Outcomes of transctheter mitral valve repair in a large urban US health system

Background

Transcatheter mitral valve repair (TMVR) has become an important minimally invasive alternative to open surgical repair in patients with severe mitral regurgitation. As TMVR develops as an established practice, real-world outcome data is needed to guide clinical decision making as the body of literature on this topic is limited. In our study, we investigate TMVR outcomes in a large urban health system.

Methods

We retrospectively analyzed clinical data from the electronic health records of the extensive urban health system Mount Sinai Data Warehouse and analyzed all individuals who underwent TMVR. Baseline demographics were obtained as well as significant morbidity and mortality outcomes. Finally, multivariable analysis was used to determine associated characteristics with mortality.

Results

We identified 3533 patients who underwent TMVR from 2008 to 2018. The overall mortality was 3.7%. The most common comorbidities observed were heart failure (56%), pulmonary hypertension (26%), atrial fibrillation (26%) and CKD or ESRD (16%). After multivariable analyses, ischemic stroke (adjusted OR 3.46; 95% CI 1.93–5.97, p = <0.001), CKD or ESRD (3.95; 2.72–5.75, p 0.01), aortic stenosis (2.23; 1.12–4.15, p<0.001), and heart failure (8.18; 4.16–18.5, p<0.001) were independently associated with mortality.

Conclusion

In all patients who underwent TMVR at a large urban health system, ischemic stroke, aortic stenosis, heart failure, CKD and ESRD were independently associated with mortality. Future prospective studies will be needed to further define these observed associations.

Funding Acknowledgement

Type of funding sources: None.

A genome-wide association study identifies novel genetic loci associated with pulmonary embolism

Background

Pulmonary embolism (PE) is a life-threatening cardiovascular condition. Studies showed that PE patients were associated with disorders of lipid metabolism and had higher triglyceride and lower HDL-C levels compared with healthy. We conducted the genome-wide association study to identify novel loci contributing to PE.

Methods

We conducted a large-scale GWAS of PE in 5,466 PE cases and 461,219 controls of European ancestry from the UK Biobank (466,685 participants total). We used genome-wide summary statistics to test for enrichment of functional annotations using ENRICHR. Example pathways included in Enrichr for testing include membership of genes in pathway databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG), Wikipathway, PANTHER, BioCarta or NCI-Nature pathways. We analyzed the pathways using combined score and p-values which were well validated by comparing to several methods. For pathway analyses, we considered a nominal P-value threshold of 0.05.

Results

We identified genome-wide significant genetic associations in 63 independent genetic loci for PE (P<5.0x10–7). Our findings for top pathways highlight that lipid metabolism (LIPC, LCAT, NPC2), caffeine metabolism (NAT2), and sudden cardiac death (ABCG8) related genetic loci play an important role in PE alongside genes already associated with coagulation-thrombosis pathway (VWF, THPO, PTPN11, INPP5D, UROS, HMBS) (all p-values p-values <0.05).

Conclusion

Our findings uncovered unexpected novel factors of PE etiology, suggesting novel mechanistic concepts of PE pathophysiology.

Funding Acknowledgement

Type of funding source: None

Gender differences in spontaneous coronary artery dissection: a nationwide analysis

Background

Spontaneous coronary artery dissection (SCAD) is a very rare cause of acute coronary syndromes in young otherwise healthy patients with a striking predilection for the female gender. Unfortunately, SCAD can result in significant morbidities and mortality. The pathological mechanism has not been fully clarified yet but hormonal changes might represent a sufficiently convincing explanation for some patients with SCAD. We hypothesized that gender difference in mortality in SCAD patients.

Methods

Data for this retrospective cohort study were extracted from the Nationwide Inpatient Sample for 2014 using the 9th revision of the International Classification of Diseases (ICD) 414.12 (spontaneous coronary artery dissection). Demographics, in-hospital mortality, conventional risk factors (diabetes, hypertension, hyperlipidemia, alcohol and tobacco abuse), acute critical illnesses like sepsis, septic shock, stroke, acute respiratory insufficiency, acute renal failure, and chronic conditions (anxiety, depression, malignancy and metastatic diseases) were studied. Univariate and multivariate logistic regression modeling were performed to determine predictors associated with the development of inpatient mortality in SCAD patients. All analyses were conducted using R 3.4.0 and STATA/MP 14.2. All p-values were two-sided, and statistical significance was determined at the level of p<0.05.

