Prevalence and impact of tobacco use disorder on in-hospital mortality in patients hospitalized with non-group 1 pulmonary hypertension: a nationwide propensity score-matched analysis, 2019

Numerous studies indicated that patients with tobacco use disorder (TUD) are inversely associated with mortality in what is known as the smoker's paradox. However, limited studies have been conducted on the impact of TUD on the in-hospital mortality rates of patients with secondary pulmonary hypertension (PH, Non-Group 1 PH). Using the 2019 National Inpatient Sample, we identified PH and divided it into TUD and non-TUD to compare the comorbidities and in-hospital mortality between the two after 1:1 propensity-score matching. Of 1,129,440 PH hospitalizations, 12.1 % had TUD. After matching (n=133545, each group), TUD had lower median age (62 vs. 63), higher females (49 vs. 46.6 %), blacks (25.9 vs. 25.3 %), lower household income (40.8 vs. 32.7 %), Medicaid (22.4 vs. 14.8 %), non-elective (93.5 vs. 89.8 %), rural (9.3 vs. 6.7 %), urban non-teaching (17.2 vs 15.8 %) admissions. All CV comorbidities and other substance use were higher in TUD except CHF and valvular heart disease, TUD+ cohort and lower mortality (3.3 vs. 4.2 %, OR 0.78, p<0.001), higher routine discharges (53.8 vs. 51.3 %, p<0.001) and lower total charges ($47155 vs. 51909, p<0.001) than non-TUD. Although PH patients with TUD had a higher comorbidity burden, they had lower in-hospital mortality rates along with lower total charges of hospitalization, mandating real-world data to validate these results. See also the Graphical abstract(Fig. 1).

Hypertensive Crisis-Related Hospitalizations and Subsequent Major Adverse Cardiac Events in Young Adults with Cannabis Use Disorder: A Nationwide Analysis

Background and Objectives: With the growing recreational cannabis use and recent reports linking it to hypertension, we sought to determine the risk of hypertensive crisis (HC) hospitalizations and major adverse cardiac and cerebrovascular events (MACCE) in young adults with cannabis use disorder (CUD+). Material and Methods: Young adult hospitalizations (18−44 years) with HC and CUD+ were identified from National Inpatient Sample (October 2015−December 2017). Primary outcomes included prevalence and odds of HC with CUD. Co-primary (in-hospital MACCE) and secondary outcomes (resource utilization) were compared between propensity-matched CUD+ and CUD- cohorts in HC admissions. Results: Young CUD+ had higher prevalence of HC (0.7%, n = 4675) than CUD- (0.5%, n = 92,755), with higher odds when adjusted for patient/hospital-characteristics, comorbidities, alcohol and tobacco use disorder, cocaine and stimulant use (aOR 1.15, 95%CI:1.06−1.24, p = 0.001). CUD+ had significantly increased adjusted odds of HC (for sociodemographic, hospital-level characteristics, comorbidities, tobacco use disorder, and alcohol abuse) (aOR 1.17, 95%CI:1.01−1.36, p = 0.034) among young with benign hypertension, but failed to reach significance when additionally adjusted for cocaine/stimulant use (aOR 1.12, p = 0.154). Propensity-matched CUD+ cohort (n = 4440, median age 36 years, 64.2% male, 64.4% blacks) showed higher rates of substance abuse, depression, psychosis, previous myocardial infarction, valvular heart disease, chronic pulmonary disease, pulmonary circulation disease, and liver disease. CUD+ had higher odds of all-cause mortality (aOR 5.74, 95%CI:2.55−12.91, p < 0.001), arrhythmia (aOR 1.73, 95%CI:1.38−2.17, p < 0.001) and stroke (aOR 1.46, 95%CI:1.02−2.10, p = 0.040). CUD+ cohort had fewer routine discharges with comparable in-hospital stay and cost. Conclusions: Young CUD+ cohort had higher rate and odds of HC admissions than CUD-, with prevalent disparities and higher subsequent risk of all-cause mortality, arrhythmia and stroke.

