# Association between marital status and in-hospital mortality in patients with acute coronary syndrome: a multivariable logistic regression analysis

## TL;DR

This study finds that being unmarried is linked to higher in-hospital death risk for patients with acute coronary syndrome.

## Contribution

The study identifies marital status as an independent risk factor and develops a predictive scoring system for in-hospital mortality.

## Key findings

- Unmarried patients had significantly higher in-hospital mortality (OR = 4.20) after adjusting for other factors.
- A predictive model including marital status showed high accuracy (AUC = 0.972) for in-hospital mortality.
- A nomogram scoring system was developed to predict mortality risk using marital status and clinical variables.

## Abstract

In patients with acute coronary syndrome (ACS), marital status may have a significant impact on the prognosis. However, it remains unclear whether marital status influences in-hospital mortality separately.

This study aims to examine the relationship between marital status and in-hospital mortality in ACS patients and to develop a predictive scoring system using a multivariable logistic regression model to evaluate marital status as an independent risk factor for in-hospital mortality.

We included 12,760 consecutive patients diagnosed with ACS during hospitalization. Patients were categorized into a death group or a survival group based on in-hospital outcomes, and further divided into married and non-married groups according to their marital status. Clinical data, including age, gender, ACS type, Killip classification, high-sensitivity troponin T (hsTnT), creatinine, and CKMB, were collected. We performed multivariable logistic regression analysis to assess the relationship between marital status and in-hospital mortality, and developed a predictive model. The model's performance was validated using ROC curve analysis and decision curve analysis (DCA).

Univariate analysis showed that being unmarried was significantly associated with higher in-hospital mortality (OR = 5.40, 95% CI: 3.26–8.95, P < 0.0001). Multivariable logistic regression confirmed this association (OR = 4.20, 95% CI: 1.93–9.10, P = 0.0003), indicating that marital status is an independent risk factor for in-hospital mortality. The ROC curve demonstrated a high predictive accuracy for the model, with an AUC of 0.972 (95% CI: 0.957–0.987). Decision curve analysis showed that the model including marital status provided the highest net benefit across most threshold probabilities. Based on these findings, we developed a nomogram scoring system incorporating marital status, age, ACS type, hsTnT, creatinine, CKMB, and Killip classification to predict in-hospital mortality risk.

The marital status of ACS patients is an important independent predictor of in-hospital mortality. Unmarried patients have a significantly higher risk of in-hospital death.