Result

A total of 270 SCAD patients were identified. Of those SCAD patients, no fibromuscular dysplasia (FMD) or pregnancy were identified. Patients were predominantly women (71%) and the mean age was 53 years. Overall in-hospital mortality was 5.6%, with 6.6% in male and 5.3% in female. Ethnicity, gender, stroke, acute renal failure, anxiety and depression did not predict mortality, length of stay, annual income, total hospital charge (all p>0.05). Multivariate analysis revealed no gender difference in SCAD patients and no independent predictors of mortality were identified.

Conclusions

This large nationwide study reveals that SCAD may be underdiagnosed but underutilization of work up such as FMD. SCAD is thought to be hormone related likely associated with female gender. Our results showed that no gender difference in mortality. Further large prospective studies are needed to determine gender difference in mortality and other predictors in mortality.

Funding Acknowledgement

Type of funding source: None

LncRNA MALAT1 knockdown alleviates myocardial apoptosis in rats with myocardial ischemia-reperfusion through activating PI3K/AKT signaling pathway

OBJECTIVE

To observe the effect of long non-coding ribonucleic acid metastasis-associated lung adenocarcinoma transcript 1 (lncRNA MALAT1) on the myocardial ischemia-reperfusion (I/R) injury in rats and to explore its potential mechanism, to provide certain references for clinical prevention and treatment of myocardial I/R injury.

MATERIALS AND METHODS

A total of 60 male Wistar rats were randomly divided into the Control group (n=20), I/R group (n=20) and I/R + MALAT1 small-interfering RNA (siRNA) group (n=20) using a random number table. The I/R model was established through recanalization after ligation of left anterior descending coronary artery (LAD), and the MALAT1 knockdown model was established via tail intravenous injection of MALAT1 siRNA in the I/R + MALAT1 siRNA group. The ejection fraction (EF%) and fractional shortening (FS%) of rats in each group were detected via echocardiography and the infarction area in each group was detected using 2,3,5-triphenyl tetrazolium chloride (TTC) assay. Moreover, the morphological changes in myocardial cells in each group were detected via hematoxylin-eosin (H&E) staining, and the myocardial apoptosis level was detected via terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) staining. At the same time, the expression levels of the anti-apoptotic protein B-cell lymphoma-2 (Bcl-2) and pro-apoptotic protein Bcl-2 associated X protein (Bax) in myocardial tissues in each group were determined via Western blotting. Finally, the effect of MALAT1 knockdown on the phosphatidylinositol 3-hydroxy kinase/protein kinase B (PI3K/AKT) protein expression was detected via Western blotting.

RESULTS

The expression level of lncRNA MALAT1 in myocardial tissues was significantly higher in the I/R group than that in the Control group (p<0.05). The MALAT1 knockdown could significantly improve the cardiac insufficiency caused by I/R injury, and increase both EF% and FS% in rats (p<0.05). In addition, the MALAT1 knockdown could markedly inhibit myocardial infarction caused by I/R injury and reduce the infarction area from (62.12 ± 1.29) to (27.66 ± 3.58; p<0.05). The results of the H&E staining showed that the myofilaments were arranged more orderly, the degrees of degradation and necrosis were lower and the cellular edema was significantly alleviated in the I/R + MALAT1 siRNA group compared with those in the I/R group. According to the results of TUNEL staining, the rats in I/R + MALAT1 siRNA group had a markedly lower level of myocardial apoptosis than the I/R group (p<0.05), and the Bax/Bcl-2 ratio also remarkably declined in the I/R + MALAT1 siRNA group (p<0.05). Furthermore, the results of Western blotting revealed that MALAT1 siRNA could significantly reverse the I/R injury-induced inhibition on the AKT phosphorylation (p<0.05).

