Preparedness and Response Strategies for Chemical, Biological, Radiological, and Nuclear Incidents in the Middle East and North Africa: An Artificial Intelligence-Enhanced Delphi Approach.

OBJECTIVE: Chemical, biological, radiological, and nuclear (CBRN) incidents require meticulous preparedness, particularly in the Middle East and North Africa (MENA) region. This study evaluated CBRN response operational flowcharts, tabletop training scenarios methods, and a health sector preparedness assessment tool specific to the MENA region. METHODS: An online Delphi survey engaging international disaster medicine experts was conducted. Content validity indices (CVIs) were used to validate the items. Consensus metrics, including interquartile ranges (IQRs) and Kendall's W coefficient, were utilized to assess the panelists' agreement levels. Advanced artificial intelligence computing methods, including sentiment analysis and machine-learning methods (t-distributed stochastic neighbor embedding [t-SNE] and k-means), were used to cluster the consensus data. RESULTS: Forty experts participated in this study. The item-level CVIs for the CBRN response flowcharts, preparedness assessment tool, and tabletop scenarios were 0.96, 0.85, and 0.84, respectively, indicating strong content validity. Consensus analysis demonstrated an IQR of 0 for most items and a strong Kendall's W coefficient, indicating a high level of agreement among the panelists. The t-SNE and k-means identified four clusters with greater European response engagement. CONCLUSIONS: This study validated essential CBRN preparedness and response tools using broad expert consensus, demonstrating their applicability across different geographic areas.

Incidence, characteristics, and prehospital outcomes of out-of-hospital cardiac arrest in Qatar: a nationwide gender-based investigation.

BACKGROUND: Research on incidence and characteristics of Out-of-Hospital Cardiac Arrest (OHCA) in the Middle East is limited. We assessed the incidence, prehospital characteristics, and outcomes of OHCA in Qatar, a Middle Eastern country. Subsequently, we performed gender-specific analysis. METHODS: This was a retrospective examination of data obtained from the OHCA registry at Hamad Medical Corporation (HMC) in Qatar from 2017 to 2022. We included adults, non-traumatic, EMS-treatment OHCA. We calculated the incidence of adult OHCA and conducted descriptive analyses for prehospital characteristics, and prehospital outcomes presented by return of spontaneous circulation (ROSC). We evaluated gender differences in prehospital characteristics and ROSC using Student's t-test and the Chi-Square test as appropriate. Furthermore, we conducted a multivariable logistic regression analysis to investigate the correlation between gender and achieving ROSC. RESULTS: We included 4,306 adult OHCA patients, with 869 (20.2%) being females. The mean annual incidence of adult OHCA was 27.4 per 100,000 population-year. Males had a higher annual incidence of OHCA than females. Among all cases, 36.3% occurred in a public location, 25.8% had an initial shockable rhythm, and 28.8% achieved ROSC. Males had a higher proportion of bystander CPR, arrests in public locations, and initial shockable rhythms. While unadjusted analysis showed no significant gender differences in achieving ROSC, adjusted analysis revealed that male gender was associated with higher odds of achieving ROSC (adjusted OR male vs. female 1.38, 95% CI 1.15-1.66, p < 0.001). CONCLUSIONS: Approximately 720 adults undergo non-traumatic OHCA in Qatar every year, with a higher incidence observed in males. Male gender was associated with higher odds of achieving ROSC. Further gender-specific research in OHCA intervention and outcome in the Middle East is required.

Integrating Inter-Professional Insights for Enhanced Disaster Response: A Cross-Sectional Analysis in Jubail's Royal Commission Hospital, Saudi Arabia.

