Perception and clinical practice regarding mucus clearance devices with chronic obstructive pulmonary disease: a cross-sectional study of healthcare providers in Saudi Arabia

OBJECTIVES: Clearing secretions from the airway can be difficult for people with chronic obstructive pulmonary disease (COPD). Mucus clearance devices (MCDs) are an option in disease management to help with this, but healthcare provider awareness and knowledge about them as well as current clinical practice in Saudi Arabia are not known. DESIGN: A cross-sectional online survey consisting of four themes; demographics, awareness, recommendations and clinical practice, for MCDs with COPD patients. SETTING: Saudi Arabia. PARTICIPANTS: 1188 healthcare providers including general practitioners, family physicians, pulmonologists, nursing staff, respiratory therapists and physiotherapists. PRIMARY OUTCOME MEASURES: Healthcare providers' level of awareness about MCDs, and the identification of current clinical practices of COPD care in Saudi Arabia. RESULTS: 1188 healthcare providers (44.4% female) completed the survey. Regarding devices, 54.2% were aware of the Flutter, 23.8% the Acapella and 5.4% the positive expiratory pressure mask. 40.7% of the respondents identified the Acapella, and 22.3% the Flutter as first choice for COPD management. 75% would usually or always consider their use in COPD patients reporting daily difficulty clearing mucus, whereas 55.9% would sometimes or usually consider the use of MCDs with COPD patients who produced and were able to clear mucus with cough. In clinical practice, 380 (32%) of the respondents would prescribe MCDs, 378 (31.8%) would give MCDs without prescriptions, 314 (26.4%) would not provide them at all and 116 (9.8%) would only advise patients about them. CONCLUSION: Healthcare providers are aware of the existence of MCDs and their benefits for sputum clearance and believe that MCDs are beneficial for sputum clearance in some COPD patients. TRIAL REGISTRATION NUMBER: ISRCTN44651852

SPARC 2018 Internationalisation and collaboration : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2018 SPARC conference. This year we not only celebrate the work of our PGRs but also the launch of our Doctoral School, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 100 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

Cross-border movement, economic development and malaria elimination in the Kingdom of Saudi Arabia

Malaria at international borders presents particular challenges with regards to elimination. International borders share common malaria ecologies, yet neighboring countries are often at different stages of the control-to-elimination pathway. Herein, we present a case study on malaria, and its control, at the border between Saudi Arabia and Yemen. Malaria program activity reports, case data, and ancillary information have been assembled from national health information systems, archives, and other related sources. Information was analyzed as a semi-quantitative time series, between 2000 and 2017, to provide a plausibility framework to understand the possible contributions of factors related to control activities, conflict, economic development, migration, and climate. The malaria recession in the Yemeni border regions of Saudi Arabia is a likely consequence of multiple, coincidental factors, including scaled elimination activities, cross-border vector control, periods of low rainfall, and economic development. The temporal alignment of many of these factors suggests that economic development may have changed the receptivity to the extent that it mitigated against surges in vulnerability posed by imported malaria from its endemic neighbor Yemen. In many border areas of the world, malaria is likely to be sustained through a complex congruence of factors, including poverty, conflict, and migration

Exploring Barriers in Self-Reporting of Errors and Near Misses: A Cross-Sectional Study on Radiation Oncology in Saudi Arabia

