Examining the Role of Cerebral Embolic Protection Devices in Preventing Postoperative Stroke in Patients with a History of Stroke or Transient Ischemic: Insights from the National Inpatient Sample.

Cerebral embolic protection devices (CEPD) during transcatheter aortic valve replacement (TAVR) have been shown to lower the risk of stroke during the procedure. However, their long-term and clinical effects on neuro-cognition are unknown. Therefore, we hypothesized the benefit of CEPD in TAVR patients with a prior history of stroke or transient ischemic attack (TIA). National Inpatient Sample (2019) and International Classification of Diseases, 10th Revision codes were used to identify patients undergoing TAVR with prior stroke or TIA. Propensity-matched analysis was performed to adjust for baseline characteristics and comorbidities. Primary outcome measures were postoperative stroke and all-cause mortality. Length of stay and hospital cost were secondary outcomes. Of 8450 unmatched TAVR patients with prior stroke or TIA in 2019, 1095 (13%) utilized CEPD. After propensity matching previous myocardial infarction (MI), coronary artery bypass grafting, and drug abuse were higher in the TAVR-only cohort. Postoperative stroke rate (1.4% vs 2.2%; P = 0.081) and odds [adjusted odds ratio (aOR), 0.48; 95% confidence interval (CI), 0.11-2.17; P = 0.341] were lower in the CEPD group. There was no difference in all-cause in-hospital mortality between the 2 groups (0.9% vs 1.0%). Length of stay (3 vs 2 days, P <0.001) and hospital expenditure ($172,711 vs $162,284; P = 0.002) were higher for the TAVR-only cohort. CEPD in TAVR patients with prior stroke or TIA did not show statistically significant postoperative stroke benefits. However, further larger-scale prospective studies are needed to evaluate the long-term neurocognitive benefits of CEPD in these patients. As the use of TAVR continues to expand, optimizing peri-procedural strategies such as the use of CEPD remains a critical area of research to improve patient outcomes.

Association of Prediabetes and Recurrent Stroke in Atrial Fibrillation Patients: A Population-Based Analysis of Hospitalizations and Outcomes.

Prediabetes is a risk factor for ischemic stroke in atrial fibrillation (AF) patients, yet, its impact on recurrent stroke in AF patients remains understudied. Using the 2018 National Inpatient Sample, we investigated the link between Prediabetes and recurrent stroke in AF patients with prior stroke or transient ischemic attack (TIA). Among 18,905 non-diabetic AF patients, 480 (2.5%) had prediabetes. The prediabetic group, with a median age of 78, exhibited a two-fold higher risk of recurrent stroke compared to the non-prediabetic cohort (median age 82), as evidenced by both unadjusted (OR 2.14, 95% CI 1.72-2.66) and adjusted (adjusted for socio-demographics/comorbidities, OR 2.09, 95% CI 1.65-2.64, p < 0.001). The prediabetes cohort, comprising more male and Black patients, demonstrated associations with higher Medicaid enrollment, admissions from certain regions, and higher rates of hyperlipidemia, smoking, peripheral vascular disease, obesity, and chronic obstructive pulmonary disease (all p < 0.05). Despite higher rates of home health care and increased hospital costs in the prediabetes group, the adjusted odds of all-cause mortality were not statistically significant (OR 0.55, 95% CI 0.19-1.56, p = 0.260). The findings of this study suggest that clinicians should be vigilant in managing prediabetes in AF patients, and strategies to prevent recurrent stroke in this high-risk population should be considered.

Prediabetes: An overlooked risk factor for major adverse cardiac and cerebrovascular events in atrial fibrillation patients.

BACKGROUND: Prediabetes is a well-established risk factor for major adverse cardiac and cerebrovascular events (MACCE). However, the relationship between prediabetes and MACCE in atrial fibrillation (AF) patients has not been extensively studied. Therefore, this study aimed to establish a link between prediabetes and MACCE in AF patients. AIM: To investigate a link between prediabetes and MACCE in AF patients. METHODS: We used the National Inpatient Sample (2019) and relevant ICD-10 CM codes to identify hospitalizations with AF and categorized them into groups with and without prediabetes, excluding diabetics. The primary outcome was MACCE (all-cause inpatient mortality, cardiac arrest including ventricular fibrillation, and stroke) in AF-related hospitalizations. RESULTS: Of the 2965875 AF-related hospitalizations for MACCE, 47505 (1.6%) were among patients with prediabetes. The prediabetes cohort was relatively younger (median 75 vs 78 years), and often consisted of males (56.3% vs 51.4%), blacks (9.8% vs 7.9%), Hispanics (7.3% vs 4.3%), and Asians (4.7% vs 1.6%) than the non-prediabetic cohort (P < 0.001). The prediabetes group had significantly higher rates of hypertension, hyperlipidemia, smoking, obesity, drug abuse, prior myocardial infarction, peripheral vascular disease, and hyperthyroidism (all P < 0.05). The prediabetes cohort was often discharged routinely (51.1% vs 41.1%), but more frequently required home health care (23.6% vs 21.0%) and had higher costs. After adjusting for baseline characteristics or comorbidities, the prediabetes cohort with AF admissions showed a higher rate and significantly higher odds of MACCE compared to the non-prediabetic cohort [18.6% vs 14.7%, odds ratio (OR) 1.34, 95% confidence interval 1.26-1.42, P < 0.001]. On subgroup analyses, males had a stronger association (aOR 1.43) compared to females (aOR 1.22), whereas on the race-wise comparison, Hispanics (aOR 1.43) and Asians (aOR 1.36) had a stronger association with MACCE with prediabetes vs whites (aOR 1.33) and blacks (aOR 1.21). CONCLUSION: This population-based study found a significant association between prediabetes and MACCE in AF patients. Therefore, there is a need for further research to actively screen and manage prediabetes in AF to prevent MACCE.