Introduction: This study aimed to evaluate disaster preparedness and management among an inter-professional team at the Royal Commission Hospital (RCH) in Jubail, Saudi Arabia. Methods: Conducted between May and July 2023, this cross-sectional study involved healthcare providers in both patient-facing and non-patient-facing roles. Participants responded to a comprehensive online questionnaire comprising 22 questions across seven sections covering aspects of emergency response, disaster management, and infection control. The study targeted a minimum sample size of 500 participants, successfully garnering responses from 512 individuals. Results: Of the 512 participants, 59.9% (n=312) were healthcare providers in patient-facing roles, and 40.1% (n=209) were in non-patient-facing roles. The results revealed notable disparities in awareness and preparedness between these two groups. Healthcare providers demonstrated higher awareness levels compared to their non-patient-facing counterparts. For instance, 76.9% of healthcare providers were aware of the hospital's emergency response plan compared to 56.2% of non-healthcare providers (χ² = 52.165, p < 0.001). Similar disparities were observed in understanding the term "disaster" (86.5% vs 54.1%, χ² = 27.931, p < 0.001), and awareness of a command center (73.4% vs 45.2%, χ² = 42.934, p < 0.001). Discussion: These findings underscore the critical need for enhancing awareness, education, and preparedness within healthcare facilities, emphasizing an integrated approach that includes both healthcare and non-healthcare staff. By addressing these gaps, healthcare facilities can significantly improve their emergency response efficiency, disaster management capabilities, and infection control measures, thereby enhancing the overall safety and quality of patient care.

Evaluation of the implementation of the objective structured clinical examination in health sciences education from a low-income context in Tunisia: A cross-sectional study.

Background: Objective structured clinical examination (OSCE) is well-established and designed to evaluate students' clinical competence and practical skills in a standardized and objective manner. While OSCEs are widespread in higher-income countries, their implementation in low-resource settings presents unique challenges that warrant further investigation. Aim: This study aims to evaluate the perception of the health sciences students and their educators regarding deploying OSCEs within the School of Health Sciences and Techniques of Sousse (SHSTS) in Tunisia and their efficacity in healthcare education compared to traditional practical examination methods. Methods: This cross-sectional study was conducted in June 2022, focusing on final-year Health Sciences students at the SHSTS in Tunisia. The study participants were students and their educators involved in the OSCEs from June 6th to June 11th, 2022. Anonymous paper-based 5-point Likert scale satisfaction surveys were distributed to the students and their educators, with a separate set of questions for each. Spearman, Mann-Whitney U and Krusakll-Wallis tests were utilized to test the differences in satisfaction with the OSCEs among the students and educators. The Wilcoxon Rank test was utilized to examine the differences in students' assessment scores in the OSCEs and the traditional practical examination methods. Results: The satisfaction scores were high among health sciences educators and above average for students, with means of 3.82 ± 1.29 and 3.15 ± 0.56, respectively. The bivariate and multivariate analyzes indicated a significant difference in the satisfaction between the students' specialities. Further, a significant difference in their assessment scores distribution in the practical examinations and OSCEs was also demonstrated, with better performance in the OSCEs. Conclusion: Our study provides evidence of the relatively high level of satisfaction with the OSCEs and better performance compared to the traditional practical examinations. These findings advocate for the efficacy of OSCEs in low-income countries and the need to sustain them.

Predictive modelling of transport decisions and resources optimisation in pre-hospital setting using machine learning techniques.

BACKGROUND: The global evolution of pre-hospital care systems faces dynamic challenges, particularly in multinational settings. Machine learning (ML) techniques enable the exploration of deeply embedded data patterns for improved patient care and resource optimisation. This study's objective was to accurately predict cases that necessitated transportation versus those that did not, using ML techniques, thereby facilitating efficient resource allocation. METHODS: ML algorithms were utilised to predict patient transport decisions in a Middle Eastern national pre-hospital emergency medical care provider. A comprehensive dataset comprising 93,712 emergency calls from the 999-call centre was analysed using R programming language. Demographic and clinical variables were incorporated to enhance predictive accuracy. Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost) algorithms were trained and validated. RESULTS: All the trained algorithm models, particularly XGBoost (Accuracy = 83.1%), correctly predicted patients' transportation decisions. Further, they indicated statistically significant patterns that could be leveraged for targeted resource deployment. Moreover, the specificity rates were high; 97.96% in RF and 95.39% in XGBoost, minimising the incidence of incorrectly identified "Transported" cases (False Positive). CONCLUSION: The study identified the transformative potential of ML algorithms in enhancing the quality of pre-hospital care in Qatar. The high predictive accuracy of the employed models suggested actionable avenues for day and time-specific resource planning and patient triaging, thereby having potential to contribute to pre-hospital quality, safety, and value improvement. These findings pave the way for more nuanced, data-driven quality improvement interventions with significant implications for future operational strategies.

