Sex differences in heart transplantation - analysis of the national inpatient sample 2012-2019

INTRODUCTION

Advanced heart failure therapies and heart transplantation (HT) have been underutilized in women. Therefore, we aimed to explore the clinical characteristics and outcomes of HT by sex.

METHODS

We conducted a retrospective analysis of adult discharges from the National Inpatient Sample (NIS) between 2012 and 2019. International Classification of Disease (ICD) procedure codes were used to identify those who underwent HT.

RESULTS

A total of 20,180 HT hospitalizations were identified from 2012-2019. Among them, 28 % were female. Women undergoing HT were younger (mean age 51 vs. 54.5 years, p<0.001). HT hospitalizations among men were more likely to have atrial fibrillation, diabetes, hypertension, renal failure, dyslipidemia, smoking, and ischemic heart disease. HT hospitalizations among women were more likely to have hypothyroidism and valvular heart disease. HT hospitalizations in women were associated with no significant difference in risk of in-hospital mortality (adjusted odds ratio [OR] 0.82; 95 % confidence interval [CI] 0.58-1.16, p=0.271), no significant difference in length of stay or inflation-adjusted cost. Men were more likely to develop acute kidney injury during HT hospitalization (69.2 % vs. 59.7 %, adjusted OR 0.71, 95 % CI 0.61-0.83, p<0.001).

CONCLUSIONS

HT utilization is lower in women. However, most major in-hospital outcomes for HT are similar between the sexes. Further studies are need to explore the causes of lower rates of HT in women.

Percutaneous Correction of a Large Left Superior Vena Cava to Left Atrium Fistula

•Fistula between the PLSVC and the LA is a rare congenital condition. •Patients can present as adults with cerebrovascular accidents and dyspnea. •Percutaneous correction using a covered stent is feasible.

Severe Symptomatic Aortic Stenosis in an Octogenarian with Congenitally Corrected Transposition of the Great Arteries

•ccTGA accounts for 0.5%-1.4% of patients with congenital heart disease. •Patients with isolated ccTGA can remain undiagnosed for decades. •Very rarely, patients with ccTGA develop symptomatic AS. •Management of severe AS in patients with ccTGA presents unique challenges. •Transcatheter options are limited due to the unique anatomy.

A Rare Case of Uterine Blastomycosis and Its Management: A Case Report and Literature Review

The report delineates the rare occurrence of uterine blastomycosis, an atypical systemic presentation of Blastomyces dermatitidis infection prevalent in North America. Focused on a 51-year-old immunocompetent female displaying abdominal pain and irregular vaginal bleeding, it underscores the intricate diagnostic hurdles posed by symptoms mirroring common gynecological conditions. Despite fewer than 10 recorded cases, the rarity of uterine involvement highlights the imperative for heightened clinical suspicion. The multifaceted diagnostic strategy integrates risk factors, travel history, imaging, and histopathological examinations. Emphasizing a multidisciplinary treatment helmed by gynecologists, pathologists, and infectious disease specialists, the utilization of antifungal agents, notably itraconazole, is pivotal. Addressing the scarcity of literature and the condition's clinical resemblance to prevalent ailments, further research becomes paramount in devising tailored diagnostic and treatment protocols for uterine blastomycosis. This study enriches the existing literature by providing critical insights into a scarcely documented condition, contributing novel perspectives essential for clinical understanding and management strategies.

A Systematic Review of Artificial Intelligence Applications in the Management of Lung Disorders

This systematic review examines the transformative impact of artificial intelligence (AI) in managing lung disorders through a comprehensive analysis of articles spanning 2014 to 2023. Evaluating AI's multifaceted roles in radiological imaging, disease burden prediction, detection, diagnosis, and molecular mechanisms, this review presents a critical synthesis of key insights from select articles. The findings underscore AI's significant strides in bolstering diagnostic accuracy, interpreting radiological imaging, predicting disease burdens, and deepening the understanding of tuberculosis (TB), chronic obstructive pulmonary disease (COPD), silicosis, pneumoconiosis, and lung fibrosis. The synthesis positions AI as a revolutionary tool within the healthcare system, offering vital implications for healthcare workers, policymakers, and researchers in comprehending and leveraging AI's pivotal role in lung disease management.