Association of Cannabis Use Disorder With Hospitalizations for Pulmonary Embolism and Subsequent in-Hospital Mortality in Young Adults: A Contemporary Nationwide Analysis.

BACKGROUND: With the increase in popularity of cannabis and its use and the lack of large-scale data on cannabis use and venous thromboembolism and pulmonary embolism (PE), we used a nationally representative cohort of young adults (aged 18-44 years) to compare the odds of admissions and in-hospital mortality of PE with and without cannabis use disorder (CUD). METHODS AND RESULTS: Identified patients with PE using the National Inpatient Sample (2018) were compared for baseline, comorbidities, and outcomes. Multivariable regression analysis, adjusted for covariates, was used to compare the odds of PE in young patients with CUD (CUD+) versus those without (CUD-) and those with prior venous thromboembolism. Propensity score-matched analysis (1:6) was also performed to assess in-hospital outcomes. A total of 61 965 (0.7%) of 8 438 858 young adult admissions in 2018 were PE related, of which 1705 (0.6%) had CUD+. On both unadjusted (odds ratio, 0.80 [95% CI, 0.71-0.90]; P<0.001) and adjusted regression analyses, the CUD+ cohort had a lower risk of PE admission. The CUD+ cohort had fewer routine discharges (58.3% versus 68.3%) and higher transfers to short-term (7.9% versus 4.8%) and nursing/intermediate care (12.6% versus 9.5%) (P<0.001). The PE-CUD+ cohort of in-hospital mortality did not differ from the CUD- cohort. Propensity score-matched (1:6) analysis revealed comparable mortality odds with higher median hospital stay and cost in the CUD+ cohort. CONCLUSIONS: Young adults with CUD demonstrated lower odds of PE hospitalizations without any association with subsequent in-hospital mortality. The median hospital stay of the CUD+ cohort was longer, they were often transferred to other facilities, and they had a higher cost.

Examining prevalence and predictors of pulmonary hypertension in adults with idiopathic pulmonary fibrosis: a population-based analysis in the United States.

Pulmonary hypertension (PH) often complicates idiopathic pulmonary fibrosis (IPF), a progressive parenchymal lung disease. We investigated predictors of PH in IPF hospitalizations in the United States. We identified IPF hospital- izations with or without PH using the National Inpatient Sample (2018) and relevant ICD-10-CM codes. We com- pared demographics, comorbidities, PH prevalence, and its multivariable predictors adjusted for confounders among patients with IPF. In 2018, 30,335 patients from 30,259,863 hospitalizations had IPF, of which 8,075 (26.6%) had PH. Black (41%), Hispanic (21.3%), and female (28.7%) patients had higher rates of PH compared to white patients (25%). The IPF-PH cohort was hospitalized more often in urban teaching (77.7% vs. 72.2%), Midwest, and West hospitals vs. non-PH cohort. Comorbidities including congestive heart failure (2.08 [1.81-2.39]), valvular disease (2.12 [1.74-2.58]), rheumatoid arthritis/collagen vascular disease (1.32 [1.08-1.61]) predicted higher odds of PH. The PH-IPF cohort was less often routinely discharged (35.4%) and more likely to be transferred to intermediate care facilities (22.6%) and home health care (27.1%) (P < 0.001). The PH-IPF group had higher rates of all-cause mortality (12.3% vs. 9.4%), cardiogenic shock (2.4% vs. 1%), dysrhythmia (37.6% vs. 29%), and cardiac arrest (2.7% vs. 1.5%) vs. non-PH cohort (all P < 0.001). Patients with PH-IPF also had longer hospital stays (9 vs. 8) and a higher median cost ($23,054 vs. $19,627, P < 0.001). Nearly 25% of IPF hospitalizations with PH were linked to higher mortality, extended stays, and costs, emphasizing the need to integrate demographic and comorbidity predictors into risk stratification for improved outcomes in patients with IPF-PH.

Predicting Risk of Cardiac Arrest in Young Asian Americans: Insights from an Artificial Neural Network Analysis of the Nationwide Cohort.

We used the Artificial Neural Network (ANN) model to identify predictors of Sudden Cardiac Arrest (SCA) in a national cohort of young Asian patients in the United States. The National Inpatient Sample (2019) was used to identify young Asians (18-44-year-old) who were hospitalized with SCA. The neural network's predicted criteria for SCA were selected. After eliminating missing data, young Asians (n = 65,413) were randomly divided into training (n = 45,094) and testing (n = 19347) groups. Training data (70%) was used to calibrate ANN while testing data (30%) was utilized to assess the algorithm's accuracy. To determine ANN's performance in predicting SCA, we compared the frequency of incorrect prediction between training and testing data and measured the area under the Receiver Operating Curve (AUC). The 2019 young Asian cohort had 327,065 admissions (median age 32 years; 84.2% female), with SCA accounting for 0.21%. The exact rate of error in predictions vs. tests was shown by training data (0.2% vs 0.2%). In descending order, the normalized importance of predictors to accurately predict SCA in young adults included prior history of cardiac arrest, sex, age, diabetes, anxiety disorders, prior coronary artery bypass grafting, hypertension, congenital heart disease, income, peripheral vascular disease, and cancer. The AUC was 0.821, indicating an excellent ANN model for SCA prediction. Our ANN models performed excellently in revealing the order of important predictors of SCA in young Asian American patients. These findings could have a considerable impact on clinical practice to develop risk prediction models to improve the survival outcome in high-risk patients.