Epidemiology of prehospital emergency calls according to patient transport decision in a middle eastern emergency care environment: Retrospective cohort-based.

Background and Aim: Though emergency medical services (EMS) respond to all types of emergency calls, they do not always result in the patient being transported to the hospital. This study aimed to explore the determinants influencing emergency call-response-based conveyance decisions in a Middle Eastern ambulance service. Methods: This retrospective quantitative analysis of 93,712 emergency calls to the Hamad Medical Corporation Ambulance Service (HMCAS) between January 1 and May 31, 2023, obtained from the HMCAS electronic system, was analyzed to determine pertinent variables. Sociodemographic, emergency dispatch-related, clinical, and miscellaneous predictors were analyzed. Descriptive, bivariate, ridge logistic regression, and combination analyses were evaluated. Results: 23.95% (N = 21,194) and 76.05% (N = 67,285) resulted in patient nontransport and transportation, respectively. Sociodemographic analysis revealed that males predominantly activated EMS resources, and 60% of males (n = 12,687) were not transported, whilst 65% of females (n = 44,053) were transported. South Asians represented a significant proportion of the transported patients (36%, n = 24,007). "Home" emerged as the primary emergency location (56%, n = 37,725). Bivariate analysis revealed significant associations across several variables, though multicollinearity was identified as a challenge. Ridge regression analysis underscored the role of certain predictors, such as missing provisional diagnoses, in transportation decisions. The upset plot shows that hypertension and diabetes mellitus were the most common combinations in both groups. Conclusions: This study highlights the nuanced complexities governing conveyance decisions. By unveiling patterns such as male predominance, which reflects Qatar's expatriate population, and specific temporal EMS activity peaks, this study accentuates the importance of holistic patient assessment that transcends medical histories.

Exploring factors influencing time from dispatch to unit availability according to the transport decision in the pre-hospital setting: an exploratory study.

BACKGROUND: Efficient resource distribution is important. Despite extensive research on response timings within ambulance services, nuances of time from unit dispatch to becoming available still need to be explored. This study aimed to identify the determinants of the duration between ambulance dispatch and readiness to respond to the next case according to the patients' transport decisions. METHODS: Time from ambulance dispatch to availability (TDA) analysis according to the patients' transport decision (Transport versus Non-Transport) was conducted using R-Studio™ for a data set of 93,712 emergency calls managed by a Middle Eastern ambulance service from January to May 2023. Log-transformed Hazard Ratios (HR) were examined across diverse parameters. A Cox regression model was utilised to determine the influence of variables on TDA. Kaplan-Meier curves discerned potential variances in the time elapsed for both cohorts based on demographics and clinical indicators. A competing risk analysis assessed the probabilities of distinct outcomes occurring. RESULTS: The median duration of elapsed TDA was 173 min for the transported patients and 73 min for those not transported. The HR unveiled Significant associations in various demographic variables. The Kaplan-Meier curves revealed variances in TDA across different nationalities and age categories. In the competing risk analysis, the 'Not Transported' group demonstrated a higher incidence of prolonged TDA than the 'Transported' group at specified time points. CONCLUSIONS: Exploring TDA offers a novel perspective on ambulance services' efficiency. Though promising, the findings necessitate further exploration across diverse settings, ensuring broader applicability. Future research should consider a comprehensive range of variables to fully harness the utility of this period as a metric for healthcare excellence.

Enhancing Patient Safety in Prehospital Environment: Analyzing Patient Perspectives on Non-Transport Decisions With Natural Language Processing and Machine Learning.

