Could Algometric Assessment be Effective to Adjust Postoperative Analgesic Requirement?
NCT ID: NCT02375607
Last Updated: 2015-03-02
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
UNKNOWN
NA
80 participants
INTERVENTIONAL
2012-02-29
2015-05-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
The Prediction for Postoperative Pain
NCT03585088
Evaluation of Postoperative Pain in Cases Undergoing Cataract Surgery Under Topical Versus General Anesthesia
NCT07287683
Effects of Different Anesthetic Techniques on Intraoperative and Postoperative Pain Levels and Cognitive Function in Patients Undergoing Hepatectomy for Liver Cancer
NCT07097220
Multimodal and Unimodal Analgesia in Cholecystectomy
NCT05547659
Prediction of Postoperative Pain by Nociception Monitoring
NCT05063227
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
NA
SINGLE_GROUP
SCREENING
NONE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Algometer
Algometer used patients
Algometer
Algometer performed patients
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
Algometer
Algometer performed patients
Other Intervention Names
Discover alternative or legacy names that may be used to describe the listed interventions across different sources.
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
Exclusion Criteria
* Diabetes mellitus type 1 or 2
* Continuous use of analgesics
* Patients whose do not accept to participate in the study
* Patients those reoperated for bleeding
18 Years
65 Years
ALL
Yes
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Tokat Gaziosmanpasa University
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Ziya Kaya
Associate Professor, MD
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
ZIYA KAYA, Assoc.Prof.
Role: PRINCIPAL_INVESTIGATOR
Gaziosmanpasa University, Medical Faculty, Department of Anesthesiology and Reanimation
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Gaziosmanpasa University
Tokat Province, , Turkey (Türkiye)
Countries
Review the countries where the study has at least one active or historical site.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
References
Explore related publications, articles, or registry entries linked to this study.
Hsu YW, Somma J, Hung YC, Tsai PS, Yang CH, Chen CC. Predicting postoperative pain by preoperative pressure pain assessment. Anesthesiology. 2005 Sep;103(3):613-8. doi: 10.1097/00000542-200509000-00026.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
26/07/2011-195
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.