Adjunctive left atrial posterior wall isolation for atrial fibrillation: An updated systematic review and meta-analysis.

OBJECTIVE: Posterior left atrial wall isolation (PWI) plus traditional pulmonary vein isolation (PVI) has been proposed as a promising intervention to decrease atrial fibrillation (AF) recurrence. We aim to investigate the efficacy and safety of adding PWI to the traditional PVI in patients with AF. METHODS: A systematic review and meta-analysis was conducted using synthesizing randomized controlled trials (RCTs) retrieved by systematically searching PubMed, Web of Science, SCOPUS, EMBASE, and Cochrane through June 14, 2023. We used Stata version 17 to pool dichotomous data using risk ratio (RR) and continuous data using mean difference (MD), with a 95% confidence interval (CI) (PROSPERO ID: CRD42023446227). RESULTS: We included 11 RCTs with a total number of 1534 patients. Combined ablation with PWI + PVI was not associated with any significant difference over PVI only regarding the recurrence of clinical AF (RR: 0.86 with 95% CI [0.70-1.06]), all atrial arrhythmia (RR: 0.93 with 95% CI [0.82-1.07]), nonatrial fibrillation arrhythmia (RR: 1.22 with 95% CI [0.97-1.53]), early AF (RR: 0.89 with 95% CI [0.62-1.27]), and antiarrhythmic drugs at discharge (RR: 0.83 with 95% CI [0.67-1.04]). However, it was associated with increased total ablation duration (minutes) (MD: 12.58 with 95% CI [6.80-18.37]) and total procedure duration (minutes) (MD: 16.77 with 95% CI [9.63-23.91]), without any significant difference regarding adverse events (RR: 1.05 with 95% CI [0.63-1.74]). CONCLUSION: While the pooled data from PWI + PVI using point-by-point radiofrequency did not suggest a benefit in the recurrence of various atrial arrhythmias compared to PVI alone, PWI+PVI using direct posterior wall ablation, especially with cryoballoon, demonstrated a significant reduction in recurrence of AF/atrial arrhythmias. Also, PWI + PVI significantly increased the ablation and total procedure durations.

ArabBert-LSTM: improving Arabic sentiment analysis based on transformer model and Long Short-Term Memory.

Sentiment analysis also referred to as opinion mining, plays a significant role in automating the identification of negative, positive, or neutral sentiments expressed in textual data. The proliferation of social networks, review sites, and blogs has rendered these platforms valuable resources for mining opinions. Sentiment analysis finds applications in various domains and languages, including English and Arabic. However, Arabic presents unique challenges due to its complex morphology characterized by inflectional and derivation patterns. To effectively analyze sentiment in Arabic text, sentiment analysis techniques must account for this intricacy. This paper proposes a model designed using the transformer model and deep learning (DL) techniques. The word embedding is represented by Transformer-based Model for Arabic Language Understanding (ArabBert), and then passed to the AraBERT model. The output of AraBERT is subsequently fed into a Long Short-Term Memory (LSTM) model, followed by feedforward neural networks and an output layer. AraBERT is used to capture rich contextual information and LSTM to enhance sequence modeling and retain long-term dependencies within the text data. We compared the proposed model with machine learning (ML) algorithms and DL algorithms, as well as different vectorization techniques: term frequency-inverse document frequency (TF-IDF), ArabBert, Continuous Bag-of-Words (CBOW), and skipGrams using four Arabic benchmark datasets. Through extensive experimentation and evaluation of Arabic sentiment analysis datasets, we showcase the effectiveness of our approach. The results underscore significant improvements in sentiment analysis accuracy, highlighting the potential of leveraging transformer models for Arabic Sentiment Analysis. The outcomes of this research contribute to advancing Arabic sentiment analysis, enabling more accurate and reliable sentiment analysis in Arabic text. The findings reveal that the proposed framework exhibits exceptional performance in sentiment classification, achieving an impressive accuracy rate of over 97%.

Safety and feasibility of rotational atherectomy (RA) versus conventional stenting in patients with chronic total occlusion (CTO) lesions: a systematic review and meta-analysis.