Apical Hypertrophic Cardiomyopathy With a Sub-aortic Membrane: A Case Report

Hypertrophic obstructive cardiomyopathy (HOCM) and subaortic membrane (SAS) are distinct cardiac conditions, but their coexistence presents complex diagnostic challenges. We report the case of a 52-year-old male with HOCM and a concurrent subaortic membrane, highlighting the intricacies of diagnosis and management. The patient's presentation included symptoms of dyspnea and chest tightness, and diagnostic evaluations revealed a unique combination of dynamic left ventricular outflow tract (LVOT) obstruction from HOCM and fixed obstruction from the subaortic membrane. This case emphasizes the importance of a comprehensive diagnostic workup to guide appropriate treatment decisions when managing multiple cardiac abnormalities.

Long-Term Surveillance of Coronary Artery Dissection in an Orthotopic Heart Transplant Recipient

We describe a case of an orthotopic heart transplant recipient who presented with chest pain related to blunt chest trauma 3 weeks post-transplantation. Electrocardiogram showed anterior ST-segment elevation. Coronary angiography revealed a dissection of the mid-distal left anterior descending artery with preserved antegrade flow. Conservative management of the coronary artery dissection was pursued. While the patient had a favorable long-term clinical outcome, the coronary dissection persisted on 1- and 2-year follow-up coronary angiography.

Pathophysiology and Management of Heart Failure in the Elderly

The population of elderly adults is increasing globally. It has been projected that the population of adults aged 65 years will increase by approximately 80% by 2050 in the United States. Similarly, the elderly population is rising in other countries; a notable example being Japan where approximately 30% of the population are aged above 65 years. The pathophysiology and management of heart failure (HF) in this age group tend to have more intricacies than in younger age groups owing to the presence of multiple comorbidities. The normal aging biology includes progressive disruption at cellular and genetic levels and changes in molecular signaling and mechanical activities that contribute to myocardial abnormalities. Older adults with HF secondary to ischemic or valvular heart disease may benefit from surgical therapy, valve replacement or repair for valvular heart disease and coronary artery bypass grafting for coronary artery disease. While referring these patients for surgery, patient and family expectations and life expectations should be taken into account. In this review, we will cover the pathophysiology and the management of HF in the elderly, specifically discussing important geriatric domains such as frailty, cognitive impairment, delirium, polypharmacy, and multimorbidity.

High Prevalence of Cardiac Amyloidosis in Clinically Significant Aortic Stenosis: A Meta-Analysis

Background

There is growing evidence of coexistence of aortic stenosis (AS) and transthyretin cardiac amyloidosis (CA). Not screening AS patients at the time of hospital/clinic visit for CA represents a lost opportunity.

Methods

We surveyed studies that reported the prevalence of CA among AS patients. Studies that compared patients with aortic stenosis with cardiac amyloidosis (AS-CA) and AS alone were further analyzed, and meta-regression was performed.

Results

We identified nine studies with 1,321 patients of AS, of which 131 patients had concomitant CA, with a prevalence of 11%. When compared to AS-alone, the patients with AS-CA were older, more likely to be males, had higher prevalence of carpal tunnel syndrome, right bundle branch block. On echocardiogram, patients with AS-CA had thicker interventricular septum, higher left ventricular mass index (LVMI), lower myocardial contraction fraction, and lower stroke volume index. Classical low-flow low-gradient (LFLG) physiology was more common among patients with AS-CA. Patients with AS-CA had higher all-cause mortality than patients with AS alone (33% vs. 22%, P = 0.02) in a follow-up period of at least 1 year.

Conclusions

CA has a high prevalence in patients with AS and is associated with worse clinical, imaging, and biochemical parameters than patients with AS alone.

Natural language processing for identification of hypertrophic cardiomyopathy patients from cardiac magnetic resonance reports

Background

Cardiac magnetic resonance (CMR) imaging is important for diagnosis and risk stratification of hypertrophic cardiomyopathy (HCM) patients. However, collection of information from large numbers of CMR reports by manual review is time-consuming, error-prone and costly. Natural language processing (NLP) is an artificial intelligence method for automated extraction of information from narrative text including text in CMR reports in electronic health records (EHR). Our objective was to assess whether NLP can accurately extract diagnosis of HCM from CMR reports.