Predictors of acute pulmonary embolism-related hospitalizations – an artificial neural network analysis using a nationwide cohort in the United States

Background

Considering a paucity of large-scale data on predictors of pulmonary embolism (PE) and its higher association with complications and worse outcomes, we aimed to determine the predictors of PE in this United States population-based analysis using Artificial Neural Network (ANN) Model in a nationally representative cohort.

Methods

We identified PE-related hospitalizations using 2018's National Inpatient Sample database. The relevant predictive factors for ANN were selected for this cohort. Of all admissions (unweighted n=7,105,498, weighted n=35,527,481), PE cohort (weighted n=387805) consisted of 1.1% of all admissions in 2018. The 2018 cohort was randomly split into training data (unweighted n=4716132, 70.0%) which were used to calibrate ANN and testing data (unweighted n=2019290, 30%) which were used to assess the accurateness of the algorithm. We equated the rate of incorrect prediction between training and testing data and measured the Area under Receiver Operator Curve (AUC) to determine ANN's efficacy in predicting PE hospitalizations.

Results

Patients hospitalized with PE often consisted of older (mean age 62.5±17.1 years), female (51.3%), white (70.5%) patients, and patients from lower-income quartile (0–25% income quartile: 28.8%%), often admitted non-electively (93.7%) with higher rates of cardiovascular disease risk factors. PE admissions revealed significantly higher (6.5% vs. 1.9%, p&lt;0.001) in-hospital mortality, less frequent routine discharges (51.4% vs. 68.1%) and more frequent other facility transfers and requirement of home health care. Normalized Predictors of PE admissions are displayed in Fig. 1. Our ANN model had AUC 0.873 which correlates with an excellent prediction model. Our data demonstrated low levels (0.8%) error in both testing and training models.

Conclusion

Our ANN model showed high performance to predict risk factors for PE admissions in the US population. It will enable clinicians to screen patients at high-risk for PE admissions, curtail complication rate, improve survival and lower the healthcare cost.

Funding Acknowledgement

Type of funding sources: None.

Comparison of Percutaneous Coronary Intervention Outcomes Among Patients With Obstructive Sleep Apnea, Chronic Obstructive Pulmonary Disease Overlap, and Pickwickian Syndrome (Obesity Hypoventilation Syndrome)

Background

Obstructive sleep apnea (OSA) is often present in coronary artery disease patients and confers a high risk of complications following percutaneous coronary interventions (PCI). The impact of two commonly associated comorbid conditions, chronic obstructive pulmonary disease (COPD) and obesity hypoventilation syndrome (OHS, Pickwickian syndrome) in OSA patients undergoing PCI has never been studied.

Methods

The National Inpatient Sample (NIS; 2007-2014) was queried using the International Classification of Diseases, Clinical Modification 9 (ICD-9-CM) codes to compare baseline characteristics, comorbidities, and outcomes in adults undergoing PCI with OSA, COPD-overlap syndrome, and OSA+OHS.

Results

Of a total of 4,792,177 PCI-related inpatient encounters, OSA, OSA-COPD overlap syndrome, and OSA+OHS were found to be present in 153,706 (median age 62 years, 79.4% male), 65135 (median age 65 years, 66.0% male), and 2291 (median age 63 years, 58.2% males) patients, respectively. The OHS+OSA cohort, when compared to the COPD-OSA and OSA cohorts, was found to have the worst outcomes in terms of all-cause mortality (2.8% vs. 1.5% vs. 1.1%), hospital stay (median 6 vs. 3 vs. 2 days), hospital charges ($147, 209 vs. $101,416 vs. $87,983). Complications, including cardiogenic shock (7.3% vs. 3.4% vs. 2.6%), post-procedural myocardial infarction (11.2% vs. 7.1% vs. 6.0%), iatrogenic cardiac complications (6.1% vs. 3.5% vs. 3.7%), respiratory failure, acute kidney injury, infections, and pulmonary embolism, were also significantly higher in patients with OHS+OSA. Adjusted multivariable analysis revealed equivalent results with OHS+OSA having worse outcomes than OSA-COPD and OSA.