BACKGROUND AND AIM: Interventional cardiologists face challenges in managing chronic total occlusion (CTO) lesions, with conflicting results when comparing rotational atherectomy (RA) to conventional PCI. This meta-analysis aims to provide a critical evaluation of the safety and feasibility of RA in CTO lesions. METHODS: PubMed, Scopus, Web of Science, Ovid, and Cochrane central library until April 2023 were searched for relevant studies. MACE was our primary outcomes, other outcomes were all cause of death, cardiac death, MI, and TVR. Also, we reported angiographic outcomes as technical success, procedural success, and procedural complications in a random effect model. The pooled data was analyzed using odds ratio (OR) with its 95% CI using STATA 17 MP. RESULTS: Seven studies comprising 5494 patients with a mean follow-up of 43.1 months were included in this meta-analysis. Our pooled analysis showed that RA was comparable to PCI to decrease the incidence of MACE (OR = 0.98, 95% CI [0.74 to 1.3], p = 0.9). Moreover, there was no significant difference between RA and conventional PCI in terms of other clinical or angiographic outcomes. CONCLUSION: Our study showed that RA had comparable clinical and angiographic outcomes as conventional PCI in CTO lesions, which offer interventional cardiologists an expanded perspective when addressing calcified lesions. PROSPERO REGISTRATION: CRD42023417362.

Rapid Grapevine Health Diagnosis Based on Digital Imaging and Deep Learning.

Deep learning plays a vital role in precise grapevine disease detection, yet practical applications for farmer assistance are scarce despite promising results. The objective of this research is to develop an intelligent approach, supported by user-friendly, open-source software named AI GrapeCare (Version 1, created by Osama Elsherbiny). This approach utilizes RGB imagery and hybrid deep networks for the detection and prevention of grapevine diseases. Exploring the optimal deep learning architecture involved combining convolutional neural networks (CNNs), long short-term memory (LSTM), deep neural networks (DNNs), and transfer learning networks (including VGG16, VGG19, ResNet50, and ResNet101V2). A gray level co-occurrence matrix (GLCM) was employed to measure the textural characteristics. The plant disease detection platform (PDD) created a dataset of real-life grape leaf images from vineyards to improve plant disease identification. A data augmentation technique was applied to address the issue of limited images. Subsequently, the augmented dataset was used to train the models and enhance their capability to accurately identify and classify plant diseases in real-world scenarios. The analyzed outcomes indicated that the combined CNNRGB-LSTMGLCM deep network, based on the VGG16 pretrained network and data augmentation, outperformed the separate deep network and nonaugmented version features. Its validation accuracy, classification precision, recall, and F-measure are all 96.6%, with a 93.4% intersection over union and a loss of 0.123. Furthermore, the software developed through the proposed approach holds great promise as a rapid tool for diagnosing grapevine diseases in less than one minute. The framework of the study shows potential for future expansion to include various types of trees. This capability can assist farmers in early detection of tree diseases, enabling them to implement preventive measures.

A comprehensive guide on the optimal timing of PCI in the setting of acute coronary syndrome: An updated meta-analysis.

BACKGROUND: Invasive revascularization is recommended for cohorts of patients with ST-elevation myocardial infarction (STEMI) and non-ST-elevation acute coronary syndrome (NSTE-ACS). However, the optimal timing of invasive revascularization is still controversial and no defined consensus is established. We aim to give a comprehensive appraisal on the optimal timing of invasive strategy in the heterogenous population of ACS. METHODS: Relevant studies were assessed through PubMed, Scopus, Web of science, and Cochrane Library from inception until April 2023. Major adverse cardiovascular events (MACE) and all-cause mortality were our primary outcomes of interest, other secondary outcomes were cardiac death, TVR, MI, repeat revascularization, recurrent ischemia, and major bleeding. The data was pooled as odds ratio (OR) with its 95% confidence interval (CI) in a random effect model using STATA 17 MP. RESULTS: A total of 26 studies comprising 21,443 patients were included in the analysis. Early intervention was favor to decrease all-cause mortality (OR = 0.79, 95% CI: 0.64 to 0.98, p = 0.03), when compared to delayed intervention. Subgroup analysis showed that early intervention was significantly associated with all-cause mortality reduction in only NSTE-ACS (OR = 0.83, 95% CI [0.7 to 0.99], p = 0.04). However, there was no significant difference between early and delayed intervention in terms of MACE, cardiac death, TVR, MI, repeat revascularization, recurrent ischemia, and major bleeding. CONCLUSION: An early intervention was associated with lower mortality rates compared to delayed intervention in NSTE-ACS with no significant difference in other clinical outcomes. PROSPERO registration: CRD42023415574.

Drug-coated balloons versus drug-eluting stents in patients with acute myocardial infarction undergoing percutaneous coronary intervention: an updated meta-analysis with trial sequential analysis.

