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Cardiology Consultation in Noncardiac Surgery

Impact of 2014 ACC/AHA Perioperative Guidelines on Cardiological Resource Use in Noncardiac Surgery Patients

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05532917
Enrollment
898
Registered
2022-09-08
Start date
2022-01-15
Completion date
2023-04-12
Last updated
2023-04-13

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Myocardial Infarction, Surgery-Complications

Keywords

ACC/AHA guidelines, Perioperative cardiac risk, Cardiology consultation

Brief summary

Recently, a predictive model has been developed to assess the risk of myocardial infarction or cardiac arrest (MICA) during and after surgery using the American Society of Surgeons' National Surgical Quality Improvement Program (NSQIP) database. In this MICA model, 180 hospital databases were used in 2007 and 2008 and included more than 200 000 patients. The Gupta score developed with this MICA model identified five predictors of perioperative myocardial infarction and cardiac arrest: type of surgery, functional status, creatinine increase (\>130 mmol/L or \>1.5 mg/dL), age, and American Association of Anesthesiologists (ASA) class. The Gupta score is presented as an interactive risk calculation program in the 2014 guideline of the ACC/AHA. The risk can be calculated simply and accurately at the bedside or clinic. The Gupta score is in spreadsheet format and can be downloaded online at http://www.surgicalriskcalculator.com/miorcardiacarrest. Unlike the previously used indexes, a scoring system has not been established. An estimate of the probability of myocardial infarction/cardiac arrest is provided for individual patients. In this study, the primary aim was to compare the frequency of cardiology consultation requests according to the use of the Gupta score. The secondary aim is to evaluate the perioperative clinical results (coronary angiography, ECHO, acute coronary syndrome, arrhythmia, 30-day mortality, etc.).SPSS 21.0 (Version 22.0, SPSS, Inc, Chicago, IL, USA) program will be used for statistical analysis. After applying the Shapiro-Wilk test for normality, the student's t-test will be used if the distribution is normal, and the Mann-Whitey U test will be used if the distribution is not normal. Fisher's exact test or chi-square test will be used for categorical variables. Results p\<0.05 will be considered significant.

Detailed description

All patients undergoing non-cardiac surgery are at risk of major perioperative cardiovascular events. Cardiac complications account for 42% of the overall complications of these surgeries. Therefore, cardiologists are the most frequently consulted specialists in preoperative evaluation. Unnecessary cardiology consultations may cause comments that will not affect the practice of anesthesia, inappropriate tests and interventions, and delay in the surgical procedure. Recently, a predictive model has been developed to assess the risk of myocardial infarction or cardiac arrest (MICA) during and after surgery using the American Society of Surgeons' National Surgical Quality Improvement Program (NSQIP) database. In this MICA model, 180 hospital databases were used in 2007 and 2008 and included more than 200 000 patients. The Gupta score developed with this MICA model identified five predictors of perioperative myocardial infarction and cardiac arrest: type of surgery, functional status, creatinine increase (\>130 mmol/L or \>1.5 mg/dL), age, and American Association of Anesthesiologists (ASA) class. The Gupta score is presented as an interactive risk calculation program in the 2014 guideline of the ACC/AHA. The risk can be calculated simply and accurately at the bedside or clinic. The Gupta score is in spreadsheet format and can be downloaded online at http://www.surgicalriskcalculator.com/miorcardiacarrest. Unlike the previously used indexes, a scoring system has not been established. An estimate of the probability of myocardial infarction/cardiac arrest is provided for individual patients.

Interventions

OTHERGupta score

The Gupta score is presented as an interactive risk calculation program in the 2014 guideline of the ACC/AHA. The Gupta score developed with this MICA model identified five predictors of perioperative myocardial infarction and cardiac arrest: type of surgery, functional status, creatinine increase (\>130 mmol/L or \>1.5 mg/dL), age, and American Association of Anesthesiologists (ASA) class. The frequency of cardiology consultation requests will be investigated according to the use of the Gupta score.

Sponsors

Diskapi Yildirim Beyazit Education and Research Hospital
Lead SponsorOTHER_GOV

Study design

Observational model
OTHER
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 99 Years
Healthy volunteers
No

Inclusion criteria

* Patients undergoing non-cardiovascular surgery * Patients evaluated routinely preoperatively in the anesthesiologist preoperative outpatient clinic

Exclusion criteria

* Emergency surgeries * ASA Physical Status V * Patients undergoing cardiovascular surgery * Minor surgeries * Patients who did not want to participate in the study

Design outcomes

Primary

MeasureTime frameDescription
Gupta scoreperioperative periodThe frequency of cardiology consultation requests will be compared according to the use of the Gupta score.

Secondary

MeasureTime frameDescription
Perioperative clinical resultsperioperative periodPerioperative clinical results (coronary angiography, ECHO, acute coronary syndrome, arrhythmia, 30-day mortality, etc.) will be evaluated.

Countries

Turkey (Türkiye)

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026