clinically manifest.

Key facts

Study ID

NCT05789953

Run by

Britta Trautwein

People needed

512

Starts

2023-04-25

Expected to finish

2026-12-01

Last updated by the study team

2026-05-08

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• adult patients
• elective, surgical procedure
• general anaesthesia

You may not qualify if…

• patients younger than 18 years of age
• outpatient surgery
• postoperative admission to intensive care unit

Where it is running

• University Hospital Ulm — Ulm, Germany (enrolling)

Full record on ClinicalTrials.gov

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