Citations

Background: Obstructive sleep apnea (OSA) increases the risk of stroke and cardiovascular diseases. However, its impact on geriatric patients with a prior history of stroke/transient ischemic attack (TIA) has not been adequately studied. Methods: We utilized the 2019 National Inpatient Sample in the US to identify geriatric patients with OSA (G-OSA) who had a prior history of stroke/TIA. We then compared subsequent stroke (SS) rates among sex and race subgroups. We also compared the demographics and comorbidities of SS+ and SS− groups and utilized logistic regression models to assess outcomes. Results: Out of 133,545 G-OSA patients admitted with a prior history of stroke/TIA, 4.9% (6520) had SS. Males had a higher prevalence of SS, while Asian-Pacific Islanders and Native Americans had the highest prevalence of SS, followed by Whites, Blacks, and Hispanics. The SS+ group had higher all-cause in-hospital mortality rates, with Hispanics showing the highest rate compared to Whites and Blacks (10.6% vs. 4.9% vs. 4.4%, p < 0.001), respectively. Adjusted analysis for covariates showed that complicated and uncomplicated hypertension (aOR 2.17 [95% CI 1.78–2.64]; 3.18 [95% CI 2.58–3.92]), diabetes with chronic complications (aOR 1.28 [95% CI 1.08–1.51]), hyperlipidemia (aOR 1.24 [95% CI 1.08–1.43]), and thyroid disorders (aOR 1.69 [95% CI 1.14–2.49]) were independent predictors of SS. The SS+ group had fewer routine discharges and higher healthcare costs. Conclusions: Our study shows that about 5% of G-OSA patients with a prior history of stroke/TIA are at risk of hospitalization due to SS, which is associated with higher mortality and healthcare utilization. Complicated and uncomplicated hypertension, diabetes with chronic complications, hyperlipidemia, thyroid disorders, and admission to rural hospitals predict subsequent stroke.

Background: Bariatric surgery (BS) has been shown to be beneficial in improving co-morbid conditions in morbidly obese patients. Long-term cardiovascular complications remain undefined and warrant further investigation. We examined the prevalence and risk of atrial fibrillation (AF) in obese patients who underwent BS. Methods: PUBMED/Medline, SCOPUS, EMBASE databases were systematically reviewed using relevant keywords to search prospective and retrospective studies reporting AF with long-term (at least >1-year follow-up) follow-up in patients who had undergone BS. Random effects models were used for meta-analysis and subgroup analysis. I 2 statistics was used to identify substantial (>75%) heterogeneity. Results: Nine studies (3 USA, 2 UK, 4 Sweden) including 24,164 patients who had undergone BS (mean BMI cut off: 35, mean age 42 years) with 29,330 controls were included in the analysis with a median follow-up of 8 years. Pooled prevalence of AF was lower in BS arm (3.0%, 95%CI: 1.4%-5%) as compared to non-BS arm (3.8%, 95% CI: 1.8%-5.0%). The Forest Plot (Fig. 1) depicts significantly reduced odds of having AF in patients who have undergone BS vs controls (OR: 0.74, 95%CI: 0.60-0.91, I 2 =70.2%, p<0.01). Sensitivity analysis using the leave-one-out method did confirm equivalent results. On subgroup analysis, AF prevalence in the BS group was slightly higher in studies with a mean age of ≥50 years (4.8%, 0-12%) as compared to cohorts with mean age <50 (2.0%, 1.4-5.0%). The pooled rate of AF was low on short-term follow-up compared to long-term follow-up after BS: 1.5% (0.9-2.5%) in 1-5 years, 1.9% (0.2-4.5%) in 6-10 years, 5.4% (0-13.9%) ≥10 years of BS. Conclusions: Obese patients undergoing BS had nearly 25% lower risk and lower pooled rate of AF when compared to controls over 8 years of follow-up. The protective effect of BS on reduced risk of AF was seen to gradually wane over longer follow-up which warrants continued efforts to effectively control CVD risk factors.

Introduction: Atrial Fibrillation (AF) has been associated with various behavioral risk factors such as tobacco, alcohol, and/or substance abuse. Hypothesis: The main objective is to describe the national trends and burden of tobacco and substance abuse in AF hospitalizations. Methods: The National Inpatient Sample database from 2007 to 2015 was utilized and the hospitalizations with AF were identified using the international classification of disease, Ninth Revision, Clinical Modification (ICD-9-CM) code 427.31 in the primary diagnosis column. They were stratified into without abuse, tobacco use disorder (TUD), substance use disorder (SUD), alcohol use disorder (AUD), and drug use disorder (DUD). We used the Jonckheere-Terpstra trend test to analyze the trend in this study. Results: Out of 3,631,507 AF hospitalizations, 852,110 (23.46%) had TUD, 1851,170 (5.1%) had SUD, 155,681 (4.29%) had AUD and 42,667 (1.17%) had DUD. The trends of all increased substantially during the study period (Figure) . The prevalence of TUD, SUD, AUD, and DUD was substantially increased across all age groups, races, and gender during the study period. Female sex was associated with lower odds TUD (0.57 (0.56-0.57), P-value <0.001), SUD (0.27 (0.26-0.27), P-value <0.001), AUD (0.22 (0.22-0.22), P-value <0.001), and DUD (0.51 (0.5-0.52), P-value <0.001). Among AF hospitalizations, the black race was associated with higher odds of SUD (1.12 (1.1-1.14), P-value <0.001), and DUD(1.42 (1.38-1.47), P-value <0.001). The younger age group (18-35 years), male, Medicare/Medicaid as primary insurance, and lower socioeconomic status were associated with increased risk of both TUD and SUDs. Conclusions: Tobacco and substance use disorder among hospitalized AF patients in the US mainly affects males, younger individuals, white more than black, and those of lower socioeconomic status which demands the development of preventive strategies to address multilevel influences.

Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.

Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.

Objectives: Atrial fibrillation is frequently seen in sepsis-related hospitalizations. However, large-scale contemporary data from the United States comparing outcomes among sepsis-related hospitalizations with versus without atrial fibrillation are limited. The aim of our study was to assess the frequency of atrial fibrillation and its impact on outcomes of sepsis-related hospitalizations. Design: Retrospective cohort study. Setting: The National Inpatient Sample databases (2010–2014). Patients: Primary discharge diagnosis of sepsis with and without atrial fibrillation were identified using prior validated International Classification of Diseases, 9th Edition, Clinical Modification codes. Interventions: None. Measurements and Main Results: Overall, 5,808,166 hospitalizations with the primary diagnosis of sepsis, of which 19.4% (1,126,433) were associated with atrial fibrillation. The sepsis-atrial fibrillation cohort consisted of older (median [interquartile range] age of 79 yr [70–86 yr] vs 67 yr [53–79 yr]; p < 0.001) white (80.9% vs 68.8%; p < 0.001) male (51.1% vs 47.5%; p < 0.001) patients with an extended length of stay (median [interquartile range] 6 d [4–11 d] vs 5 d [3–9 d]; p < 0.001) and higher hospitalization charges (median [interquartile range] $44,765 [$23,234–$88,657] vs $35,737 [$18,767–$72,220]; p < 0.001) as compared with the nonatrial fibrillation cohort. The all-cause mortality rate in the sepsis-atrial fibrillation cohort was significantly higher (18.4% and 11.9%; p = 0.001) as compared with those without atrial fibrillation. Although all-cause mortality (20.4% vs 16.6%) and length of stay (median [interquartile range] 7 d [4–11 d] vs 6 d [4–10 d]) decreased between 2010 and 2014, hospitalization charges increased (median [interquartile range] $41,783 [$21,430–$84,465] vs $46,251 [$24,157–$89,995]) in the sepsis-atrial fibrillation cohort. The greatest predictors of mortality in the atrial fibrillation-sepsis cohort were African American race, female gender, advanced age, and the presence of medical comorbidities. Conclusions: The presence of atrial fibrillation among sepsis-related hospitalizations is a marker of poor prognosis and increased mortality. Although we observed rising trends in sepsis and sepsis-atrial fibrillation–related hospitalizations during the study period, the rate and odds of mortality progressively decreased.

BackgroundObesity can lead to increased oxidative stress which is one of the proposed mechanisms in the etiopathogenesis of takotsubo cardiomyopathy (TCM).HypothesisThe presence of obesity adversely impacts clinical outcomes in TCM patients.MethodsWe queried the Nationwide Inpatient Sample database (2010‐2014) to identify adult patients admitted with a principal diagnosis of TCM with and without obesity. We compared the categorical and continuous variables by Pearson χ2 and Student t test, respectively, in propensity‐score matched cohorts.ResultsThe study cohort comprised 612 obese TCM (weighted n = 3034) and 5696 nonobese TCM (weighted n = 28 186) patients. Obese TCM patients were more often younger and private‐insurance enrollees. Cardiac complications including acute myocardial infarction (9.0% vs 7.4%; P = 0.04), cardiac arrest (2.3% vs. 0.4%; P < 0.001), cardiogenic shock (4.3% vs. 3.2%; P = 0.03), congestive heart failure (5.0% vs. 3.8%; P = 0.02), respiratory failure (12.9% vs. 11.0%; P = 0.021) and use of mechanical hemodynamic support (Impella; 0.2% vs. 0.0%, P = 0.02) were significantly higher among obese TCM patients. There were no significant differences between the 2 groups in all‐cause mortality (1.0% vs. 0.8%; P = 0.35), arrhythmia (24.5% vs. 22.7%, P = 0.123), length of stay (3.7 ±3.5 vs. 3.7 ±3.6 days; P = 0.68), and total hospital charges ($40 780.16 vs. $42 575.14; P = 0.08).ConclusionsObese TCM patients were more susceptible to developing TCM‐related cardiac complications than were nonobese TCM patients, without any impact on all‐cause in‐hospital mortality, LOS, and hospital charges.