Haitham Alahmad,1 Abdulrhman M Alshahrani,2 Khaled Alenazi,1 Mohammad Alarifi,1 Ahmad Abanomy,1 Ahmad A Alhulail,3 Raed A Albathi,4 Saleh Alzughaibi,5 Mansour Almanaa1 1Department of Radiological Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, 4545, Saudi Arabia; 2Radiology Technology Department, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia; 3Department of Radiology and Medical Imaging, Prince Sattam Bin Abdulaziz University, Al-Kharj, 16278, Saudi Arabia; 4Radiology Department, Prince Sultan Military Medical City, Riyadh, Saudi Arabia; 5Health Informatics Department, College of Health Science, Saudi Electronic University, Riyadh, Saudi ArabiaCorrespondence: Haitham Alahmad, Department of Radiological Sciences, College of Applied Medical Sciences, King Saud University, P.O. Box 145111, Riyadh, 4545, Saudi Arabia, Tel +966114693567, Email [email protected]: Radiation therapy utilizes complex technologies to target tumors. Radiation therapy is not immune to human errors. Reporting medical errors and near misses is crucial to improving patient outcomes and ensuring the safety of future patients.Objective: This study aimed to measure the attitudes of radiotherapy staff members in Saudi Arabia regarding reporting errors and near misses in radiation therapy practice. It also examined the participants’ reporting patterns and behaviors and explored the potential barriers to reporting errors and near misses as perceived by the participants.Methods: A cross-sectional study utilizing an online questionnaire was implemented. A sample of 70 health professionals working in radiation oncology departments in Saudi Arabia, including radiation oncologists, medical physicists, and radiotherapists, were recruited to participate in this study from January to June 2023. The data was analyzed using chi-squared testing to compare different groups, and the Kruskal–Wallis was used to find any statistically significant differences between different groups.Results: The study included 70 radiotherapy staff members. Professional roles did not significantly impact participants’ decisions to report minor or major errors, with most consistently reporting errors to their supervisors regardless of role. The study revealed that fear of professional sanctions and the potential negative impact on a department’s reputation are significant barriers to reporting errors or near misses. However, Only 17% of radiation oncologists did consider departmental sanctions as a barrier. Participants identified communication failure as the most significant source of errors in radiation oncology departments. The study also found a high level of agreement among the participants regarding the responsibility of reporting errors and near misses.Conclusion: The study investigated reporting errors and near misses in radiotherapy and considered the factors influencing them. The findings highlight the importance of effective communication and the implementation of an electronic reporting system.Keywords: radiotherapy, radiation oncology, medical errors, near misse

A Study of the Effect of Treatment on the Clinical Profile, Pain, and Disability in Migraine Patients Seen in a Tertiary Hospital [Response to Letter]

Geetha Kandasamy,1 Dalia Almaghaslah,1 Mona Almanasef,1 Tahani Musleh Almeleebia,1 Khalid Orayj,1 Ayesha Siddiqua,1 Eman Shorog,1 Asma M Alshahrani,1 Kousalya Prabahar,2 Vinoth Prabhu Veeramani,2 Palanisamy Amirthalingam,2 Saleh Alqifari,2 Naif Alshahrani,3 Aram Hamad AlSaedi,4 Alhanouf A Alsaab,5 Fatimah Aljohani,6 M Yasmin Begum,7 Akhtar Atiya8 1Department of Clinical Pharmacy, College of Pharmacy, King Khalid University, Abha, Kingdom of Saudi Arabia; 2Department of Pharmacy Practice, Faculty of Pharmacy, University of Tabuk, Tabuk, Kingdom of Saudi Arabia; 3Department of Pharmacy, Ad Diriyah Hospital, Ministry of Health (MOH), Riyadh, 13717, Kingdom of Saudi Arabia; 4College of Medicine, Taibah University, Al Madinah Al Munawwarah, Saudi Arabia; 5Pharmacist at Abha International Private Hospital, Abha, Saudi Arabia; 6Pharmacist at Prince Sultan Armed Forces Hospital, Almadenah Almonwarah, Saudi Arabia; 7Department of Pharmaceutics, College of Pharmacy, King Khalid University, Abha, Kingdom of Saudi Arabia; 8Department of Pharmacognosy, College of Pharmacy, King Khalid University, Abha, Kingdom of Saudi ArabiaCorrespondence: Geetha Kandasamy, Department of Clinical Pharmacy, College of Pharmacy, King Khalid University, Abha, Kingdom of Saudi Arabia, Email [email protected]

Prospective Applications of Artificial Intelligence In Fetal Medicine: A Scoping Review of Recent Updates

