Eosinophilic and neutrophilic leukemoid reaction in a woman with spindle cell sarcoma: a case report

<p>Abstract</p> <p>Introduction</p> <p>We report a case of a patient with marked eosinophilia and neutrophilia as a manifestation of a spindle cell sarcoma.</p> <p>Case presentation</p> <p>A 41-year-old African American woman presented with an enlarging, painful mass in her right knee area. Four years previously, she had had a mass similar to this diagnosed as an osteosarcoma, and had undergone a radical resection and hinge-knee replacement. Before the surgery, she was treated with neoadjuvant docetaxel and gemcitabine. A biopsy was taken from the recurrent mass, and histological examination revealed high-grade soft-tissue sarcoma. The patient received no further treatment. Complete blood counts revealed a white blood cell (WBC) count of 13.6 to 17.9 × 10⁹/L, with neutrophils being 8.2 to 10.9 × 10⁹/L and eosinophils 1.8 to 1.9 × 10⁹/L. At readmission six months later, WBC was 126.7 × 10⁹/L, with neutrophils being 57.02 × 10⁹/L and eosinophils 60.82 × 10⁹/L. The eosinophils peaked at 77.79 × 10⁹/L two days later. Evaluations for allergies, infection, and autoimmune mechanisms were negative. Bone marrow revealed increased eosinophils without blasts. After resection, blood counts abruptly decreased to the normal range. Pathology confirmed high-grade spindle cell sarcoma. Approximately one year after resection, the patient was readmitted with metastatic disease to her lungs. During this presentation, her eosinophil and neutrophil count was again increased. WBC was 107.8 × 10⁹/L, with eosinophil count of 47.43 × 10⁹/L and neutrophil count of 44.10 × 10⁹/L. Interleukin-5 was normal, and granulocyte–macrophage colony-stimulating factor (GM-CSF) was elevated at 208.8 (normal < 4.8).</p> <p>Conclusion</p> <p>In our case, the patient had eosinophilia and neutrophilia associated with a spindle cell sarcoma, possibly representing a paraneoplastic syndrome secondary to GM-CSF. There were no signs of infectious, allergic, or autoimmune causes for the eosinophilia or neutrophilia. Even though the occurrence of eosinophilia and neutrophilia with malignancy is rare, patients who have either condition without an apparent cause should be checked for malignancy.</p

International longitudinal registry of patients with atrial fibrillation and treated with rivaroxaban: RIVaroxaban Evaluation in Real life setting (RIVER)

Background Real-world data on non-vitamin K oral anticoagulants (NOACs) are essential in determining whether evidence from randomised controlled clinical trials translate into meaningful clinical benefits for patients in everyday practice. RIVER (RIVaroxaban Evaluation in Real life setting) is an ongoing international, prospective registry of patients with newly diagnosed non-valvular atrial fibrillation (NVAF) and at least one investigator-determined risk factor for stroke who received rivaroxaban as an initial treatment for the prevention of thromboembolic stroke. The aim of this paper is to describe the design of the RIVER registry and baseline characteristics of patients with newly diagnosed NVAF who received rivaroxaban as an initial treatment. Methods and results Between January 2014 and June 2017, RIVER investigators recruited 5072 patients at 309 centres in 17 countries. The aim was to enroll consecutive patients at sites where rivaroxaban was already routinely prescribed for stroke prevention. Each patient is being followed up prospectively for a minimum of 2-years. The registry will capture data on the rate and nature of all thromboembolic events (stroke / systemic embolism), bleeding complications, all-cause mortality and other major cardiovascular events as they occur. Data quality is assured through a combination of remote electronic monitoring and onsite monitoring (including source data verification in 10% of cases). Patients were mostly enrolled by cardiologists (n = 3776, 74.6%), by internal medicine specialists 14.2% (n = 718) and by primary care/general practice physicians 8.2% (n = 417). The mean (SD) age of the population was 69.5 (11.0) years, 44.3% were women. Mean (SD) CHADS2 score was 1.9 (1.2) and CHA2DS2-VASc scores was 3.2 (1.6). Almost all patients (98.5%) were prescribed with once daily dose of rivaroxaban, most commonly 20 mg (76.5%) and 15 mg (20.0%) as their initial treatment; 17.9% of patients received concomitant antiplatelet therapy. Most patients enrolled in RIVER met the recommended threshold for AC therapy (86.6% for 2012 ESC Guidelines, and 79.8% of patients according to 2016 ESC Guidelines). Conclusions The RIVER prospective registry will expand our knowledge of how rivaroxaban is prescribed in everyday practice and whether evidence from clinical trials can be translated to the broader cross-section of patients in the real world

Alveolar Soft-Part Sarcoma Presenting with Eosinophilia and Shunt

Alveolar soft-part sarcoma (ASPS) is a rare soft tissue tumour found in young adults that usually arises in skeletal muscle and occurs most frequently in the lower limbs. Radiological and pathological findings of ASPS in a 34-year-old man who presented with increasing shortness of breath over a period of four to six weeks with peripheral blood eosinophilia, hypoxemia and a significant arteriovenous shunt are reported. The present article is the fourth report of eosinophilia in association with sarcoma, and the first involving ASPS

A deep facial recognition system using computational intelligent algorithms.

The development of biometric applications, such as facial recognition (FR), has recently become important in smart cities. Many scientists and engineers around the world have focused on establishing increasingly robust and accurate algorithms and methods for these types of systems and their applications in everyday life. FR is developing technology with multiple real-time applications. The goal of this paper is to develop a complete FR system using transfer learning in fog computing and cloud computing. The developed system uses deep convolutional neural networks (DCNN) because of the dominant representation; there are some conditions including occlusions, expressions, illuminations, and pose, which can affect the deep FR performance. DCNN is used to extract relevant facial features. These features allow us to compare faces between them in an efficient way. The system can be trained to recognize a set of people and to learn via an online method, by integrating the new people it processes and improving its predictions on the ones it already has. The proposed recognition method was tested with different three standard machine learning algorithms (Decision Tree (DT), K Nearest Neighbor(KNN), Support Vector Machine (SVM)). The proposed system has been evaluated using three datasets of face images (SDUMLA-HMT, 113, and CASIA) via performance metrics of accuracy, precision, sensitivity, specificity, and time. The experimental results show that the proposed method achieves superiority over other algorithms according to all parameters. The suggested algorithm results in higher accuracy (99.06%), higher precision (99.12%), higher recall (99.07%), and higher specificity (99.10%) than the comparison algorithms