Conclusion

Concomitant OHS and COPD were linked to worse clinical outcomes in patients with OSA undergoing PCI. Future prospective studies are warranted to fully understand related pathophysiology, evaluate and validate long-term outcomes, and formulate effective preventive and management strategies.

Abstract 69: Predictors Of Cardiac Arrest-related Hospitalizations In Young (18-44 Years) Females - An Artificial Neural Network Analysis Using A Nationwide Cohort

Background: Considering the limited availability of data on Cardiac Arrest (CA) in young patients and especially females, we aimed to determine the predictors of CA in this population using Artificial Neural Network (ANN) Model in a national cohort from the United States.

Methods: We identified CA-related hospitalizations among young females (18-44 years) using 2018’s National Inpatient Sample database. ANN’s predictive factors were selected for this cohort. Young females with CA (n=10810, 0.2% of all 2018 young female admissions) were randomly split into training data (n=7567, 70%) which were used to calibrate ANN and testing data (n=3243, 30%) which were used to evaluate the accuracy of the algorithm. We compared the frequency of incorrect prediction between training and testing data and measured the Area under Receiver Operator Curve (AUC) to determine ANN’s efficacy in predicting CA.

Results: Young females with CA often consisted of older (median age 36 vs 30 years), blacks (25.3% vs 18%), and patients from lower-income quartile (0-25% income quartile:36.4% vs 29.9%) with higher rates of modifiable cardiovascular disease risk factors vs. females admitted without CA (p<0.001). Females with CA expectedly had significantly high (48.4%) in-hospital mortality. Normalized Predictors are displayed in Table 1. Our ANN model had AUC 0.902 (Fig 1) which correlates with an excellent prediction model. Our data showed 0.2% error in both testing and training models.

Conclusion: Our ANN model achieved high performance to predict risk factors for CA admissions in young females. It will enable clinicians to screen high-risk young female hospitalized patients and improve survival in them.

Abstract 158: Burden And Predictors Of Mortality And Major Adverse Cardiovascular Outcomes In Heart Failure Preserved Ejection Fraction Patients Admitted With Acute Respiratory Distress Syndrome (ARDS)

Background: Relation between Acute Respiratory Distress Syndrome (ARDS) and heart failure with preserved ejection fraction (HFpEF) are understudied and the data on these two concomitantly is lacking in the literature. Therefore, we sought to assess the burden and predictors of major adverse cardiovascular and cerebrovascular events (MACCE) and all-cause mortality in ARDS patients with HFpEF.

Methods: The National Inpatient Sample (NIS) database was used to identify patients with HFpEF (after excluding patients with heart failure reduced ejection fraction) who required inpatient hospitalization for ARDS. Administrative ICD10 codes were used to identify the population of interest. Multivariate regression analysis was performed to assess the predictors of all-cause mortality and major adverse cardiovascular outcomes in the selected cohort.

Results: Of 28,731,562 hospital admissions, 3,010 (0.14%) patients were admitted with ARDS and had HFpEF. Of those patients, 1,095 (36.4%) had all-cause mortality, and 1,415 (47.0%) had MACCE. In multivariate regression analysis, older age (OR 3.60, CI 1.40-9.28), 26-50 th quartile income (OR 2.10, CI 1.13-3.91), urban hospital admissions (OR 2.19, CI 1.20-4.01) as well as comorbidities such as coagulopathy (OR 1.77, CI 1.09-2.88), fluid and electrolyte imbalance (OR 1.65, CI 1.05-2.60), prior CABG (OR 2.99, CI 1.19-7.47), need for mechanical ventilation (OR 2.18, CI 1.12-4.23) were significant predictors of all-cause mortality. In our analysis, chronic pulmonary disease, valvular heart disease, hypertension, smoking, obesity were not significant predictors. The result of our analysis is reported in Table 1.