BACKGROUND: Drug-coated balloons (DCBs) are an established strategy for coronary artery disease. However, the new generation drug-eluting stent (DES) is recommended for patients with Acute myocardial infarction (AMI) for coronary artery revascularization. Our aim is to provide a comprehensive appraisal of the efficacy of DCBs in patients with AMI undergoing PCI. METHODS: We searched the WOS, PubMed, Scopus, and Cochrane CENTRAL till March 2023, for studies that compared DCBs versus DES in patients with AMI undergoing PCI. We used a random-effects model to compare major adverse cardiac events (MACE), cardiac death, all-cause death, myocardial infarction, target lesion revascularization (TLR), stent thrombosis, Late lumen Loss (LLL), and minimum lumen diameter (MLD) between the two groups. RESULTS: Thirteen studies comprising 2644 patients were included. The pooled OR showed non-inferiority of DCB over DES in terms of MACE (OR = 0.89, 95% CI [0.57 to 1.40], p = 0.63). When we defined MACE as a composite of cardiac death, MI, and TLR; the pooled OR favored DCB over DES (OR = 0.50, 95% CI [0.28 to 0.9], p = 0.02). Moreover, DCB was not inferior to DES in terms of all-cause mortality (OR = 0.88, 95% CI: 0.43 to 1.8, p = 0.73), cardiac mortality, (OR = 0.59, 95% CI: 0.22 to 1.56, p = 0.29), MI (OR = 0.88, 95% CI: 0.34 to 2.29, p = 0.79), stent thrombosis (OR = 1.21, 95% CI: 0.35 to 4.23, p = 0.76), TLR (OR = 0.9, 95% CI: 0.43 to 1.93, p = 0.8), LLL (MD = -0.6, 95% CI: -0.3 to 0.19, p = 0.64), or MLD (MD = -0.4, 95% CI: -0.33 to 0.25, p = 0.76). CONCLUSION: Our meta-analysis indicated that DCB intervention was not inferior to DES in the PCI setting in patients with AMI, and can be recommended as a feasible strategy in AMI. PROSPERO REGISTRATION: CRD42023412757.

Short- and Long-term Outcomes of Percutaneous Coronary Interventions in Chronic and Non-chronic Total Occlusions: A Meta-analysis of 690,123 Patients.

The use of percutaneous coronary intervention (PCI) in patients with chronic total occlusion (CTO) is still a subject of debate, with conflicting outcomes reported in different studies when compared to non-CTO lesions. This meta-analysis aims to clarify the clinical outcomes of PCI in CTO cases compared to non-CTO lesions, both in the short and long-term. PubMed, Scopus, Web of Science, Ovid, and Cochrane Central were searched until March 2023 for relevant studies addressing short- and long-term outcomes of PCI in CTO vs non-CTO lesions. Dichotomous data were pooled as odds ratio (OR) with its 95% confidence interval (CI) in a random Der-Simonian lair effect model using STATA 17 MP. Eight studies with a total of 690,123 patients were included. In terms of short-term outcomes, CTO PCI was associated with higher rates of vessel perforation (OR = 2.16, 95% CI: 1.31-3.57) and cardiac tamponade (OR = 5.19, 95% CI: 4.29-6.28). Additionally, CTO PCI showed lower rates of procedural success (OR = 0.84, 95% CI: 0.73-0.96). Moreover, in the long-term, CTO PCI had higher rates of MACE (OR = 1.02, 95% CI: 1.01-1.04), however, it showed lower rates of cardiac death (OR = 0.61, 95% CI: 0.38-0.98), with no significant difference in other reported outcomes. Our findings underscore the challenges and adverse outcomes associated with using PCI to treat CTO lesions in the short term. This suggests that interventional cardiologists should carefully evaluate the risks and benefits before proceeding with PCI in CTO lesions.

Diabetic Retinopathy and Diabetic Macular Edema Detection Using Ensemble Based Convolutional Neural Networks.

Diabetic retinopathy (DR) and diabetic macular edema (DME) are forms of eye illness caused by diabetes that affects the blood vessels in the eyes, with the ground occupied by lesions of varied extent determining the disease burden. This is among the most common cause of visual impairment in the working population. Various factors have been discovered to play an important role in a person's growth of this condition. Among the essential elements at the top of the list are anxiety and long-term diabetes. If not detected early, this illness might result in permanent eyesight loss. The damage can be reduced or avoided if it is recognized ahead of time. Unfortunately, due to the time and arduous nature of the diagnosing process, it is harder to identify the prevalence of this condition. Skilled doctors manually review digital color images to look for damage produced by vascular anomalies, the most common complication of diabetic retinopathy. Even though this procedure is reasonably accurate, it is quite pricey. The delays highlight the necessity for diagnosis to be automated, which will have a considerable positive significant impact on the health sector. The use of AI in diagnosing the disease has yielded promising and dependable findings in recent years, which is the impetus for this publication. This article used ensemble convolutional neural network (ECNN) to diagnose DR and DME automatically, with accurate results of 99 percent. This result was achieved using preprocessing, blood vessel segmentation, feature extraction, and classification. For contrast enhancement, the Harris hawks optimization (HHO) technique is presented. Finally, the experiments were conducted for two kinds of datasets: IDRiR and Messidor for accuracy, precision, recall, F-score, computational time, and error rate.

