What is the clinical evidence from this study?

Study design: Observational. Population: Acute myocardial infarction (AMI) (n=204). Intervention: Risk factors (NT-proBNP, RDW, Hcy). Primary outcome: New-onset atrial fibrillation (NOAF) (OR 4.677, 95% CI 1.774-12.328, p=0.002).

May 4, 2026SHILAP Revista de lepidopterología0 citationsOpen Access

Exploring risk factors for new-onset atrial fibrillation in elderly patients with myocardial infarction based on serum NT-proBNP, RDW, Hcy, and clinical parameters: an exploratory study using LASSO-logistic regression

QFQun FanWannan Medical College YLYang LingWannan Medical College CFCong FuWannan Medical College

Key Result

In elderly patients with acute myocardial infarction, elevated serum NT-proBNP was independently associated with a significantly increased risk of new-onset atrial fibrillation (OR 4.677).

Key Points

To explore the association of NT-proBNP, RDW, Hcy, and clinical parameters with new-onset atrial fibrillation in elderly myocardial infarction patients.
Retrospective study with 204 elderly myocardial infarction patients (January 2020—December 2022)
Used LASSO logistic regression for feature selection and multivariate logistic regression to identify risk factors
Developed a nomogram for visualizing risk factors and evaluated model performance with ROC and bootstrap resampling.
Identified key predictors of NOAF: female gender (OR=3.367), longer hospitalization (OR=1.110), Killip class II-IV (OR=3.171), NT-proBNP (OR=4.677), RDW (OR=1.358), and Hcy (OR=1.814), all P < 0.05
Nomogram model achieved AUC of 0.926 with good calibration (P=0.541)
Internal validation gave optimism-corrected AUC of 0.901, confirming model accuracy and clinical benefit.

Study Design

Type

Observational (n=204)

Multicenter

Structured PICO

Population

204 elderly patients (age ≥60 years) with acute myocardial infarction (AMI), divided into new-onset atrial fibrillation (NOAF) (n=41) and non-NOAF (n=163) groups. Mean age ~73 years.

Outcome

New-onset atrial fibrillation (NOAF) during hospitalization

Elevated NT-proBNP, RDW, and Hcy, along with female gender, longer hospitalization, and Killip class II-IV, are independent predictors of new-onset atrial fibrillation in elderly patients with acute myocardial infarction.

Main Result

Effect estimate: OR 4.677 (95% CI 1.774-12.328)

p-value: p=0.002

Limitations

Modest sample size and low number of events (n=41) resulting in a low events-per-variable ratio and risk of overfitting.
Feature selection and model evaluation were performed on the same dataset without external validation.
Inclusion of hospitalization duration introduces temporal ambiguity as it may be a consequence rather than a predictor.
Lack of data on key medications (e.g., beta-blockers, antiarrhythmics) and revascularization strategies.
Short follow-up duration may underestimate the true incidence of NOAF.

Abstract

ObjectiveTo investigate the association of serum N-terminal pro-brain natriuretic peptide (NT-proBNP), red cell distribution width (RDW), homocysteine (Hcy), and clinical parameters with new-onset atrial fibrillation (NOAF) in elderly patients with acute myocardial infarction (AMI), and to identify potential risk factors in an exploratory analysis.MethodsThis retrospective exploratory study enrolled 204 elderly AMI patients (January 2020—December 2022), divided into NOAF (n = 41) and non-NOAF (n = 163) groups. Clinical and laboratory data were collected. LASSO regression was used for initial feature selection from candidate variables. Multivariate logistic regression was then employed to identify factors associated with NOAF. A nomogram was constructed to visualize the risk factor model. Given the exploratory nature and limited number of events (n = 41), model performance metrics including area under the ROC curve (AUC), calibration, and decision curve analysis were evaluated with caution, accompanied by internal validation using 1,000 bootstrap resamples to assess overfitting.ResultsSignificant differences were found between the NOAF and non-NOAF groups in gender, smoking status, hospitalization duration, Killip class, NT-proBNP, RDW, and Hcy (P < 0.05). LASSO regression identified six key predictors: gender, hospitalization duration, Killip class, NT-proBNP, RDW, and Hcy. Multivariate logistic regression confirmed these as independent risk factors: female gender (OR = 3.367, 95% CI: 1.193–9.498), longer hospitalization duration (OR = 1.110 per day, 95% CI: 1.021–1.206), Killip class II-IV (OR = 3.171, 95% CI: 1.157–8.689), higher NT-proBNP (OR = 4.677 per ng/mL increase, 95% CI: 1.774–12.328), higher RDW (OR = 1.358 per % increase, 95% CI: 1.163–1.585), and higher Hcy (OR = 1.814 per µmol/L increase, 95% CI: 1.414–2.328); all P < 0.05. The model showed good fit (Hosmer-Lemeshow χ² = 6.957, P = 0.541). The final combined nomogram model achieved an AUC of 0.926 (95% CI: 0.880–0.973) in the development set. Internal validation via 1,000 bootstrap resamples yielded an optimism-corrected AUC of 0.901. Calibration was assessed visually and statistically (Hosmer–Lemeshow χ² = 6.957, P = 0.541), showing good agreement between predicted and observed risks (Figure 4). Internal validation indicated good calibration (Cox-Snell R² = 0.593, Nagelkerke R² = 0.376), and decision curve analysis confirmed a high net clinical benefit.ConclusionThis exploratory study identifies gender, hospitalization duration, Killip class, NT-proBNP, RDW, and Hcy as factors significantly associated with NOAF in elderly AMI patients. However, due to the modest sample size, low events-per-variable ratio, and lack of external validation, these findings should be considered hypothesis-generating. The proposed model is not ready for clinical application. Further validation in larger, prospective cohorts is essential to confirm these associations and to develop a robust predictive tool.

Ask AI

Helpful

Bookmark

View Full Paper