Cardiovascular risks associated with use of non-steroidal anti-inflammatory drugs in patients with non-obstructive coronary artery disease

Predicting heart failure mortality using the Danish Comorbidity Index for Acute Myocardial Infarction (DANCAMI)

BACKGROUND

Patients with congestive heart failure (HF) are often burdened with comorbidities that increase mortality. Comorbidity indices provide a standardised method to measure comorbidity burden and predict prognosis. We aimed to investigate whether the Danish Comorbidity Index for Acute Myocardial Infarction (DANCAMI) can discriminate mortality in patients with HF.

METHODS

We conducted a population-based cohort study of all adult Danish patients with first-time HF during 1995-2020 (N = 311,628). We used logistic regression to calculate the area under the receiver operating characteristic curve (AUC) for cardiovascular and all-cause mortality within 30 days, 1 year, and 10 years of diagnosis. The AUCs were computed for a model including age and sex (baseline) and models also including the DANCAMI, the Charlson Comorbidity Index (CCI), or the Elixhauser Comorbidity Index (ECI).

RESULTS

For all-cause mortality, the AUCs were higher for the DANCAMI than for the baseline model (30-day: 0.688 vs. 0.662; 1-year: 0.715 vs. 0.680; 10-year: 0.840 vs. 0.810). For cardiovascular mortality, the AUCs were comparable between the DANCAMI and the baseline model (30-day: 0.683 vs. 0.676; 1-year: 0.690 vs. 0.684; 10-year: 0.659 vs. 0.658). For both 30-day, 1-year, and 10-year all-cause and cardiovascular mortality, the AUCs for the CCI and the ECI were comparable to those for the DANCAMI.

CONCLUSIONS

Adding the DANCAMI to a model including patient age and sex improved discrimination of short and long-term all-cause mortality but not of cardiovascular mortality.

Influence of Low-Density Lipoprotein Cholesterol Levels on NSAID-Associated Cardiovascular Risks After Myocardial Infarction: A Population-Based Cohort Study

Aim

To examine whether low-density lipoprotein cholesterol (LDL-C) levels influence the cardiovascular risk associated with non-aspirin non-steroidal anti-inflammatory drug (NSAID) use after myocardial infarction (MI).

Methods

Using Danish health registries, we conducted a population-based cohort study of all adult patients with first-time MI during 2010-2020 with an LDL-C value before discharge. Based on the latest LDL-C value, we categorized patients into a low and a high LDL-C group (<3.0 vs ≥3.0 mmol/L). We used time varying Cox regression to compute hazard ratios (HRs) with 95% confidence intervals of the association between NSAID use and a major adverse cardiovascular event (MACE: recurrent MI, ischemic stroke, and all-cause death).

Results

We followed 50,573 patients for a median of 3.1 years. While exposed, 521 patients experienced a MACE: 312 in the low LDL-C group and 209 in the high LDL-C group. The HRs for MACE comparing NSAID use with non-use were 1.21 (1.11-1.32) overall, 1.19 (1.06-1.33) in the low LDL-C group, and 1.23 (1.07-1.41) in the high LDL-group. The HRs for recurrent MI and ischemic stroke were comparable between the LDL-C subgroups. The HRs for all-cause death were 1.22 (1.07-1.39) in the low LDL-C group and 1.54 (1.30-1.83) in the high LDL-C group. Changing the cut-off value for LDL-C to 1.8 and 1.4 mmol/L showed consistent results.

Conclusion

In patients with MI, LDL-C levels did not influence the increased risk of MACE associated with NSAID use, but might influence the association between NSAID use and all-cause death.