Methods

An NLP system with two tiers was developed for information extraction from narrative text in CMR reports; the first tier extracted information regarding HCM diagnosis while the second extracted categorical and numeric concepts for HCM classification. We randomly allocated 200 HCM patients with CMR reports from 2004 to 2018 into training (100 patients with 185 CMR reports) and testing sets (100 patients with 206 reports).

Results

NLP algorithms demonstrated very high performance compared to manual annotation. The algorithm to extract HCM diagnosis had accuracy of 0.99. The accuracy for categorical concepts included HCM morphologic subtype 0.99, systolic anterior motion of the mitral valve 0.96, mitral regurgitation 0.93, left ventricular (LV) obstruction 0.94, location of obstruction 0.92, apical pouch 0.98, LV delayed enhancement 0.93, left atrial enlargement 0.99 and right atrial enlargement 0.98. Accuracy for numeric concepts included maximal LV wall thickness 0.96, LV mass 0.99, LV mass index 0.98, LV ejection fraction 0.98 and right ventricular ejection fraction 0.99.

Conclusions

NLP identified and classified HCM from CMR narrative text reports with very high performance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-02017-y.

Outcomes of Heart Failure in COVID-19 Patients: An Appalachian Experience

Background

The Southeastern rural areas of the USA have a higher prevalence of heart failure (HF). Coronavirus disease 2019 (COVID-19) infection is associated with poor outcomes in patients with HF. Our study aimed to compare the outcomes of hospitalized HF patients with and without COVID-19 infection specifically in rural parts of the USA.

Methods

We conducted a retrospective cohort study of HF patients with and without COVID-19 hospitalized in Southeastern rural parts of the USA by using the Appalachian Regional Healthcare System. Analyses were stratified by waves from April 1, 2020 to May 31, 2021, and from June 1, 2021 to October 19, 2021.

Results

Of the 14,379 patients hospitalized with HF, 6% had concomitant COVID-19 infection. We found that HF patients with COVID-19 had higher mortality rate compared to those without COVID-19 (21.8% versus 3.8%, respectively, P < 0.01). Additionally, hospital resource utilization was significantly higher in HF patients with COVID-19 compared to HF patients without COVID-19 with intensive care unit (ICU) utilization of 21.6% versus 13.8%, P < 0.01, mechanical ventilation use of 17.3% versus 6.2%, P < 0.01, and vasopressor/inotrope use of 16.8% versus 7.9%, P < 0.01. A lower percentage of those with COVID-19 were discharged home compared to those without a COVID-19 diagnosis (63.4% versus 72.0%, respectively). There was a six-fold greater odds of dying in the first wave and seven-fold greater odds of dying in the second wave.

Conclusions

Our study confirms previous findings of poor outcome in HF patients with COVID-19. There is a need for review of healthcare resources in rural hospitals which already face numerous healthcare challenges.

Predictors of Mortality for Patients with COVID-19 in the Rural Appalachian Region

Background

The prevalence and outcome of coronavirus disease 2019 (COVID-19) in rural areas is unknown.

Methods

This is a multi-center retrospective cohort study of hospitalized patients diagnosed with COVID-19 from April 5, 2020 to December 31, 2020. The data were extracted from 13 facilities in the Appalachian Regional Healthcare system that share the same electronic health record using ICD-10-CM codes.

Results

The number of patients diagnosed with COVID-19 per facility ranged from 5 to 535 with a median of 106 patients. Total mortality was 11.4% and ranged from 0% to 22.6% by facility (median: 9.0%). Non-survivors had a greater prevalence of congestive heart failure (CHF), hypertension, type 2 diabetes mellitus, stroke, transient ischemic attack (TIA), and pulmonary embolism. Patients who died were also more likely to have had chronic obstructive pulmonary disease (COPD), acute respiratory failure (ARF), liver cirrhosis, chronic kidney disease (CKD), dementia, cancer, anemia, and opiate dependence.

Conclusion

The aging population, multiple co-morbidities, and health-related behaviors make rural patients vulnerable to COVID-19. A better understanding of the disease in rural areas is crucial, given its heightened vulnerability to adverse outcomes.

