AI-Assisted Analysis of Hemodynamic Stability and Short-Term Cardiovascular Outcomes of Adenosine Versus Verapamil In Elderly And Comorbid Svt Populations

Abstract

Background: Supraventricular tachycardia (SVT) is a frequent heart rhythm disorder, especially in patients with various comorbidities and of an advanced age. Pharmacological cardioversion with adenosine or verapamil is often used, but there are limited comparative data as to the restorative condition of hemodynamics and brief cardiovascular consequences in high-risk groups. AI-assisted analytical approaches may provide additional insight into treatment-related hemodynamic responses and short-term cardiovascular outcomes in high-risk SVT populations.

Objective: The study aimed to compare the hemodynamic stability and short-term cardiovascular outcomes of adenosine and verapamil in elderly and comorbid patients with SVT and to evaluate the utility of AI-assisted predictive analysis for identifying treatment-related clinical outcomes.

Methodology: It was a quantitative, comparative, observational study among elderly patients aged 60 years and above diagnosed with SVT. A structured questionnaire was used to analyze 211 responses from patients. Associated demographic variables, clinical variables, hemodynamic variables, and immediate clinical outcomes were documented. Descriptive statistics, normality test, reliability analysis, validity analysis, independent samples t-test, one-way ANOVA, Kruskal-Wallis test, chi-square test of independence, Pearson correlation, and binary logistic regression were all included as statistical analyses. AI-assisted predictive analysis was additionally performed using supervised machine-learning models to predict successful conversion to sinus rhythm and selected short-term cardiovascular outcomes. Model performance was evaluated using appropriate classification metrics, and feature-importance analysis was used to identify variables contributing to predicted outcomes.  A p-value below 0.05 was taken to be statistically significant.

Results: The findings indicated normal distribution, superior reliability, and tolerable validity. There was a significant difference in terms of the successful conversion to sinus rhythm, time taken to convert, hypotension, bradycardia, and hospital stay between the adenosine and verapamil groups (p < 0.05). Adenosine was correlated with an increased rate of conversion and hemodynamic stability, whereas verapamil was correlated with more adverse cases of hypotension and slowing of the heartbeats. A regression analysis was performed in the identification of adenosine use as an independent positive predictor of successful conversion.

Conclusion: Adenosine had better hemodynamic stability and better short-term cardiovascular outcomes with respect to verapamil among elderly and comorbid SVT patients. The present findings justify the consideration of adenosine as a first-line treatment in the at-risk populations. The AI-assisted predictive analysis provided additional insight into factors associated with successful conversion and short-term adverse cardiovascular outcomes, supporting the potential utility of AI-assisted analytical approaches in risk stratification and treatment assessment for high-risk SVT populations.