Conclusion: These results suggest HFpEF remains important comorbidity in ARDS patients. Here, we identified predictors of poor outcomes in this patient population which may help physicians to identify the high-risk patients and decrease mortality.

Abstract 54: Significantly Higher Odds Of Mortality In Stroke-Related Admissions During COVID-19 Pandemic Versus Pre-COVID/Pandemic: A Meta-Analysis Of 455,073 Stroke Admissions

Background: COVID-19, being a prothrombotic state, has been linked to ischemic infarcts. Pooled data on impact of COVID-related stroke on mortality are sparse. We conducted a meta-analysis to assess the risk of stroke-related inpatient mortality (SRIM) during the COVID pandemic vs. pre-pandemic.

Methods: Pubmed/Medline, SCOPUS & EMBASE were searched for articles till August 2021 reporting stroke and SRIM during COVID-19 pandemic vs. pre-pandemic. Random-effects model for odds ratio (OR), I 2 statistics for heterogeneity assessment and leave-one-out method for sensitivity analysis were employed.

Results: A total of 31 studies with 455,073 stroke hospitalizations; 365253 pre-pandemic and 89820 pandemics (mean age 72 vs 70 yrs) were analyzed. With a comparable distribution of males, AF, and thrombolysis, the meta-analysis showed a nearly 40% higher risk of mortality during pandemic vs. pre-pandemic admissions (OR 1.42, 95%CI:1.06-1.92, p=0.018, I 2 =98.59). Further subgroup analysis showed a slightly higher risk of mortality in cohorts with mean age <70 years of age vs. ≥70 yrs [mean <70 years (n=11): OR:1.48, p=0.020 vs. ≥70 years (n=17): OR:1.27, p<0.001]. Cross-continental subgroup analysis revealed significantly higher mortality in Europe (n=14, OR:1.31, p<0.001) during pandemic vs. pre-pandemic, and non-significantly higher association in Asia (OR 1.13, p=0.57), USA (OR 1.59, p=0.23), Africa (OR 1.20, p=0.46) (Fig. 1). Subgroup analysis of 16 studies with n=100-1000 showed significantly higher OR (1.31) for SRIM during the pandemic vs. pre-pandemic, whereas studies with n<100 or >1000 did not show any significant difference. Sensitivity analysis showed overall and subgroup stability in OR.

Conclusions: This largest meta-analysis to date on the subject found that hospitalized stroke patients, elderly or non-elderly, had nearly 40% higher risk of mortality during the COVID pandemic vs. pre-COVID era across the globe, more significantly in Europe.

Abstract 139: Higher Frequency And Odds Of Recurrent/subsequent Stroke Admissions In Young (18-44 Years) Patients With Prior Stroke/transient Ischemic Attack With Versus Without Cannabis Use Disorder: A Nationwide Inpatient Analysis

Background: Cannabis use disorder (CUD) is more prevalent in the young population and cannabis use has been linked to an increased risk of first-time stroke or transient ischemic attack (TIA). Prevalence and risk of recurrent stroke in patients with prior stroke/TIA in cannabis users are not clearly established.

Methods: Using weighted data from the National Inpatient Sample (2015 October-2017 December) and pertinent ICD-10 codes, we identified hospitalizations among young (18-44 years) patients with prior history of stroke/TIA grouped into those with CUD+ and those without (CUD-). We compared the frequency (with disparities based on gender, race, hospital region and median household income) and odds of subsequent/recurrent stroke in young adults (18-44 years) with vs without cannabis use (CUD+ vs. CUD-) and prior history of stroke/TIA.