OBJECTIVE: This research explored the experiences and perspectives of patients declining hospital transportation after receiving prehospital emergency care using advanced computational techniques. METHOD: Between 15th June and 1st August 2023, 210 patients in Qatar, treated by Hamad Medical Corporation Ambulance Service (HMCAS) but refusing transportation to hospital, were interviewed. Key outcome variables stratified by demographics included "reasons for refusing transport," "satisfaction with HMCAS service," and "postrefusal actions." Responses underwent sentiment analysis and topic modeling using latent Dirichlet allocation. Machine learning models, such as Naïve Bayes, K-nearest neighboring, random forest, and support vector machine, were used to predict patients' subsequent actions. RESULTS: Participants had an average age of 38.61 ± 19.91 years. The chief complaints were primarily chest and abdominal pains (18.49%; n = 39). Sentiment Analysis revealed a generally favorable perception of HMCAS-provided service. Latent Dirichlet allocation identified two main topics pertaining to refusal reasons and service satisfaction. Naïve Bayes and support vector machine algorithms were most effective in predicting postrefusal actions with an accuracy rate of 81.58%. CONCLUSIONS: This study highlighted the utility of Natural Language Processing and ML in enhancing our understanding of patient behaviors and sentiments in prehospital settings. These advanced computational methodologies allowed for a nuanced exploration of patient demographics and sentiments, providing insights for Quality Improvement initiatives. The study also advocates for continuously integrating automated feedback mechanisms to improve patient-centered care in the prehospital context. Continuous integration of automated feedback systems is recommended to improve prehospital patient-centered care.

Perspectives on Preparedness for Chemical, Biological, Radiological, and Nuclear Threats in the Middle East and North Africa Region: Application of Artificial Intelligence Techniques.

Over the past 3 decades, the diversity of ethnic, religious, and political backgrounds worldwide, particularly in countries of the Middle East and North Africa (MENA), has led to an increase in the number of intercountry conflicts and terrorist attacks, sometimes involving chemical and biological agents. This warrants moving toward a collaborative approach to strengthening preparedness in the region. In disaster medicine, artificial intelligence techniques have been increasingly utilized to allow a thorough analysis by revealing unseen patterns. In this study, the authors used text mining and machine learning techniques to analyze open-ended feedback from multidisciplinary experts in disaster medicine regarding the MENA region's preparedness for chemical, biological, radiological, and nuclear (CBRN) risks. Open-ended feedback from 29 international experts in disaster medicine, selected based on their organizational roles and contributions to the academic field, was collected using a modified interview method between October and December 2022. Machine learning clustering algorithms, natural language processing, and sentiment analysis were used to analyze the data gathered using R language accessed through the RStudio environment. Findings revealed negative and fearful sentiments about a lack of accessibility to preparedness information, as well as positive sentiments toward CBRN preparedness concepts raised by the modified interview method. The artificial intelligence analysis techniques revealed a common consensus among experts about the importance of having accessible and effective plans and improved health sector preparedness in MENA, especially for potential chemical and biological incidents. Findings from this study can inform policymakers in the region to converge their efforts to build collaborative initiatives to strengthen CBRN preparedness capabilities in the healthcare sector.