CONCLUSIONS

The MALAT1 knockdown can markedly improve the I/R-induced myocardial injury and promote the cardiac function of rats, whose mechanism may be related to the activation of the AKT signaling pathway by MALAT1 siRNA. Therefore, lncRNA MALAT1 is expected to be a new therapeutic target for myocardial I/R injury.

P1577Incidence, etiologies and predictors of 30-day readmission after percutaneous coronary intervention in end-stage renal disease patients; Analysis from national readmission database

Background

End stage renal disease (ESRD) is a known risk factor for coronary artery disease (CAD). The association of ESRD with short-term readmissions after percutaneous coronary intervention (PCI) has not been well studied.

Purpose

This study aims to examine he 30-day readmission rate, predictors of readmission and etiologies of readmission in ESRD patients after PCI.

Methods and results

The Healthcare Cost and Utilization Project National Readmission Database encompassing 722 US hospitals was used to identify index PCI cases in ESRD patients ≥18 years old. Hierarchical regression analyses were used to examine the factors associated with risk of 30-day readmission and higher cumulative costs.

Results

We evaluated 96,869 hospitalized patients who survived to discharge after PCI from January through November 2014 and analyzed unplanned readmissions over 30 days after discharge. A total of 11,624 patients (12%) were readmitted within 30 days. Among the readmitted patients, majority of readmissions were due to non-cardiac causes. Nineteen percent had congestive heart failure (HF), 11% had PCI, 2% had coronary artery bypass surgery, and 1.5% died during the readmission. Acute respiratory failure (21%) and infections (14%) compromised majority of non-cardiac causes. Predictors of increased readmissions were female sex (odds ratio (OR) 1.09, 95% confidence interval (CI) 1.01- 1.0, p<0.001), infections (OR 2.06, 95% CI 1.44–2.4, p<0.001), diabetes (OR 1.91, 95% CI 1.07–2.63, P<0.001), chronic lung disease (OR 3.16, 95% CI 2.11–4.2, p<0.001), chronic liver disease (OR 1.96, 95% CI 1.1–2.23, p<0.001), acute HF (OR 1.17, 95% CI 1.12–1.22, p<0.001) and anemia (OR 1.09, 95% CI 1.06–1.13, p<0.001).

Conclusion

ESRD patients are at high risk of 30-day readmissions after PCI. Although majority of patients are readmitted with non-cardiac causes, HF and repeat PCI were the most common cardiac etiologies of readmissions. Female sex, infections, chronic liver and lung diseases are independently associated with high risk of 30-day readmission in ESRD patients after PCI.

Acknowledgement/Funding

None

The rise of artificial intelligence and the uncertain future for physicians

Physicians in everyday clinical practice are under pressure to innovate faster than ever because of the rapid, exponential growth in healthcare data. "Big data" refers to extremely large data sets that cannot be analyzed or interpreted using traditional data processing methods. In fact, big data itself is meaningless, but processing it offers the promise of unlocking novel insights and accelerating breakthroughs in medicine-which in turn has the potential to transform current clinical practice. Physicians can analyze big data, but at present it requires a large amount of time and sophisticated analytic tools such as supercomputers. However, the rise of artificial intelligence (AI) in the era of big data could assist physicians in shortening processing times and improving the quality of patient care in clinical practice. This editorial provides a glimpse at the potential uses of AI technology in clinical practice and considers the possibility of AI replacing physicians, perhaps altogether. Physicians diagnose diseases based on personal medical histories, individual biomarkers, simple scores (e.g., CURB-65, MELD), and their physical examinations of individual patients. In contrast, AI can diagnose diseases based on a complex algorithm using hundreds of biomarkers, imaging results from millions of patients, aggregated published clinical research from PubMed, and thousands of physician's notes from electronic health records (EHRs). While AI could assist physicians in many ways, it is unlikely to replace physicians in the foreseeable future. Let us look at the emerging uses of AI in medicine.