COVID-19 Infection and Late Manifestation of Pulmonary Aspergillosis

We present the case of a 56-year-old woman who was diagnosed with severe coronavirus disease 2019 (COVID-19) pneumonia complicated by severe acute respiratory distress syndrome who was intubated for 19 days. She recovered from COVID-19 after a month. A computed tomography (CT) scan of the chest, after a month, showed improved infiltrates with a small residual cavity within the lingula. A CT angiogram showed a more confluent density in the lingular portion on follow-up 2 months later. She developed intermittent hemoptysis after 3 months in December 2020, which persisted for almost 6 months, and CT of the chest showed the lingular nodular with resolution of the cavitation. She underwent bronchoscopy with bronchoalveolar lavage, confirming Aspergillus fumigatus by galactomannan assay and histology showing branching hyphae. Once she started treatment with itraconazole, her hemoptysis resolved. The follow-up CT of the chest after 2 months of treatment did not show a cavity or a nodule in the lingula. Our patient developed invasive pulmonary aspergillosis (IPA) as a sequela of severe COVID-19 infection. COVID-19-associated invasive pulmonary aspergillosis (CAPA) is an underrecognized complication that needs to be investigated on whether prophylactic treatment is required. Our case also demonstrates that the diagnosis of IPA needs to be considered months after COVID-19 infection when a superimposed fungal infection can occur after a viral infection if the patient continues to have persistent symptoms.

Refractory Torsades de Pointes Due to Dofetilide Overdose

Dofetilide, a class III antiarrhythmic, is widely used in the treatment of cardiac arrhythmias. Antiarrhythmic drugs can have a long duration of action that prolongs the QT interval. This causes bradycardia that predisposes to R-on-T phenomenon subsequently leading to torsades de pointes (TdP). This necessitates constant monitoring to prevent or treat ventricular arrhythmias or bradycardia associated with cardiac medications. Although extremely rare, dofetilide overdose has been described in the literature. However, no evidence found in the current literature required prolonged intervention after the initial acute stabilization, leading to scarcity of data for treatment of ongoing dofetilide overdose. We present the case of an intentional dofetilide overdose in a 61-year-old Caucasian woman with a history of congestive heart failure, atrial fibrillation, stage IIIb chronic kidney disease, diabetes mellitus type II, hypothyroidism, morbid obesity, and hypertension that required extensive interventions for refractory TdP that lasted 4 days. Therapeutic as well as excess dosage of dofetilide can lead to TdP, which is usually controlled by decreasing the dose or terminating drug administration. If the arrhythmia is not resolved, guidelines recommend management with activated charcoal if ingestion is within 15 minutes, followed by administration of 2 g IV (intravenous) magnesium and addressing the electrolyte imbalance. However, if the arrhythmia is persistent due to ongoing dofetilide toxicity, isoproterenol is given as a bridge to overdrive pacing and dopamine is used as an alternative to isoproterenol.

Natural language processing of implantable cardioverter-defibrillator reports in hypertrophic cardiomyopathy: A paradigm for longitudinal device follow-up

Background

The follow-up of implantable cardioverter-defibrillators (ICDs) generates large amounts of valuable structured and unstructured data embedded in device interrogation reports.

Objective

We aimed to build a natural language processing (NLP) model for automated capture of ICD-recorded events from device interrogation reports using a single-center cohort of patients with hypertrophic cardiomyopathy (HCM).

Methods

A total of 687 ICD interrogation reports from 247 HCM patients were included. Using a derivation set of 480 reports, we developed a rule-based NLP algorithm based on unstructured (free-text) data from the interpretation field of the ICD reports to identify sustained atrial and ventricular arrhythmias, and ICD therapies. A separate model based on structured numerical tabulated data was also developed. Both models were tested in a separate set of the 207 remaining ICD reports. Diagnostic performance was determined in reference to arrhythmia and ICD therapy annotations generated by expert manual review of the same reports.

Results

The NLP system achieved sensitivity 0.98 and 0.99, and F1-scores 0.98 and 0.92 for arrhythmia and ICD therapy events, respectively. In contrast, the performance of the structured data model was significantly lower with sensitivity 0.33 and 0.76, and F1-scores 0.45 and 0.78, for arrhythmia and ICD therapy events, respectively.

Conclusion

An automated NLP system can capture arrhythmia events and ICD therapies from unstructured device interrogation reports with high accuracy in HCM. These findings demonstrate the feasibility of an NLP paradigm for the extraction of data for clinical care and research from ICD reports embedded in the electronic health record.

