Validation of prediction tools for GI bleeding in patients on dual anti-platelet therapy after percutaneous coronary intervention.

BACKGROUND AND AIMS: The management of dual anti-platelet therapy after percutaneous coronary intervention (PCI) and GI bleeding (GIB) remains a clinical dilemma. We sought to identify predictors of GIB and recurrent bleeding and to determine whether recurrent bleeding increases the risk of major adverse cardiovascular events (MACEs). METHODS: In this single-center retrospective study, patients undergoing PCI were identified. The primary and secondary endpoints were GIB at 180 days and recurrent bleeding or MACE at 365 days. Logistic regression was used to identify predictors of GIB and recurrent bleeding. Cox proportional hazards modeling was used to determine whether recurrent bleeding can predict a MACE. RESULTS: Five hundred thirty-six patients were included. On multivariable analysis, PCI for acute coronary syndrome was associated with a 95% increased odds of GIB (P < .001). The P2Y12 inhibitor was continued in >90% of patients, which trended toward significance for recurrent bleeding (P < .10). The HAS-BLED score (Hypertension, Abnormal renal and liver function, Stroke, Bleeding tendency or predisposition, Labile INRs, Elderly, Drugs), including a labile international normalized ratio and prior major bleeding, was strongly associated with recurrent bleeding (P ≤ .009). Recurrent bleeding was associated with a 115% increased risk of MACEs (P = .02). We derived a novel risk score, named the SIGE score ([S]TEMI at PCI, having a labile [I]NR at PCI, index [G]IB within 180 days of PCI, and previous precatheterization [E]ndoscopy within 6 months), to predict recurrent bleeding at 365 days with a high predictive accuracy (area under the curve, .773; 95% confidence interval, .702-.845). CONCLUSIONS: The SIGE score may help to predict recurrent bleeding, which was shown to be associated with an increased risk of MACEs. Further external validation is needed.

Metabolic Unhealthiness is Associated With Increased Risk of Critical COVID-19 Pneumonia and Inpatient Mortality in Hospitalized Patients with Obesity or Overweight.

Background and aims Being metabolically unhealthy (MU) is defined as having either hypertension, hyperlipidemia, type 2 diabetes mellitus/pre-diabetes, or fatty liver disease. We aimed to determine if MU was associated with severe COVID-19 pneumonia (severe disease). Methods We performed a single-center retrospective study between March 2020 and August 2021 for patients with overweight or obesity hospitalized with COVID-19 pneumonia. Logistic regression analysis was utilized to derive a risk score for severe disease. The accuracy of the model was assessed using the area under the receiver operating characteristic curve (AUROCC) and bootstrap resampling. Results A total of 334 of 450 patients hospitalized with COVID-19 pneumonia (74.2%) were MU. Patients who were MU had higher in-hospital mortality (10.5% vs. 2.6%) and longer length of hospitalization (median 6 vs. 4 days). MU was not associated with severe disease, p=0.311. On multivariable analysis, older age, male sex, and Asian race were associated with severe disease. Not being vaccinated was associated with doubled odds of severe disease. The AUROCC of the final model was 0.66 (95% CI: 0.60 to 0.71). The risk score at the lowest quintile had a 33.1% to 65.5% predicted risk and a 58.7% observed risk of severe disease, whereas, at the highest quintile, there was an 85.7% to 97.7% predicted risk and an 89.7% observed risk of severe disease. Conclusion Being MU was not a predictor of severe disease, even though mortality was higher despite having higher rates of vaccination. This risk score may help to predict severe disease in hospitalized patients with obesity or overweight. External validation is recommended.