ClinicalTrials.gov
public full text
Public Domain
Ultrasound Detection of Position of Diaphragm During Laparoscopic Surgery
Position of diaphragm in the region of electrical impedance tomography measurement is to be determined by ultrasound in approx. 20 patients undergoing laparoscopic surgery. Data are to be obtained at three phases at supine horizontal position (during spontaneous breathing, at mechanically ventilated patient under general anesthesia with muscle relaxation and at mechanically ventilated patient under general anesthesia with muscle relaxation during insufflation of carbon dioxide into the peritoneal cavity to achieve exposure during laparoscopic surgery).
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Effect of Optimized PEEP on Mechanical Ventilation During Robot Assisted Laparoscopic Prostatectomy#845099
- Recruitment Maneuvers and PEEP-guided Electrical Impedance Tomography for Abdominal Laparoscopic Surgery Patients#801832
- Electromyography in abdominal laparoscopic and robot-assisted laparoscopic surgery: A scoping review.#427631
- Place of Ultrasound Guidance of Surgery Site in Surgery for Lumbar Canal Stenosis and Lumbar Disc Herniations#886445
- Abdominal Diastasis Repair by Robotic Surgery#833957
Record · ID 1124834
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive