An enhanced drought forecasting in coastal arid regions using deep learning approach with evaporation index.

Coastal arid regions are similar to deserts, where it receives significantly less rainfall, less than 10 cm. Perhaps the world's worst natural disaster, coastal area droughts, can only be detected using reliable monitoring systems. Creating a reliable drought forecast model and figuring out how well various models can analyze drought factors in coastal arid regions are two of the biggest obstacles in this field. Different time-series methods and machine-learning models have traditionally been utilized in forecasting strategies. Deep learning is promising when describing the complex interplay between coastal drought and its contributing variables. Considering the possibility of enhancing our understanding of drought features, applying deep learning approaches has yet to be tried widely. The current investigation employs a deep learning strategy. Coastal Drought indices are commonly used to comprehend the situation better; hence the Standard Precipitation Evaporation Index (SPEI) was used since it incorporates temperatures and precipitation into its computation. An integrated coastal drought monitoring model was presented and validated using convolutional long short-term memory with self-attention (SA-CLSTM). The Climatic Research Unit (CRU) dataset, which spans 1901-2018, was mined for the drought index and predictor data. To learn how LSTM forecasting could enhance drought forecasting, we analyzed the findings regarding numerous drought parameters (drought severity, drought category, or geographic variation). The model's ability to predict drought intensity was assessed using the Coefficient of Determination (R2), the Root Mean Square Error (RMSE), and the Mean Absolute Error (MAE). Both the SPEI 1 and SPEI 3 examples had R2 values more than 0.99 for the model. The range of predicted outcomes for each drought group was analyzed using a multi-class Receiver Operating Characteristic based Area under Curves (ROC-AUC) method. The research showed that the AUC for SPEI 1 was 0.99 and for SPEI 3, 0.99. The study's results indicate progress over machine learning models for one month in advance, accounting for various drought conditions. This work's findings may be used to mitigate drought, and additional improvement can be achieved by testing other models.

Coastal Flood risk assessment using ensemble multi-criteria decision-making with machine learning approaches.

Coastal areas are at a higher risk of flooding, and novel changes in the climate are induced to raise the sea level. Flood acceleration and frequency have increased recently because of unplanned infrastructural conveniences and anthropogenic activities. Therefore, the assessment of flood susceptibility mapping is considered the most significant flood management model. In this paper, flood susceptibility identification is performed by applying the innovative Multi-criteria decision-making model (MCDM) called Analytical Hierarchy Process (AHP) by ensembles with Support vector machine (AHP-SVM) and Decision Tree (AHP-DT). This model combines two Representation concentration pathway (RCP) scenarios such as RCP 2.6 & RCP 8.5. The factors influencing the coastal flooding in Bandar Abbas, Iran, identified through Flood susceptibility mapping. Multi-criteria decision-making (MCDM) has been applied to evaluate the Coastal flood conditioning factors, and ensemble machine learning (ML) approaches are employed for Coastal risk factor (CRF) prediction and classification. The statistical variances are measured through Friedman and Wilcoxon signed rank tests and statistical metrics such as Accuracy, sensitivity, and specificity. Among the models, AHP-DT obtained an improved AUC value of ROC as 0.95. After applying the ML models, the northern and western park of Raidak Basin River recognises very low and low flood susceptibility because of their topographic characteristics. The eastern part of the middle section fell very high and high CFSM. Observed from this result analysis, the people living nearer to the coastline are distributed by the low to medium exposure in the region of the west and middle of the considered study area. The results of this study can help decision-makers take necessary risk reduction approaches in the high-risk flooding zones of the coastal system.

Cardiac monitoring in memory clinics: national survey of UK practice.

