Logo

American Heart Association

  32
  0


Final ID: Su3112

Evaluating the Atherogenic Index of Plasma as a Prognostic Indicator for Readmission Risk in Heart Failure Patients: A Retrospective Cohort Study

Abstract Body (Do not enter title and authors here): Aims: Among patients who are hospitalized with heart failure (HF), about 50% have readmissions within 6 months. The impact of atherogenic index of plasma (AIP) and low-density lipoprotein cholesterol (LDL-C) on HF readmission risk is unclear. Our study aims to determine if there is an association between AIP, LDL-C and readmission rate for HF.
Methods: We used a public dataset of patients hospitalized with a prior or new diagnosis of HF in Zigong Fourth People’s Hospital in China between 2016 to 2019 (https://doi.org/10.13026/5m60-vs44). AIP was categorized into <0.11 (normal risk), 0.11-0.21 (intermediate risk), and >0.21 (high risk). The association between AIP and 6-month readmission rate was explored through a Cox proportional hazard analysis with a crude model, one adjusted for age, gender, and BMI (Model 1), and one adjusted for additional variables such as type of HF, guideline-directed medical therapy, New York Heart Association cardiac function classification (fully adjusted model). The association between LDL- C tertile (≤1.46, 1.462.1 mmol/L) and readmission rate was also analyzed with the same adjustments. Competing risk analysis for mortality was done using the Fine-Gray model.
Results: A total of 1805 patients were included. There was no significant association between AIP level and readmission rate in the crude model (HR 1.03, 95% CI 0.93-1.14), Model 1 (HR 1.05, 95% CI 0.95-1.17), fully adjusted model (HR 1.03, 95% CI 0.95-1.18), and the Fine-Gray model (HR 0.99, 95% CI 0.94-1.05). In contrast, the higher LDL-C tertile was associated with decreased readmission risk in the crude model (HR 0.87, 95% CI 0.79-0.96) and Model 1 (HR 0.89, 95% CI 0.80-0.97). This association was no longer statistically significant in the fully adjusted (HR 0.93, 95% CI 0.84-1.03) and Fine-Gray model (HR 1.02, 95% CI 0.97-1.08).
Conclusion: In this Chinese cohort of hospitalized HF patients, we found no significant association between AIP levels and 6-month readmission rate, even after extensive clinical covariate adjustment and accounting for competing mortality risk. Lower LDL-C level showed a modest trend toward reduced readmission in unadjusted models but this association was not sustained after full adjustment. These findings suggest that AIP and LDL-C may have limited utility as independent predictors of 6-month HF readmission rates. Future research is warranted to evaluate the role of AIP and LDL-C level in long-term HF outcomes.
  • Lee, Grace  ( Boston Medical Center , Boston , Massachusetts , United States )
  • Yoo, Tae Kyung  ( Boston Medical Center , Boston , Massachusetts , United States )
  • Lee, Seung Wook  ( MetroWest Medical Center , Framingham , Massachusetts , United States )
  • Miyashita, Satoshi  ( Cleveland Clinic , Cleveland , Ohio , United States )
  • Author Disclosures:
    Grace Lee: DO NOT have relevant financial relationships | Tae Kyung Yoo: No Answer | Seung Wook Lee: DO NOT have relevant financial relationships | Satoshi Miyashita: No Answer
Meeting Info:

Scientific Sessions 2025

2025

New Orleans, Louisiana

Session Info:

AI, Digital Health and Remote Monitoring on the HF Horizon

Sunday, 11/09/2025 , 11:30AM - 12:30PM

Abstract Poster Board Session

More abstracts on this topic:
A Bridge from Sweet to Sour: A Case of Recurrent Myocardial Stunning in Diabetic Ketoacidosis

Satish Vikyath, Pargaonkar Sumant, Slipczuk Leandro, Schenone Aldo, Maliha Maisha, Chi Kuan Yu, Sunil Kumar Sriram, Borkowski Pawel, Vyas Rhea, Rodriguez Szaszdi David Jose Javier, Kharawala Amrin, Seo Jiyoung

A Machine Learning Readmission Risk Prediction Model for Cardiac Disease

Bailey Angela, Wang Wei, Shannon Clarence, Huling Jared, Tignanelli Christopher

You have to be authorized to contact abstract author. Please, Login
Not Available