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NCT07164664COMPLETEDanonymous

External Oblique Intercostal Block Versus Port-Site Infiltration for Postoperative Analgesia in Laparoscopic Cholecystectomy

Sponsor

Source record

Ondokuz Mayıs University

Phase

Source record

NA

Modality

AI-normalized

RNA therapy

Target

AI-normalized

External Oblique Intercostal Block, Port-Site Infiltration, ıv morphine PCA

Indication / condition

AI-normalized

Pain, Postoperative

Intervention

Source record

External Oblique Intercostal Block, Port-Site Infiltration, ıv morphine PCA

Source & freshness

Source record

NCT ID

NCT07164664

Original source

ClinicalTrials.gov

Source last updated

Apr 09, 2026

Ingested at

Jun 09, 2026

Internal sync

Jun 09, 2026

Model version

trialsignal-ai-v1

Normalized confidence

96%

Validation status

validated

Open original registry record
View original source fields

NCT ID

NCT07164664

Title

External Oblique Intercostal Block Versus Port-Site Infiltration for Postoperative Analgesia in Laparoscopic Cholecystectomy

Sponsor

Ondokuz Mayıs University

Status

COMPLETED

Phase

NA

Condition raw

Pain, Postoperative, Pain, Acute, Opioid Use

Condition normalized

Pain, Postoperative, Pain, Acute, Opioid Use

Modality raw

RNA therapy

Modality normalized

RNA therapy

Target raw

External Oblique Intercostal Block, Port-Site Infiltration, ıv morphine PCA

Target normalized

External Oblique Intercostal Block, Port-Site Infiltration, ıv morphine PCA

Interventions

External Oblique Intercostal Block, Port-Site Infiltration, ıv morphine PCA

Public preview

Source record

Adequate postoperative pain management is essential for improving patient comfort and recovery after laparoscopic cholecystectomy. This study evaluated the effectiveness of the external oblique intercostal block compared with port-site infiltration in terms of pain scores and opioid consumption during the first 24 hours after surgery.

AI-generated analysis supports research triage only. Verify source records, publications, sponsor disclosures and IP databases before making diligence decisions. Model: trialsignal-ai-v1.

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