Heart Block, Risk Factor
Conditions
Keywords
Postoperative new-onset heart blocks, Noncardiac surgery, Machine learning, Prediction model, Prognosis
Brief summary
This study aimed to investigate new-onset heart blocks after noncardiac surgery, identify risk factors, and develop a prediction model.
Detailed description
Objective: This study aimed to investigate new-onset heart blocks after noncardiac surgery, identify risk factors, and develop a prediction model. Methods: A retrospective cohort study included 281,497 patients aged 18 or older who underwent noncardiac surgery at a single center between Jan 2008 and Aug 2019. The main outcome was postoperative new-onset heart blocks within one year, including atrioventricular and bundle blocks. Prognostic impact was assessed using Kaplan-Meier survival curves and time-dependent Cox regression analysis. Perioperative data was used for machine learning models (logistic regression, support vector machine, random forest, decision tree). Model performance was measured using the area under the receiver operating characteristic curve (AUC).
Interventions
OTHERnon interventions
Sponsors
Chinese PLA General Hospital
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* patients above 18 yrs undergoing noncardiac surgery at the First Medical Center of the Chinese People's Liberation Army General Hospital (PLAGH) from January 1, 2008 to August 1, 2019.
Exclusion criteria
* surgical duration of less than 30 minutes * incomplete data
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| New-onset heart blocks | within one year after surgery | The number of new-onset heart blocks within one year after surgery, including first-, second-, and third-degree AV blocks and left- and right-branch bundle blocks |
Outcome results
None listed