Romidepsin Plus Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone Versus Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone in Patients With Previously Untreated Peripheral T-Cell Lymphoma: Final Analysis of the Ro-CHOP Trial.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.The primary analysis of the Ro-CHOP phase III randomized controlled trial (ClinicalTrials.gov identifier: NCT01796002) established that romidepsin (Ro) plus cyclophosphamide, doxorubicin, vincristine, prednisone (CHOP) did not yield an increased efficacy compared with CHOP alone as first-line treatment of peripheral T-cell lymphoma. We report the planned final analysis 5 years after the last patient enrolled. With a median follow-up of 6 years, median progression-free survival (PFS) was 12.0 months compared with 10.2 months (hazard ratio [HR], 0.79 [95% CI, 0.62 to 1.005]; P = .054), while median overall survival was 62.2 months (35.7-86.6 months) and 43.8 months (30.1-70.2 months; HR, 0.88 [95% CI, 0.68 to 1.14]; P = .324) in the Ro-CHOP and CHOP arms, respectively. In an exploratory analysis, the median PFS in the centrally reviewed follicular helper T-cell lymphoma subgroup was significantly longer in the Ro-CHOP arm (19.5 v 10.6 months, HR, 0.703 [95% CI, 0.502 to 0.985]; P = .039). Second-line treatments were given to 251 patients with a median PFS2 and OS2 after relapse or progression of 3.3 months and 11.5 months, respectively. Within the limits of highly heterogeneous second-line treatments, no specific regimen seemed to provide superior disease control. However, a potential benefit was observed with brentuximab vedotin in association with chemotherapy even after excluding anaplastic large-cell lymphoma subtype or after adjusting for histology and international prognostic index in a multivariate model (HR for PFS, 0.431 [95% CI, 0.238 to 0.779]; P = .005).

Understanding patient non-transport decision theories in the pre-hospital setting: a narrative review.

BACKGROUND: In pre-hospital emergency care, decisions regarding patient non-conveyance emerged as significant determinants of healthcare outcomes and resource utilization. These complex decisions became integral to the progress of emergency medical services, thus warranting an evolving exploration within the medical discourse. OBJECTIVES AND METHODS: This narrative review aimed to synthesize and critically evaluate various theoretical stances on patient non-conveyance in the pre-hospital emergency. The focus on studies published between January 2012 and August 2022 was intentional to capture contemporary practices and insights. PubMed and Google Scholar served as the primary databases for the investigation, while the AL-Rayyan® software facilitated a thorough screening process. RESULTS AND DISCUSSION: Twenty-nine studies-encompassing articles, books, and theses-were discovered through our search, each presenting unique perspectives on patient non-transport, thus highlighting its criticality as a healthcare concern. Predominant factors influencing non-transport decisions were classified into patient-initiated refusals (PIR), clinician-initiated decisions (CID), and dispatcher-initiated decisions (DID). CONCLUSIONS: The issue of patient non-conveyance to hospitals continues to pose a crucial challenge to the seamless operation of emergency healthcare systems, warranting increased attention from various healthcare entities. To comprehend and pinpoint potential areas of improvement, a comprehensive analysis of pre-hospital non-transport events is imperative. A well-informed, strategic approach could prevent resource waste while ensuring patients receive the required and definitive care. KEY MESSAGES: Why is this topic important? Some studies have suggested that non-transport to hospitals following emergency calls is safe. However, it is a concerning issue for health systems. It is also considered a key performance metric for health systems. What does this review attempt to show? This review aimed to map the various factors discussed in the literature regarding the decisions not to transport patients following emergency calls in a pre-hospital setting. What are the key findings? The existing theories regarding non-transport to hospitals after the provision of emergency care in the pre-hospital setting were identified. Non-transport due to non-clinical decisions jeopardizes emergency care outcomes for paediatric and elderly patients in particular. Hence, further research is required to identify and control the factors governing these decisions. How is patient care impacted? The decisions regarding patient transport following emergency calls in a pre-hospital setting are crucial for patient outcomes. They could impact the pre-hospital emergency care outcomes as well as patient safety. They can also affect the emergency services resources' ability to respond to other critical emergencies.

Provision of bystander CPR for out-of-hospital cardiac arrest in the Middle East: a retrospective gender-based analysis.

