Case of Bilateral Atrial Myxomas in Carney Syndrome.

Carney complex is rare neoplastic disorder. Intracardiac myxoma presenting the most common non-cutaneous lesions in this complex. We are reporting a 31-year-old Saudi female known case of Carney complex presented with asymptomatic biatrial myxoma that was identified on routine transthoracic echocardiogram, and was successfully excised. However, these patients need a careful surveillance in order to detect any new masses and prevent their complications.

Advances Towards Automatic Detection and Classification of Parasites Microscopic Images Using Deep Convolutional Neural Network: Methods, Models and Research Directions.

In the developing world, parasites are responsible for causing several serious health problems, with relatively high infections in human beings. The traditional manual light microscopy process of parasite recognition remains the golden standard approach for the diagnosis of parasitic species, but this approach is time-consuming, highly tedious, and also difficult to maintain consistency but essential in parasitological classification for carrying out several experimental observations. Therefore, it is meaningful to apply deep learning to address these challenges. Convolution Neural Network and digital slide scanning show promising results that can revolutionize the clinical parasitology laboratory by automating the process of classification and detection of parasites. Image analysis using deep learning methods have the potential to achieve high efficiency and accuracy. For this review, we have conducted a thorough investigation in the field of image detection and classification of various parasites based on deep learning. Online databases and digital libraries such as ACM, IEEE, ScienceDirect, Springer, and Wiley Online Library were searched to identify sufficient related paper collections. After screening of 200 research papers, 70 of them met our filtering criteria, which became a part of this study. This paper presents a comprehensive review of existing parasite classification and detection methods and models in chronological order, from traditional machine learning based techniques to deep learning based techniques. In this review, we also demonstrate the summary of machine learning and deep learning methods along with dataset details, evaluation metrics, methods limitations, and future scope over the one decade. The majority of the technical publications from 2012 to the present have been examined and summarized. In addition, we have discussed the future directions and challenges of parasites classification and detection to help researchers in understanding the existing research gaps. Further, this review provides support to researchers who require an effective and comprehensive understanding of deep learning development techniques, research, and future trends in the field of parasites detection and classification.

Validation of Various Prediction Scores for Cardiac Surgery-Associated Acute Kidney Injury.

Background and objectives: Following cardiac surgery, acute kidney injury (AKI) is a well-known complication that increases morbidity and mortality. This study was carried out to determine the factors associated with acute kidney injury and to assess the predictive value of three predictive scores for the development of AKI post-cardiac surgery in the Saudi community. Methods: In this retrospective study, the medical records of patients aged 18 years and above who underwent cardiac surgery on cardiopulmonary bypass (CPB) at Saud Albabtin Cardiac Center between January 2018 and March 2021 were reviewed. The first stage of both Kidney Disease Improving Global Outcomes (KDIGO) criteria and the risk, injury, failure, loss, end-stage (RIFLE) criteria were used to define AKI. The predicting value for acute kidney injury following cardiac surgery (AKICS score) and Renal replacement therapy for acute kidney injury (RRT-AKI) (Cleveland score, and SRI) were evaluated by area under receiver operating characteristic curve (AUROC) for the discrimination and Hosmer-Lemeshow test for the calibration. Results: Among the 329 patients evaluated, the total postoperative incidence of acute kidney injury was 26.4%. Moreover, the incidence of RRT-AKI was 2.1%. Using multivariate logistic analysis, the factors independently associated with AKI were CABG on pump-beating heart, presence of chronic kidney disease, pre-operative anemia, prolonged bypass time, and post-operative exposure to inotropes or vasopressors. For the prediction of CSA-AKI, the discrimination of AKICS (AUROC = 0.689) was poor, while the calibration (x2 = 9.380, P = 0.311) was fair. For RRT-AKI prediction, the discrimination of Cleveland score (AUROC = 0.717) was fair while the discrimination of SRI (AUROC = 0. 681) was poor. On the other hand, the calibration for both of them was fair (Cleveland score x2 = 3.339, P = 0.342; SRI x2 = 7.326, P = 0.120). Conclusion: In this single-center study, SRI score demonstrated a reasonably good prediction of RRT-AKI incidence. However, further researches are required to investigate the perioperative factors in order to create a unique risk score model that may be used in a population with widespread comorbidities.