A Rare Presentation of an Acute Type A Aortic Dissection Obscured Due to the Simultaneous Presence of Acute Pancreatitis

Introduction

Acute pancreatitis (AP) and acute aortic dissection (AAD) are medical emergencies that must be promptly recognized to avoid the development of life-threatening complications. Both of these diseases can present with chest or epigastric pain which can radiate to the back, thus, early suspicion based on clinical presentation and risk factors is essential. We present the case of a 56-year-old patient initially diagnosed with AP who was later found to have an AAD.

Clinical Findings

A 56-year-old man with a history of alcohol abuse presented with 1 day of diffuse abdominal pain, nausea and vomiting. His lipase was 3,909 U/L and creatinine was 2.19 mg/dL and he was diagnosed with acute alcoholic pancreatitis with acute kidney injury. A non-contrast computed tomography (NCCT) scan of the abdomen showed aortic calcifications. He received 3.8 liters of fluids after which he developed acute respiratory distress requiring intubation. A workup for extracorporeal membrane oxygenation (ECMO) was initiated, given the suspicion of acute respiratory distress syndrome (ARDS) due to pancreatitis. This revealed an AAD with severe aortic regurgitation on transthoracic echocardiography (TTE). CT angiogram showed type A AAD involving the aortic root, ascending aorta, descending aorta, suprarenal and infrarenal abdominal aorta. The celiac axis, superior mesenteric artery (SMA) and inferior mesenteric artery (IMA) were patent.

Outcomes

The patient underwent type A AAD repair with mechanical aortic valve replacement and survived the acute event. His AP resolved and he was discharged home with appropriate follow up.

Conclusion

We hypothesize that if our patient was not assessed for ECMO, the finding of AAD would have been a diagnostic challenge. AP secondary to AAD is rare but a high index of suspicion is required for diagnosis.

Usability of a Digital Registry to Promote Secondary Prevention for Peripheral Artery Disease Patients

Objective

To evaluate usability of a quality improvement tool that promotes guideline-based care for patients with peripheral arterial disease (PAD).

Patients and Methods

The study was conducted from July 19, 2018, to August 21, 2019. We compared the usability of a PAD cohort knowledge solution (CKS) with standard management supported by an electronic health record (EHR). Two scenarios were developed for usability evaluation; the first for the PAD-CKS while the second evaluated standard EHR workflow. Providers were asked to provide opinions about the PAD-CKS tool and to generate a System Usability Scale (SUS) score. Metrics analyzed included time required, number of mouse clicks, and number of keystrokes.

Results

Usability evaluations were completed by 11 providers. SUS for the PAD-CKS was excellent at 89.6. Time required to complete 21 tasks in the CKS was 4 minutes compared with 12 minutes for standard EHR workflow (median, P = .002). Completion of CKS tasks required 34 clicks compared with 148 clicks for the EHR (median, P = .002). Keystrokes for CKS task completion was 8 compared with 72 for EHR (median, P = .004). Providers indicated that overall they found the tool easy to use and the PAD mortality risk score useful.

Conclusions

Usability evaluation of the PAD-CKS tool demonstrated time savings, a high SUS score, and a reduction of mouse clicks and keystrokes for task completion compared to standard workflow using the EHR. Provider feedback regarding the strengths and weaknesses also created opportunities for iterative improvement of the PAD-CKS tool.

Conversion of left atrial volume to diameter for automated estimation of sudden cardiac death risk in hypertrophic cardiomyopathy

Background

A subset of patients with hypertrophic cardiomyopathy (HCM) is at high risk of sudden cardiac death (SCD). Practice guidelines endorse use of a risk calculator, which requires entry of left atrial (LA) diameter. However, American Society of Echocardiography (ASE) guidelines recommend the use of LA volume index (LAVI) for routine quantification of LA size. The aims of this study were to (a) develop a model to estimate LA diameter from LAVI and (b) evaluate whether substitution of measured LA diameter by estimated LA diameter derived from LAVI reclassifies HCM‐SCD risk.