BACKGROUND: Previous studies conducted in North America, Europe, and East Asia (Liu et al., EClinicalMedicine 44:101293, 2022; Matsui et al., JAMA Netw Open 2:e195111, 2019; Awad et al., J Am Coll Emerg Physicians Open 4:e12957, 2023; Yoon et al., Prehosp Emerg Care :1-7, 2022) reported gender disparities in the provision of bystander CPR for patients with out-of-hospital cardiac arrest (OHCA). However, it remains unknown whether similar disparities exist in the Middle Eastern and Gulf regions. The primary objective of this study is to evaluate gender differences in the provision of bystander CPR for patients with OHCA in Qatar. METHODS: Retrospective analysis of data obtained from Hamad Medical Corporation OHCA registry in the State of Qatar (2016-2022). We included adults with non-traumatic and EMS-attended OHCA. We used multilevel logistic regression to examine the association between gender and provision of bystander CPR. RESULTS: In total, 4283 patients were included. Of those, 3414 (79.7%) were males, 1639 (38.3%) arrested in public locations, and 1463 (34.2%) received bystander CPR. Unadjusted comparisons showed that females were significantly older than males (mean age: 62.2 vs. 52.7). Females had a lower proportion of OHCA occurring in public locations (15.1% vs. 44.2%) and a lower proportion of shockable rhythm (11.9 vs. 27.5%). Regarding the outcome variable (provision of bystander CPR), the unadjusted analysis showed that the proportion of females who received bystander CPR was lower than that of males (29.2% vs. 35.4%, p < 0.001). However, after adjustment, we found no significant difference in provision of bystander CPR by gender (adjusted OR female vs. male 0.99, 95% CI 0.84-1.20, p = 0.97). In the subgroup who arrested in public locations, the analysis revealed females had greater odds of receiving bystander CPR (adjusted OR female vs. male 1.47, 95% CI 1.10-1.82, p = 0.04). CONCLUSIONS: Overall, bystander CPR was less common in female gender; after adjustment for other covariates, including arrest location, we found no significant gender differences in provision of bystander CPR. We also observed that females were found to have a lower incidence of cardiac arrest in public locations. Nevertheless, if females were to experience cardiac arrest in a public location, they would be more likely to receive CPR. Further research is required to explain the observed differences in provision of bystander CPR.

Epidemiological Determinants of Patient Non-Conveyance to the Hospital in an Emergency Medical Service Environment.

BACKGROUND: The increasing prevalence of comorbidities worldwide has spurred the need for time-effective pre-hospital emergency medical services (EMS). Some pre-hospital emergency calls requesting EMS result in patient non-conveyance. Decisions for non-conveyance are sometimes driven by the patient or the clinician, which may jeopardize the patients' healthcare outcomes. This study aimed to explore the distribution and determinants of patient non-conveyance to hospitals in a Middle Eastern national Ambulance Service that promotes the transportation of all emergency call patients and does not adopt clinician-based non-conveyance decision. METHODS: Using R Language, descriptive, bivariate, and binary logistic regression analyses were conducted for 334,392 multi-national patient non-conveyance emergency calls from June 2018 to July 2022, from a total of 1,030,228 calls to which a response unit was dispatched. RESULTS: After data pre-processing, 237,862 cases of patient non-conveyance to hospital were retained, with a monthly average of 41.96% (n = 8799) of the emergency service demands and a standard deviation of 5.49% (n = 2040.63). They predominantly involved South Asians (29.36%, n = 69,849); 64.50% (n = 153,427) were of the age category from 14 to 44 years; 61.22% (n = 145,610) were male; 74.59% (n = 177,424) from the urban setting; and 71.28% (n = 169,552) had received on-scene treatment. Binary logistic regression with full variables and backward methods identified the final models of the determinants of patient non-conveyance decisions with an Akaike information criterion prediction estimator, respectively, of (250,200) and (250,169), indicating no significant difference between both models (Chi-square test; p-value = 0.63). CONCLUSIONS: Despite exercising a cautious protocol by encouraging patient transportation to hospital, patient non-conveyance seems to be a problem in the healthcare system that strains the pre-hospital medical response teams' resources. Policies and regulations should be adopted to encourage individuals to access other primary care centers when required rather than draining emergency services for non-emergency situations.

Integrated machine learning-based model and WQI for groundwater quality assessment: ML, geospatial, and hydro-index approaches.