Posterior pericardiotomy for the prevention of atrial fibrillation after cardiac surgery: a systematic review and meta-analysis of 25 randomised controlled trials.

BACKGROUND: Atrial fibrillation (AF) associated with postoperative pericardial effusion is the most commonly reported adverse event after cardiac surgery. AIMS: We aimed to determine the role of posterior pericardiotomy in preventing postoperative AF (POAF). METHODS: We searched PubMed, Scopus, Web of Science, Ovid, and EBSCO from inception until 30 June 2022. We included randomised clinical trials (RCTs) that compared posterior pericardiotomy (PP) versus control (no PP) in patients undergoing cardiac surgery. The primary endpoint was the incidence of POAF after cardiac surgery. The secondary endpoints were supraventricular arrhythmias, early/late pericardial effusion, pericardial tamponade, pleural effusion, length of hospital/intensive care unit stay, intra-aortic balloon pump use, revision surgery for bleeding, and mortality. RESULTS: Twenty-five RCTs comprising 4,467 patients were included in this systematic review and meta-analysis. The overall incidence rate of POAF was 11.7% in the PP group compared with 23.67% in the no PP or control group, with a significant decrease in the risk of POAF following PP (odds ratio [OR] 0.49, 95% confidence interval [CI]: 0.38-0.61). Compared with the control group, the risk of supraventricular tachycardia (OR 0.66, 95% CI: 0.43-0.89), early pericardial effusion (OR 0.32, 95% CI: 0.22-0.46), late pericardial effusion (OR 0.15, 95% CI: 0.09-0.25), and pericardiac tamponade (OR 0.18, 95% CI: 0.10-0.33) were lower in the PP group. CONCLUSIONS: PP is an effective intervention for reducing the risk of POAF after cardiac surgery. Also, PP is economically efficient in terms of decreasing the length of hospital stay.

Management of Atopic Dermatitis in Adults in Saudi Arabia: Consensus Recommendations from the Dermatological Expert Group.

Background: Atopic dermatitis (AD) is a long-term, pruritic, recurrent, systemic, inflammatory skin disorder. In the Middle East region, the burden of AD is understudied, and there is a dearth of AD guideline documents for practitioners. Methods: An expert panel meeting, encompassing 12 dermatologists from the Kingdom of Saudi Arabia (KSA), was congregated to develop evidence- and experience-based consensus recommendations for AD management, especially in adults in KSA. They completed a questionnaire with seven clinical statements, and a consensus was defined when the responses of ≥75% of participants coincided. Results: The expert recommendations were as follows: American Association of Dermatology guidelines are to be followed for defining AD; Eczema Area and Severity Index or SCORing atopic dermatitis index may be used to quantify the disease severity; Dermatology Life Quality Index may be used to determine the impact of AD on patients' quality of life; Atopic Dermatitis Control Tool may be used to assess long-term disease control in AD patients; and the European guidelines are to be followed for the management of AD. In AD patients who are inadequately controlled with topical or systemic therapies, the preferred systemic agent for use either alone or in combination with topical treatments is dupilumab, cyclosporine, methotrexate, phototherapy, or other available systemic treatments that may include mycophenolate mofetil or oral corticosteroids. Conclusion: These expert recommendations assist physicians by providing a reference framework for optimal care of adult AD patients.

Classification of Citrus Diseases Using Optimization Deep Learning Approach.

Most plant diseases have apparent signs, and today's recognized method is for an expert plant pathologist to identify the disease by looking at infected plant leaves using a microscope. The fact is that manually diagnosing diseases is time consuming and that the effectiveness of the diagnosis is related to the pathologist's talents, making this a great application area for computer-aided diagnostic systems. The proposed work describes an approach for detecting and classifying diseases in citrus plants using deep learning and image processing. The main cause of decreased productivity is considered to be plant diseases, which results in financial losses. Citrus is an important source of nutrients such as vitamin C all around the world. On the contrary, citrus diseases have a negative impact on the citrus fruit and quality. In the recent decade, computer vision and image processing techniques have become increasingly popular for the detection and classification of plant diseases. The suggested approach is evaluated on the citrus disease image gallery dataset and the combined dataset (citrus image datasets of infested scale and plant village). These datasets were used to identify and classify citrus diseases such as anthracnose, black spot, canker, scab, greening, and melanose. AlexNet and VGG19 are two kinds of convolutional neural networks that were used to build and test the proposed approach. The system's total performance reached 94% at its best. The proposed approach outperforms the existing methods.