Pain Clinical Trial - The Evaluation With Artificial Neural Network of

Status Recruiting

Clinical Trial Summary

The study evaluates with Artificial Neural Network (ANN) of pain scales in children. Pain of these patients' will be evaluated by many pain scales in the postoperative period.

Clinical Trial Description

Pain of these patients' will be evaluated by many pain scales in the postoperative period. These scales include OUCHER, Visiuel Analog Scale, FLACC, Faces Pain Scale revise, Wong Baker Faces Scale, Faces Pain Scale, Numeric rating Scale, Verbal Rating Scale, CHEOPS and also age, blood pressure, respiratuar rate, heart rate will be recorded.

In the first step of this study, the parameters taken into account on widely used each pain scale practically and importance level of each parameter will be examined. The parameters taken into account in determining the degree of pain and degree of each pain scale will be recorded. Independent t-test of the pain scales will be analyzed whether different statistically. Pain scales used in the application at conclusion statistical analysis will be grouped.

In addition, parameters considered to be effective on pain (pulse, blood pressure, etc.) will be determined and also recorded. The degree of importance on pain of the current scales and other parameters to be determined and as result, new pain scale will be created. While determining the the level of importance will be utilized from the analytic hierarchy process (AHP). Making binary comparisons between AHP and parameters, the level of importance and weightiness score of each parameter will be determined. The mathematical formulation of the pain points will be presented considering AHP weightiness score of each parameter.

Although pain scores obtained mathematically, pain score with Artificial Neural Network (ANN) will be estimated considering the parameters that impact on the pain score.

The final step, the creation of new pain scale comparing the pain scores obtained by mathematical formulation and Artificial Neural Network and, it is intended to be compared with the current scales. ;

Study Design

Observational Model: Case-Only, Time Perspective: Prospective

Related Conditions & MeSH terms

Pain

Clinical Trial Details

NCT number	NCT02682875
Study type	Observational [Patient Registry]
Source	Cukurova University
Contact	Dilek Özcengiz
Phone	05324673220
Email	dilekozcengiz@gmail.com
Status	Recruiting
Phase	N/A
Start date	November 2015
Completion date	May 2016

View Details

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Clinical trials are conducted in a series of steps, called phases - each phase is designed to answer a separate research question.

Phase 1: Researchers test a new drug or treatment in a small group of people for the first time to evaluate its safety, determine a safe dosage range, and identify side effects.
Phase 2: The drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.
Phase 3: The drug or treatment is given to large groups of people to confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug or treatment to be used safely.
Phase 4: Studies are done after the drug or treatment has been marketed to gather information on the drug's effect in various populations and any side effects associated with long-term use.

The Evaluation With Artificial Neural Network of Pain Scales in Children (ANN) — ANN

Clinical Trial Summary

Clinical Trial Description

Study Design

Related Conditions & MeSH terms