The demands upon the arid area for water supply pose threats to both the quantity and quality of social and economic activities. Thus, a widely used machine learning model, namely the support vector machines (SVM) integrated with water quality indices (WQI), was used to assess the groundwater quality. The predictive ability of the SVM model was assessed using a field dataset for groundwater from Abu-Sweir and Abu-Hammad, Ismalia, Egypt. Multiple water quality parameters were chosen as independent variables to build the model. The results revealed that the permissible and unsuitable class values range from 36 to 27%, 45 to 36%, and 68 to 15% for the WQI approach, SVM method and SVM-WQI model respectively. Besides, the SVM-WQI model shows a low percentage of the area for excellent class compared to the SVM model and WQI. The SVM model trained with all predictors with a mean square error (MSE) of 0.002 and 0.41; the models that had higher accuracy reached 0.88. Moreover, the study highlighted that SVM-WQI can be successfully implemented for the assessment of groundwater quality (0.90 accuracy). The resulting groundwater model in the study sites indicates that the groundwater is influenced by rock-water interaction and the effect of leaching and dissolution. Overall, the integrated ML model and WQI give an understanding of water quality assessment, which may be helpful in the future development of such areas.

Quality improvement tools to manage emergency callbacks from patients with diabetes in a prehospital setting.

Diabetes is rising at an alarming rate, as 1 in 10 adults worldwide now lives with the disease. In Qatar, a middle eastern Arab country, diabetes prevalence is equally concerning and is predicted to increase from 17% to 24% among individuals aged 45 and 54 years by 2050. While most healthcare strategies focus on preventative and improvement of in-hospital care of patients with diabetes, a notable paucity exists concerning diabetes in the prehospital setting should ideally be provided. This quality improvement study was conducted in a middle eastern ambulance service and aimed to reduce ambulance callbacks of patients with diabetes-related emergencies after refusing transport to the hospital at the first time. We used iterative four-stage problem-solving models. It focused on the education and training of both paramedics and patients. The study showed that while it was possible to reduce the rate of ambulance callbacks of patients with diabetes, this was short-lived and numbers increased again. The study demonstrated that improvements could be effective. Hence, changes that impacted policy, systems of care and ambulance protocols directed at managing and caring for patients with diabetes-related prehospital emergencies may be required to reify them.

Exploring pre-hospital healthcare workers' readiness for chemical, biological, radiological, and nuclear threats in the State of Qatar: A cross-sectional study.

Background: Hazardous Material-Chemical, Biological, Radiological, and Nuclear (HazMat-CBRN) incidents, though infrequent, are environmentally precarious and perilous to living beings. They can be deliberate or accidental or follow the re-emergence of highly contagious diseases. Successful management of such incidents in pre-hospital settings requires having well-trained and prepared healthcare workers. Aims: This study aimed to explore the reliability and validity of a satisfaction survey, answered by Specialized Emergency Management (SEM) personnel from a national Middle Eastern ambulance service, with a "Hazardous Material Incident Management" course offered to them as a continuing professional development activity and seek their opinion regarding Hamad Medical Corporation Ambulance Service personnel needs for other HazMat-CBRN related training topics. Method: In the cross-sectional study, we conducted an online satisfaction survey for this group of course participants to obtain their feedback as subject matter experts. Aiken's content validity coefficient (CVC) was calculated to assess the content validity. Cronbach's α coefficient was determined to explore the survey's reliability. IBM®-SPSS® version 26 was utilized to explore the data. Results: The SEM satisfaction survey demonstrated important satisfaction with the implemented training with its robust reliability and content validity (Cronbach's α = 0.922 and CVC = 0.952). The participants also recommended additional related topics. Conclusion: Sustaining and reinforcing the HazMat-CBRN Incident Management course was strongly recommended, considering the increase of HazMat-CBRN threats worldwide.

Spatial Distribution, Contamination Levels, and Health Risk Assessment of Potentially Toxic Elements in Household Dust in Cairo City, Egypt.