Methods

The study cohort was comprised of 500 randomly selected HCM patients who underwent transthoracic echocardiography (TTE). LA diameter and LAVI were measured offline using digital clips from TTE. Linear regression models were developed to estimate LA diameter from LAVI. A European Society of Cardiology endorsed equation estimated SCD risk, which was measured using LA diameter and estimated LA diameter derived from LAVI.

Results

The mean LAVI was 48.5 ± 18.8 mL/m². The derived LA diameter was 45.1 mm (SD: 5.5 mm), similar to the measured LA diameter (45.1 mm, SD: 7.1 mm). Median SCD risk at 5 years estimated by measured LA diameter was 2.22% (interquartile range (IQR): 1.39, 3.56), while median risk calculated by estimated LA diameter was 2.18% (IQR: 1.44, 3.52). 476/500 (95%) patients maintained the same risk classification regardless of whether the measured or estimated LA diameter was used.

Conclusions

Substitution of measured LA diameter by estimated LA diameter in the HCM‐SCD calculator did not reclassify risk.

Cardiac Troponin-I and COVID-19: A Prognostic Tool for In-Hospital Mortality

BACKGROUND

The number of fatalities due to coronavirus disease 2019 (COVID-19) is escalating with more than 800,000 deaths globally. The scientific community remains in urgent need of prognostic tools to determine the probability of survival in patients with COVID-19 and to determine the need for hospitalization.

METHODS

This is a retrospective cohort study of patients with a diagnosis of COVID-19 admitted to a tertiary center between March 2020 and July 2020. Patients age 18 years and older were stratified into two groups based on their troponin-I level in the first 24 h of admission (groups: elevated vs. normal). The aim of the study is to explore the utility of cardiac troponin-I level for early prognostication of patients with COVID-19.

RESULTS

This cohort of 257 patients included 122/257 (47%) women with a mean age of 63 ± 17 years. Patients with an elevated troponin-I level were more likely to be older (77 ± 13 vs. 58 ± 16 years, P < 0.0001), have a history of hypertension (P < 0.0001), diabetes mellitus (P = 0.0019), atrial fibrillation or flutter (P = 0.0009), coronary artery disease (P < 0.0001), and chronic heart failure (P = 0.0011). Patients with an elevated troponin-I level in the first 24 h of admission were more likely to have higher in-hospital mortality (52% vs. 10%, P < 0.0001). Troponin-I level in the first 24 h of admission had a negative predictive value of 89.7% and a positive predictive value of 51.9% for all-cause in-hospital mortality.

CONCLUSIONS

Troponin-I elevation is commonly seen in patients with COVID-19 and is significantly associated with fatal outcomes. However, a normal troponin-I level in the first 24 h of admission had a high negative predictive value for all-cause in-hospital mortality, thereby predicting favorable survival at the time of discharge.

Extracting hypertrophic cardiomyopathy features from cardiac magnetic resonance reports by natural language processing

Objective

Determine if information regarding hypertrophic cardiomyopathy (HCM) can be accurately retrieved from cardiac magnetic resonance (CMR) reports using natural language processing (NLP).

Background

CMR imaging is used for diagnosis and risk stratification of HCM. Manual annotation of information from CMR is time-consuming. NLP is an artificial intelligence method for automating extraction of information from narrative text.

Methods

We identified 200 HCM patients who had CMR reports from 1998 to 2018. These patients were randomly allocated into training (100 patients with 185 CMR reports) and testing sets (100 patients with 206 reports). An NLP system with 2 tiers was developed; the first extracted information regarding HCM diagnosis while second extracted categorical or numeric concepts for HCM classification. NLP performance was compared with gold-standard manual annotation.

Results

NLP algorithms achieved very high performance across all concepts with mean positive predictive value (PPV) = 0.96. An outlier was the performance for abstracting the presence of an apical pouch from CMR reports, which had noticeably lower PPV= 0.78 which be attributed to the low number of cases with this finding.

Conclusions

The algorithms developed can be translated to clinical decision support systems to increase efficiency and contribute to improved quality of care.

Funding Acknowledgement

Type of funding source: Other. Main funding source(s): Study supported by the National Heart, Lung and Blood Institute of National Institutes of Health (K01HL124045), the Mayo Clinic Center for Clinical and Translational Science (CCaTS), and the Mayo Clinic K2R award. Content is solely the responsibility of authors and does not necessarily represent official views of the National Institutes of Health.