Pulmonary artery sarcoma treated with pulmonary endarterectomy and leaflet reconstruction using Ozaki technique.

Pulmonary arterial intimal sarcomas (PAIS) are rare malignancies with a poor prognosis. Sarcomas present with signs and symptoms mimicking pulmonary thromboembolic disease, delaying the diagnosis. We present a 29-year-old male patient diagnosed with PAIS in the right and main pulmonary arteries extending to the left pulmonary leaflet. The patient was treated with pulmonary endarterectomy and pulmonary leaflet reconstruction using the Ozaki technique.

Deep learning models for predicting RNA degradation via dual crowdsourcing.

Medicines based on messenger RNA (mRNA) hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine learning competition ('Stanford OpenVaccine') on Kaggle, involving single-nucleotide resolution measurements on 6,043 diverse 102-130-nucleotide RNA constructs that were themselves solicited through crowdsourcing on the RNA design platform Eterna. The entire experiment was completed in less than 6 months, and 41% of nucleotide-level predictions from the winning model were within experimental error of the ground truth measurement. Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504-1,588 nucleotides) with improved accuracy compared with previously published models. These results indicate that such models can represent in-line hydrolysis with excellent accuracy, supporting their use for designing stabilized messenger RNAs. The integration of two crowdsourcing platforms, one for dataset creation and another for machine learning, may be fruitful for other urgent problems that demand scientific discovery on rapid timescales.

P Wave Dispersion in COVID-19

The effects of COVID-19 on the heart are still not fully known. In this study, we investigated how COVID-19 affects the P interval. Electrocardiographies (ECG) of 30 COVID-19 patients and the control group consisting of 23 healthy volunteers were examined and dispersion (Pd) of the P wave was calculated. Compared to control group mean Pd (40,1±6,6 vs. 49,6±11,5, p=0,006) values were significantly higher in Covid19 patients. Increased Pd was observed as an indication that COVID-19 affects the atriums. [ FROM AUTHOR] Copyright of Eastern Journal of Medicine is the property of Yuzuncu Yil University, Faculty of Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Elevated D-dimer levels on admission are associated with severity and increased risk of mortality in COVID-19: A systematic review and meta-analysis.

BACKGROUND: In this systematic review and meta-analysis, we aimed to investigate the correlation of D-dimer levels measured on admission with disease severity and the risk of death in patients with coronavirus disease 2019 (COVID-19) pneumonia. MATERIALS AND METHODS: We performed a comprehensive literature search from several databases. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in abstracting data and assessing validity. Quality assessment was performed using the Newcastle-Ottawa quality assessment scale (NOS). D-dimer levels were pooled and compared between severe/non-severe and surviving/non-surviving patient groups. Weighted mean difference (WMD), risk ratios (RRs) and 95% confidence intervals (CIs) were analyzed. RESULTS: Thirty-nine studies reported on D-dimer levels in 5750 non-severe and 2063 severe patients and 16 studies reported on D-dimer levels in 2783 surviving and 697 non-surviving cases. D-dimer levels were significantly higher in patients with severe clinical status (WMD: 0.45 mg/L, 95% CI: 0.34-0.56; p < 0.0001). Non-surviving patients had significantly higher D-dimer levels compared to surviving patients (WMD: 5.32 mg/L, 95% CI: 3.90-6.73; p < 0.0001). D-dimer levels above the upper limit of normal (ULN) was associated with higher risk of severity (RR: 1.58, 95% CI: 1.25-2.00; p < 0.0001) and mortality (RR: 1.82, 95% CI: 1.40-2.37; p < 0.0001). CONCLUSION: Increased levels of D-dimer levels measured on admission are significantly correlated with the severity of COVID-19 pneumonia and may predict mortality in hospitalized patients.

Prognostic significance of cardiac injury in COVID-19 patients with and without coronary artery disease.

OBJECTIVE: COVID-19 is a disease with high mortality, and risk factors for worse clinical outcome have not been well-defined yet. The aim of this study is to delineate the prognostic importance of presence of concomitant cardiac injury on admission in patients with COVID-19. METHODS: For this multi-center retrospective study, data of consecutive patients who were treated for COVID-19 between 20 March and 20 April 2020 were collected. Clinical characteristics, laboratory findings and outcomes data were obtained from electronic medical records. In-hospital clinical outcome was compared between patients with and without cardiac injury. RESULTS: A total of 607 hospitalized patients with COVID-19 were included in the study; the median age was 62.5 ± 14.3 years, and 334 (55%) were male. Cardiac injury was detected in 150 (24.7%) of patients included in the study. Mortality rate was higher in patients with cardiac injury (42% vs. 8%; P < 0.01). The frequency of patients who required ICU (72% vs. 19%), who developed acute kidney injury (14% vs. 1%) and acute respiratory distress syndrome (71%vs. 18%) were also higher in patients with cardiac injury. In multivariate analysis, age, coronary artery disease (CAD), elevated CRP levels, and presence of cardiac injury [odds ratio (OR) 10.58, 95% confidence interval (CI) 2.42-46.27; P < 0.001) were found to be independent predictors of mortality. In subgroup analysis, including patients free of history of CAD, presence of cardiac injury on admission also predicted mortality (OR 2.52, 95% CI 1.17-5.45; P = 0.018). CONCLUSION: Cardiac injury on admission is associated with worse clinical outcome and higher mortality risk in COVID-19 patients including patients free of previous CAD diagnosis.

Interpretation of arrhythmogenic effects of COVID-19 disease through ECG.

OBJECTIVE: We aimed to detect the malignant arrhythmic potential of COVID-19 with surface electrocardiographic (ECG) markers. MATERIAL AND METHOD: Of the ECG parameters PR, QT, QTc, QTd, TPe, and Tpe/QTc were measured in 51 COVID-19 patients and 40 in control subjects. RESULTS: Compared to control group mean QTc (410.8 ± 24.3 msec vs. 394.6 ± 20.3 msec, p < .001) and Tpe/QTc (0.19 ± 0.02 vs. 0.18 ± 0.04, p = .036) and median QTd (47.52 vs. 46.5) values were significantly higher in COVID-19 patients. Troponin levels were significantly correlated with heart rate (r = 0.387, p = .006) but not with ECG parameters. CONCLUSION: Several ventricular arrhythmia surface ECG predictors including QTc, QTd, and Tpe/QTc are increased in COVID-19 patients. Since medications used in COVID-19 patients have the potential to affect these parameters, giving importance to these ECG markers may have a significant contribution in decreasing disease-related arrhythmias.