Urban areas' pollution, which is owing to rapid urbanization and industrialization, is one of the most critical issues in densely populated cities such as Cairo. The concentrations and the spatial distribution of fourteen potentially toxic elements (PTEs) in household dust were investigated in Cairo City, Egypt. PTE exposure and human health risk were assessed using the USEPA's exposure model and guidelines. The levels of As, Cd, Cr, Cu, Hg, Mo, Ni, Pb, and Zn surpassed the background values. Contamination factor index revealed that contamination levels are in the sequence Cd > Hg > Zn > Pb > Cu > As > Mo > Ni > Cr > Co > V > Mn > Fe > Al. The degree of contamination ranges from considerably to very high pollution. Elevated PTE concentrations in Cairo's household dust may be due to heavy traffic emissions and industrial activities. The calculated noncarcinogenic risk for adults falls within the safe limit, while those for children exceed that limit in some sites. Cairo residents are at cancer risk owing to prolonged exposure to the indoor dust in their homes. A quick and targeted plan must be implemented to mitigate these risks.

Hybrid-based Bayesian algorithm and hydrologic indices for flash flood vulnerability assessment in coastal regions: machine learning, risk prediction, and environmental impact.

Natural hazards and severe weather events are a matter of serious threat to humans, economic activities, and the environment. Flash floods are one of the extremely devastating natural events around the world. Consequently, the prediction and precise assessment of flash flood-prone areas are mandatory for any flood mitigation strategy. In this study, a new hybrid approach of machine learning (ML) algorithm and hydrologic indices opted to detect impacted and highly vulnerable areas. The obtained models were trained and validated using a total of 189 locations from Wadi Ghoweiba and surrounding area (case study). Various controlling factors including varied datasets such as stream transport index (STI), stream power index (SPI), lithological units, topographic wetness index (TWI), slope angle, stream density (SD), curvature, and slope aspect (SA) were utilized via hyper-parameter optimization setting to enhance the performance of the proposed model prediction. The hybrid machine learning (HML) model, developed by combining naïve Bayes (NïB) approach and hydrologic indices, was successfully implemented and utilized to investigate flash flood risk, sediment accumulation, and erosion predictions in the studied site. The synthesized new hybrid model demonstrated a model accuracy of 90.8% compared to 87.7% of NïB model, confirming the superior performance of the obtained model. Furthermore, the proposed model can be successfully employed in large-scale prediction applications.

Feasibility of a virtual reality-based exercise intervention and low-cost motion tracking method for estimation of motor proficiency in youth with autism spectrum disorder.

BACKGROUND: Motor impairment is widely acknowledged as a core feature in children with autism spectrum disorder (ASD), which can affect adaptive behavior and increase severity of symptoms. Low-cost motion capture and virtual reality (VR) game technologies hold a great deal of promise for providing personalized approaches to motor intervention in ASD. The present study explored the feasibility, acceptability and potential efficacy of a custom-designed VR game-based intervention (GaitWayXR™) for improving gross motor skills in youth with ASD. METHODS: Ten children and adolescents (10-17 years) completed six, 20-min VR-based motor training sessions over 2 weeks while whole-body movement was tracked with a low-cost motion capture system. We developed a methodology for using motion tracking data to quantify whole-body movement in terms of efficiency, synchrony and symmetry. We then studied the relationships of the above quantities with standardized measures of motor skill and cognitive flexibility. RESULTS: Our results supported our presumption that the VR intervention is safe, with no adverse events and very few minor to moderate side-effects, while a large proportion of parents said they would use the VR game at home, the most prohibitive reasons for adopting the system for home therapy were cost and space. Although there was little evidence of any benefits of the GaitWayXR™ intervention in improving gross motor skills, we showed several positive correlations between the standardized measures of gross motor skills in ASD and our measures of efficiency, symmetry and synchrony from low-cost motion capture. CONCLUSIONS: These findings, though preliminary and limited by small sample size, suggest that low-cost motion capture of children with ASD is feasible with movement exercises in a VR-based game environment. Based on these preliminary findings, we recommend conducting larger-scale studies with methods for improving adherence to VR gaming interventions over longer periods.