AIMS AND METHOD: People diagnosed with dementia are often started on acetylcholinesterase inhibitors (AChEIs). As AChEIs can be associated with cardiac side-effects, an electrocardiogram (ECG) is sometimes requested before treatment. Previous work has suggested there is little consensus as to when or how ECGs should be obtained. This can create inconsistent practice, with patient safety, economic and practical repercussions. We surveyed 305 UK memory clinic practitioners about prescribing practice. RESULTS: More than 84% of respondents completed a pulse and cardiac history before prescribing AChEIs. Opinion was divided as to who should fund and conduct ECGs. It was believed that obtaining an ECG causes patients inconvenience and delays treatment. Despite regularly interpreting ECGs, 76% of respondents did not update this clinical skill regularly. CLINICAL IMPLICATIONS: The variation in practice observed has service-level and patient implications and raises potential patient safety concerns. Implementing national guidelines or seeking novel ways of conducting cardiac monitoring could help standardise practice.

Awareness, Concerns, and Protection Strategies Against Blood-Borne Viruses Among Emergency Medicine Staff.

Objectives The present study aimed to evaluate the awareness and measures taken to prevent infections of blood-borne pathogens (BBPs) among emergency department (ED) staff at King Abdulaziz Medical City in Riyadh. Method A cross-sectional research approach was adopted. The study recruited a sample of 200 ED medical staff from King Abdul Aziz Medical City in Riyadh city. A self-filled questionnaire was used to elicit data related to awareness and concerns, in addition to the protection strategies adopted by the ED medical staff. The gathered data was analyzed using the Statistical Package of Social Sciences (SPSS, v. 26). Results The study found that 42.5% (n=85) of the emergency room (ER) staff did not use regular eyewear at all, 30% (n=60) did not use face shields at all, and about 75.5% of the enrolled ED staff successfully converted to double-gloving. In addition, it was found that patients with active AIDS (64%), patients with active hepatitis (60.5%), and patients with known HIV infection (60%) were the most reported factors influencing the decision to use double-gloving. Moreover, it was found that the highest reported reasons for not double-gloving were that double-gloving is not necessary (56%, n=112) and double-gloving decreases hand sensation (31%, n=62).Finally, the study found that the most reported reasons for not using barriers other than gloves precautions were non-necessity of barriers other than gloves (31% (n=62) and non-availability (26.5%, n=53). Conclusion The study concluded that ER medical staff in King Abdul-Aziz Medical City in Riyadh perceived a high level of lifetime risk of infection when performing procedures and that there is a lack of education and awareness of ER staff related to using personal protective equipment (PPE) and double-gloving when performing procedures in the ER.

Blood Demand and Challenges for Patients With Beta-Thalassemia Major in Eastern Saudi Arabia.

Background ß-thalassemia major is a hereditary disorder of hemoglobin (Hb) that results in defective Hb synthesis, leading to severe chronic anemia. The mainstay of its treatment is lifelong regular packed red cell transfusions associated with iron-chelating therapy. Globally, there is a gap between blood donation and the actual needs of the patients who depend on transfusion. Patients with ß-thalassemia major are no exception and have limited access to regular and safe blood transfusions. This study aimed to assess the gap between the demand and supply of blood for transfusion-dependent patients with ß-thalassemia major treated at the Hereditary Blood Diseases Center, Al Ahsa, Eastern Saudi Arabia. Methodology This was a retrospective, cross-sectional study conducted at the Hereditary Blood Disease Center, Al Ahsa, Saudi Arabia, including patient data from January 2017 to December 2019. We used Excel 365 from Microsoft Office 2016, version 1706. Results A total of 158 patients were on chronic transfusion. Of the total patients, 65% were adults, while the remaining 35% comprised the pediatric population. The total number of units requested and received during the three-year period was 14,509 and 9,530, respectively, indicating a gap of 4,979 (34%) units. The age of most of the units received was more than 14 days: 36% of those in 2017, 49.9% in 2018, and 61.5% in 2019. Rare blood groups and alloimmunization accounted for <8% of the patients. Prestorage filtration was the policy for all units. Conclusions There was a gap between the demand and supply of blood for patients with ß-thalassemia major treated at our center. We suggest raising awareness regarding the high demands for fresh red blood cell components in patients with thalassemia major, encouraging voluntary blood donations, enhancing national blood-banking policies, and reducing the fragmentation of blood services to reduce the gap between demand and supply.