Results: Young adult hospitalizations with prior stroke/TIA were 4690 in the CUD+ arm, and 156700 in CUD- arm (median age 37 years in both cohorts). The CUD+ cohort often consisted of males (55.2% vs. 40.2%), African Americans (44.6% vs. 37.2%), and patients with higher rates of concomitant substance abuse, COPD, depression and psychoses, and a lower rate of cardiovascular comorbidities compared to the CUD- cohort (p<0.001) [Table 1a]. The CUD+ arm had considerably higher rate (6.9 vs 5.4%) [Table 1b] and adjusted odds (aOR 1.48, 95 CI 1.28-1.71, p<0.001) of recurrent stroke than CUD- arm [Table 1c] . On subgroup comparison, admission among male (7.7% vs. 5.9%), white (6.6% vs. 5.1%), African American (8.0% vs. 5.2%), and admissions in low household income quartile (7.7% vs. 5.5%) patients, Northeast (6.1% vs. 4.4%) and Southern (7.6% vs. 5.7%) region hospitals showed higher rates of recurrent stroke with CUD+ vs. CUD- (p<0.05).

Conclusion: The frequency and risk (~50% higher) of recurrent stroke were found to be significantly increased with disparities in subgroups among young adults with prior history of stroke/TIA and concomitant CUD.

Strongyloides Hyperinfection Causing Gastrointestinal Bleeding and Bacteremia in an Immunocompromised Patient

Strongyloidiasis is a parasitic infestation caused by Strongyloides stercoralis (S. stercoralis). Most cases are asymptomatic or mildly symptomatic with respiratory, gastrointestinal, or non-specific cutaneous symptoms. However, in immunocompromised patients, such as patients on chronic corticosteroids, malignancy, or human immunodeficiency virus (HIV) infection, hyperinfection syndrome can occur. The following is a case of Strongyloides hyperinfection in an individual taking prednisone for uveitis who developed upper gastrointestinal (GI) bleed and gram-negative bacteremia.

Extramedullary Multiple Myeloma with Hepatic Involvement

Hepatic involvement with space-occupying lesions seen in patients with multiple myeloma (MM) is a rare phenomenon. We present two cases of extramedullary multiple myeloma (EMM), with different presentations to highlight the diversity of clinical presentation. Clinically relevant hepatic involvement of myeloma is uncommon and can pose management problems. Hepatic involvement of EMM is indicative of a poor prognosis. Early recognition can help stage and prognosticate the disease.

Burst-suppression ratio underestimates absolute duration of electroencephalogram suppression compared with visual analysis of intraoperative electroencephalogram

Background

Machine-generated indices based on quantitative electroencephalography (EEG), such as the patient state index (PSI™) and burst-suppression ratio (BSR), are increasingly being used to monitor intraoperative depth of anaesthesia in the endeavour to improve postoperative neurological outcomes, such as postoperative delirium (POD). However, the accuracy of the BSR compared with direct visualization of the EEG trace with regard to the prediction of POD has not been evaluated previously.

Methods

Forty-one consecutive patients undergoing non-cardiac, non-intracranial surgery with general anaesthesia wore a SedLine ® monitor during surgery and were assessed after surgery for the presence of delirium with the Confusion Assessment Method. The intraoperative EEG was scanned for absolute minutes of EEG suppression and correlated with the incidence of POD. The BSR and PSI™ were compared between patients with and without POD.

Results

Visual analysis of the EEG by neurologists and the SedLine ® -generated BSR provided a significantly different distribution of estimated minutes of EEG suppression ( P =0.037). The Sedline ® system markedly underestimated the amount of EEG suppression. The number of minutes of suppression assessed by visual analysis of the EEG was significantly associated with POD ( P =0.039), whereas the minutes based on the BSR generated by SedLine ® were not associated with POD ( P =0.275).

Conclusions

Our findings suggest that SedLine ® (machine)-generated indices might underestimate the minutes of EEG suppression, thereby reducing the sensitivity for detecting patients at risk for POD. Thus, the monitoring of machine-generated BSR and PSI™ might benefit from the addition of a visual tracing of the EEG to achieve a more accurate and real-time guidance of anaesthesia depth monitoring and the ultimate goal, to reduce the risk of POD.