The Effect Of Perioperative Results On Mortality In Coronary Artery Bypass Surgery

February 23, 2026 updated by: Kerem Erkalp, MD, Prof, Istanbul University - Cerrahpasa

The Effect Of Perioperative Results On Mortality In Coronary Artery Bypass Surgery: Risk Assessment With Fuzzy Logic

Coronary artery bypass grafting (CABG) is one of the most common heart surgeries. Most patients are elderly with comorbidities that affect morbidity and mortality rates. Even in developed countries mortality rate is 1.9-5.3%. Determination of perioperative risk factors and creating protocols to take precautions accordingly may reduce mortality in patients.

In CABG patients, due to the surgical burden combined with existing comorbidities, it is important for physicians to evaluate the risk status and predict the mortality rates. For this purpose, various scoring systems have been developed.

Fuzzy logic method allows partially membership, so that a glass that is neither full nor empty can be numerically expressed as being partially full but also partially empty. This feature is similar to the reasoning structure of the human brain that uses linguistic tools. In this way, in cases where there is no precise mathematical model and where the existence of imprecise and uncertain information is natural, such as medical applications, in order to solve the problem, fuzzy easily allows linguistic expressions containing the knowledge, experience and intuition of expert to transforme into the model created for the solution. In decision making process, fuzzy logic provides ability to use linguistic expressions, including experts' intuition. Thus, decisions can be made even with approximate data and uncertainty. For this reason, fuzzy logic is used in a wide range of research from engineering to medicine.

The records of patients who underwent CABG surgery in Istanbul University-Cerrahpaşa Cardiology Institute between January 1, 2020 and July 31, 2024 will be examined.

Preoperative major risk factors diabetes, pulmonary, neurological, kidney and liver disease with preoperative minor risk factors age, weight and smoking will be recorded. Perioperative risk factors; duration of artificial circulation, number of vessels bypassed, and number of blood products used will be recorded. Our primary aim is to create a fuzzy logic-based perioperative risk classification model to identify high-risk patients in CABG surgery. Secondly we aimed to investigate the effect of perioperative risk factors on postoperative complications

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

Coronary artery bypass grafting (CABG) is one of the most common heart surgeries. Most patients are elderly with comorbidities such as diabetes mellitus and renal diseases. Tehese risk factors affect morbidity and mortality rates. Even in developed countries mortality rate in CABG patients is between 1.9-5.3%. Identifying perioperative risk factors and taking precautions by creating protocols can decrease mortality in patients. Experienced surgical and anesthesia teams, evidence-based practices, and advances in pharmacology and technology can increase survival.

Risk assessment is important in determining the treatment plans of patients who will be operated on, providing patient education for the postoperative period, providing insight into prognosis, and determining health care quality standards.

In CABG patients, due to the surgical burden combined with existing comorbidities, it is important for physicians to evaluate the risk status and predict the mortality rates. For this purpose low and high risk studies have been conducted and various scoring systems have been developed. European System for Cardiac Operative Risk Evaluation-II (EUROSCORE-II) is a scoring system that was created specifically for cardiac surgery patients and is widely used all over the world, predicting mortality through preoperative evaluation. EUROSCORE-II scoring may be low in older patients (over 70 years of age). A scoring system with higher predictive power is aimed by making modifications to EUROSCORE-II or comparisons with other scoring systems.

In 1965, Zadeh first introduced Fuzzy, which is the basis of the fuzzy logic procedure Fuzzy logic method allows partially membership, so that a glass that is neither full nor empty can be numerically expressed as being partially full but also partially empty. This feature is similar to the reasoning structure of the human brain that uses linguistic tools. In this way, in cases where there is no precise mathematical model and where the existence of imprecise and uncertain information is natural, such as medical applications, in order to solve the problem, fuzzy easily allows linguistic expressions containing the knowledge, experience and intuition of expert to transforme into the model created for the solution. In decision making process, fuzzy logic provides ability to use linguistic expressions, including experts' intuition. Thus, decisions can be made even with approximate data and uncertainty. For this reason, fuzzy logic is used in a wide range of research from engineering to medicine.

The records of patients who underwent isolated CABG surgery in Istanbul University-Cerrahpaşa Cardiology Institute between January 1, 2020 and July 31, 2024 will be included.

Diabetes mellitus, pulmonary, neurological, kidney and liver disease will be recorded as preoperative major risk factors. Age, weight and smoking will be recorded as preoperative minor risk factors. Duration of artificial circulation, number of vessels bypassed, and number of blood products used will be recorded as perioperative risk factors.

The effect of preoperative risk factors on mortality has been investigated in many studies. Our primary aim is to create a fuzzy logic-based perioperative risk classification model to identify high-risk patients in isolated CABG surgery.

Study Type

Observational

Enrollment (Actual)

485

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

Over 18 year of age, all isolated coronary artery bypass surgery between January 1, 2020 and July 31, 2024 at IUC Cardiology Institute hospital

Description

Inclusion Criteria:

  • All isolated coronary artery bypass surgery between January 1, 2020 and July 31, 2024 at IUC Cardiology Institute hospital

Exclusion Criteria:

  • All surgical procedures other than isolated coronary artery bypass surgery and patients under the age of 18 were excluded

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
coronary artery bypass surgery group
All patients over the age of 18 who underwent isolated coronary artery bypass surgery at the IUC Cardiology Institute hospital between January 1, 2020 and July 31, 2024 will be included in the study.
Other: There is no intervention in this study.
This study is planned as a retrospective cross sectional study. Only the information of the patients will be used.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Risk assessment with fuzzy logic
Time Frame: 4 months
Create a fuzzy logic-based perioperative risk classification model to identify high-risk patients in CABG operations.
4 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Perioperative risk factors
Time Frame: 4 months
Investigate the effects of artificial circulation time, number of bypassed vessels, and how many bags of blood products were used as perioperative risk factors on postoperative complications.
4 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Istanbul University - Cerrahpasa

Investigators

  • Study Chair: Kerem Erkalp, Istanbul University - Cerrahpasa

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 15, 2024

Primary Completion (Actual)

December 15, 2025

Study Completion (Actual)

December 15, 2025

Study Registration Dates

First Submitted

February 2, 2025

First Submitted That Met QC Criteria

February 2, 2025

First Posted (Actual)

February 6, 2025

Study Record Updates

Last Update Posted (Actual)

February 24, 2026

Last Update Submitted That Met QC Criteria

February 23, 2026

Last Verified

January 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 112

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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