Comparison of machine-learning models for the prediction of 1-year adverse outcomes of patients undergoing primary percutaneous coronary intervention for acute ST-elevation myocardial infarction.

BACKGROUND: Acute ST-elevation myocardial infarction (STEMI) is a leading cause of mortality and morbidity worldwide, and primary percutaneous coronary intervention (PCI) is the preferred treatment option. HYPOTHESIS: Machine learning (ML) models have the potential to predict adverse clinical outcomes in STEMI patients treated with primary PCI. However, the comparative performance of different ML models for this purpose is unclear. METHODS: This study used a retrospective registry-based design to recruit consecutive hospitalized patients diagnosed with acute STEMI and treated with primary PCI from 2011 to 2019, at Tehran Heart Center, Tehran, Iran. Four ML models, namely Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), Logistic Regression (LR), and Deep Learning (DL), were used to predict major adverse cardiovascular events (MACE) during 1-year follow-up. RESULTS: A total of 4514 patients (3498 men and 1016 women) were enrolled, with MACE occurring in 610 (13.5%) subjects during follow-up. The mean age of the population was 62.1 years, and the MACE group was significantly older than the non-MACE group (66.2 vs. 61.5 years, p < .001). The learning process utilized 70% (n = 3160) of the total population, and the remaining 30% (n = 1354) served as the testing data set. DRF and GBM models demonstrated the best performance in predicting MACE, with an area under the curve of 0.92 and 0.91, respectively. CONCLUSION: ML-based models, such as DRF and GBM, can effectively identify high-risk STEMI patients for adverse events during follow-up. These models can be useful for personalized treatment strategies, ultimately improving clinical outcomes and reducing the burden of disease.

Suboptimal Chest Radiography and Artificial Intelligence: The Problem and the Solution.

Chest radiographs (CXR) are the most performed imaging tests and rank high among the radiographic exams with suboptimal quality and high rejection rates. Suboptimal CXRs can cause delays in patient care and pitfalls in radiographic interpretation, given their ubiquitous use in the diagnosis and management of acute and chronic ailments. Suboptimal CXRs can also compound and lead to high inter-radiologist variations in CXR interpretation. While advances in radiography with transitions to computerized and digital radiography have reduced the prevalence of suboptimal exams, the problem persists. Advances in machine learning and artificial intelligence (AI), particularly in the radiographic acquisition, triage, and interpretation of CXRs, could offer a plausible solution for suboptimal CXRs. We review the literature on suboptimal CXRs and the potential use of AI to help reduce the prevalence of suboptimal CXRs.

Recurrent primary intracranial synovial sarcoma, a case report and review of the literature.

Synovial sarcoma (SS) occurs in various parts of the body, predominantly in the extremities. It also occurs in organs without synovial structures. The intracranial disease has been reported as metastasis, but primary intracranial SS has been reported rarely. We report a patient with hemiplegia and a mass on the brain CT. Pathology showed SS with no extracranial pathology.

Deep dorsal penile vein thrombosis in a patient with COVID-19 infection: A rare complication and the first reported case.

COVID-19 infection may have extrapulmunary manifestations such as blood hypercoagulability that may cause thrombosis in both arterial and venous system. Deep dorsal penile vein thrombosis is very rare, and the most common reason is coagulation disorders. The common observed symptom is penile pain especially during erection and it is diagnosed by ultrasound evaluation of the vein. It is necessary to distinguish deep dorsal penile vein thrombosis from superficial dorsal penile vein thrombosis as it needs anti-coagulant treatment. In present study, we describe a unique case of the deep dorsal penile vein thrombosis following COVID-19 infection.

A case report of a mammary myofibroblastoma in a male and literature review of radiologic and pathologic features of breast myofibroblastoma.

We reported a 65-year-old male with a benign mammary myofibroblastoma. This report shows that not all masses of male breast are malignant. To differentiate benign masses from malignant neoplasms, careful preoperative diagnosis should be performed. Preoperative diagnosis of the tumor prevents placing a huge financial and mental burdens on patients.

Quantitative diagnosis of osteoporosis using lumbar spine signal intensity in magnetic resonance imaging.

OBJECTIVE: Osteoporosis is the most common metabolic bone disease that is not recognized in many elderly people. To determine the cause of low back pain, lumbosacral MRI is done for a large population who may not have gone under dual energy X-ray absorptiometry (DXA). The aim of this study was to predict bone density using lumbar spine signals in lumbosacral MRI in high risk patients for osteoporosis including post-menopausal females and calculate a threshold for a new quantitative MRI-based score to be used in estimation of lumbar spine bone mass density. METHODS: 82 menopaused females, who had undergone DXA before, were selected and MRI was done within 6 months after DXA. 69 healthy females aged 20-29 years who had undergone lumbar MRI were selected as reference group. Results were analyzed and threshold and diagnostic performance of MRI-based score (M-score) on the method of T-score was calculated. RESULTS: Negative correlation between M-score and T-score was detected. Cut off point of 2.05 was found for M-score with near sensitivity of 90% and specificity of 87% for detecting osteoporotic patients from non-osteoporotic individuals. CONCLUSION: M-score is a MRI-based method which can identify patients at risk of osteoporosis. Early diagnosis of osteoporosis can reduce morbidity and mortality caused by it. ADVANCES IN KNOWLEDGE: The research introduced cut of points for M-score as a new MRI quantitative method to be used as an opportunistic technique for detecting osteoporotic patients.

Association of Matrix Metalloproteinase-2 and Matrix Metalloproteinase-9 With Endothelial Dysfunction, Cardiovascular Disease Risk Factors and thrombotic events in Children With End-stage Renal Disease.

INTRODUCTION: Cardiovascular disease (CVD) is the main cause of death in children with end-stage renal disease (ESRD). Matrix metalloproteinases (MMP-2 and MMP-9) are members of endopeptidases which contribute to CVD. The aim of this study was to evaluate the association of MMP-2 and MMP-9 with markers of endothelial dysfunction, soluble E-selectin and brachial flow-mediated dilatation; several biochemical risk factors of CVD; and thrombotic incidents in children with ESRD. MATERIALS AND METHODS: Thirty-one children with ESRD and 18 healthy age- and sex-adjusted controls underwent measurement of serum levels of MMP-2, MMP-9, soluble E-selectin, phosphorus, calcium, parathyroid hormone, lipid profile, thrombotic factors, and albumin. Flow-mediated dilatation was measured in both groups by Doppler ultrasonography. Thrombotic events were assessed in patients with ESRD. RESULTS: Matrix metalloproteinase-2 positively correlated with systolic and diastolic blood pressure, soluble E-selectin, creatinine, cholesterol, triglyceride, low-density lipoprotein cholesterol, phosphorus, and parathyroid hormone and negatively correlated with body mass index, hemoglobin, high-density lipoprotein cholesterol, and flow-mediated dilatation, while MMP-9 correlated with soluble E-selectin, phosphorus, parathyroid hormone, and albumin and negatively correlated with body mass index and hemoglobin. Six patients (19.3%) had thrombotic incidents. There was no significant difference between the levels of MMP-2 and MMP-9 in the children with and without thrombotic events. CONCLUSIONS: This study determined the associations of MMP-2 and MMP-9 with markers of endothelial dysfunction and several traditional and uremia related CVD risk factors in children with ESRD. No associations were found between these two MMPs and thrombotic events.