Clinical validation and evaluation of a novel six-lead handheld electrocardiogram recorder compared to the 12-lead electrocardiogram in unselected cardiology patients (EVALECG Cardio).

Aims: Handheld electrocardiogram (ECG) monitors are increasingly used by both healthcare workers and patients to diagnose cardiac arrhythmias. There is a lack of studies validating the use of handheld devices against the standard 12-lead ECG. The Kardia 6L is a novel handheld ECG monitor which can produce a 6-lead ECG. In this study, we compare the 6L ECG against the 12-lead ECG. Methods and results: A prospective study consisting of unselected cardiac inpatients and outpatients at Leeds Teaching Hospital NHS Trust. All participants had a 12- and 6-lead ECGs. All ECG parameters were analysed by using a standard method template for consistency between independent observers. Electrocardiograms from the recorders were compared by the following statistical methods: linear regression, Bland-Altman, receiver operator curve, and kappa analysis. There were 1015 patients recruited. The mean differences between recorders were small for PR, QRS, cardiac axis, with receiver operator analysis area under the curve (AUC) of >80%. Mean differences for QT and QTc (between recorders) were also small, with AUCs for QT leads of >75% and AUCs for QTc leads of >60%. Key findings from Bland-Altman analysis demonstrate overall an acceptable agreement with few outliers instances (<6%, Bland-Altman analysis). Conclusion: Several parameters recorded by the Kardia 6L (QT interval in all six leads, rhythm detection, PR interval, QRS duration, and cardiac axis) perform closely to the gold standard 12-lead ECG. However, that consistency weakens for left ventricular hypertrophy, QRS amplitudes (Lead I and AVL), and ischaemic changes.

Prevalence and 20-year epidemiological trends of glomerular diseases in the adult Saudi population: a multicenter study.

BACKGROUND: Recent international reports have shown significant changes in the incidence of different glomerular diseases. OBJECTIVE: Examine temporal and demographic trends of biopsy-diagnosed glomerular diseases in the adult population of Saudi Arabia over the last two decades. DESIGN: Medical record review. SETTINGS: Four tertiary medical centers in Saudi Arabia. PATIENTS AND METHODS: We identified all patients that underwent native kidney biopsy between 1998 and 2017. MAIN OUTCOME MEASURES: The frequency and the disease trends in four biopsy eras (1998-2002, 2003-2007, 2008-2011, and 2012-2017) for different glomerular diseases. SAMPLE SIZE AND CHARACTERISTICS: 1070 patients, 18-65 years of age; 54.1% female. RESULTS: Of 1760 patients who underwent native kidney biopsies, 1070 met inclusion criteria. Focal segmental glomerulosclerosis was the most common biopsy-diagnosed disease, with comparable frequencies over the four eras (23.6%, 19.8%, 24.1%, and 17.1, respectively [ P value for trend=.07]). The frequency of immunoglobulin A nephropathy increased progressively. The incidence of membranoproliferative glomerulonephritis declined significantly. Among the secondary types of glomerular diseases, systemic lupus erythematosus-associated lupus nephritis was the most common, followed by diabetic nephropathy. The prevalence of diabetic nephropathy increased from 1.4% in the first era to 10.2% in the last one. CONCLUSIONS: Trends in biopsy-diagnosed glomerular disease have changed. While focal segmental glomerulosclerosis remains the most common glomerular disease, there has been a significant rise in the prevalence of immunoglobulin A nephropathy and diabetic nephropathy. In contrast, membranoproliferative glomerulonephritis has declined. LIMITATIONS: Retrospective methodologies are vulnerable to lost data. CONFLICT OF INTEREST: None.