Elhadi Miskeen,1 Jaber Alfaifi,2 Dalal Mohammed Alhuian,3 Mushabab Alghamdi,4 Muffarah Hamid Alharthi,5 Nourah Abdullah Alshahrani,3 Ghala Alosaimi,6 Raydaa Abdullah Alshomrani,3 Abdullah Mohammed Hajlaa,3 Nadir Mohammed Khair,7 Abdullah Mohammed Almuawi,3 Khalifa Haytham Al-Jaber,8 Fath Elrahman Elrasheed,9 Kamal Elhassan,5 Mohammed Abbas10 1Department of Obstetrics and Gynecology, College of Medicine, University of Bisha, Bisha, Saudi Arabia; 2Department of Child Health, College of Medicine University of Bisha, Bisha, Saudi Arabia; 3Medical Student, College of Medicine University of Bisha, Bisha, Saudi Arabia; 4Department of Internal Medicine, College of Medicine, University of Bisha, Bisha, Saudi Arabia; 5Department of Family and Community Medicine, College of Medicine, University of Bisha, Bisha, Saudi Arabia; 6Medical student, College of Medicine, Taif University, Taif, Saudi Arabia; 7Department of Child Health, Mother and Children Hospital, Bisha, Saudi Arabia; 8Medical student, Royal College of Surgeons, Dublin, Ireland; 9Department of Obstetrics and Gynecology, Faculty of Medicine Najran University, Najran, Saudi Arabia; 10Department of Pediatrics, College of Medicine, Arab Gulf University, Al Manama, BahrainCorrespondence: Elhadi Miskeen, Head Department of Obstetrics and Gynecology, College of Medicine, University of Bisha, P. O. Box 731, Bisha, 61922, Saudi Arabia, Email [email protected]: With the incorporation of artificial intelligence (AI), significant advancements have occurred in the field of fetal medicine, holding the potential to transform prenatal care and diagnostics, promising to revolutionize prenatal care and diagnostics. This scoping review aims to explore the recent updates in the prospective application of AI in fetal medicine, evaluating its current uses, potential benefits, and limitations.Methods: Compiling literature concerning the utilization of AI in fetal medicine does not appear to modify the subject or provide an exhaustive exploration of electronic databases. Relevant studies, reviews, and articles published in recent years were incorporated to ensure up-to-date data. The selected works were analyzed for common themes, AI methodologies applied, and the scope of AI’s integration into fetal medicine practice.Results: The review identified several key areas where AI applications are making strides in fetal medicine, including prenatal screening, diagnosis of congenital anomalies, and predicting pregnancy complications. AI-driven algorithms have been developed to analyze complex fetal ultrasound data, enhancing image quality and interpretative accuracy. The integration of AI in fetal monitoring has also been explored, with systems designed to identify patterns indicative of fetal distress. Despite these advancements, challenges related to the ethical use of AI, data privacy, and the need for extensive validation of AI tools in diverse populations were noted.Conclusion: The potential benefits of AI in fetal medicine are immense, offering a brighter future for our field. AI equips us with tools for enhanced diagnosis, monitoring, and prognostic capabilities, promising to revolutionize the way we approach prenatal care and diagnostics. This optimistic outlook underscores the need for further research and interdisciplinary partnerships to fully leverage AI’s potential in driving forward the practice of fetal medicine.Keywords: artificial intelligence, fetal medicine, prenatal care, machine learning, fetal monitoring, Bisha, Saudi Arabi

Comorbidities and Risk Factors for Severe Outcomes in COVID-19 Patients in Saudi Arabia: A Retrospective Cohort Study

Purpose: The first novel coronavirus disease-19 (COVID-19) case in the Kingdom of Saudi Arabia (KSA) was reported in Qatif in March 2020 with continual increase in infection and mortality rates since then. In this study, we aim to determine risk factors which effect severity and mortality rates in a cohort of hospitalized COVID-19 patients in KSA. Method: We reviewed medical records of hospitalized patients with confirmed COVID-19 positive results via reverse-transcriptase-polymerase-chain-reaction (RT-PCR) tests at Prince Mohammed Bin Abdulaziz Hospital, Riyadh between May and August 2020. Data were obtained for patient’s demography, body mass index (BMI), and comorbidities. Additional data on patients that required intensive care unit (ICU) admission and clinical outcomes were recorded and analyzed with Python Pandas. Results: A total of 565 COVID-19 positive patients were inducted in the study out of which, 63 (11.1%) patients died while 101 (17.9%) patients required ICU admission. Disease incidences were significantly higher in males and non-Saudi nationals. Patients with cardiovascular, respiratory, and renal diseases displayed significantly higher association with ICU admissions (p< 0.001) while mortality rates were significantly higher in COVID-19 patients with cardiovascular, respiratory, renal and neurological diseases. Univariate cox proportional hazards regression model showed that COVID-19 positive patients requiring ICU admission [Hazard’s ratio, HR=4.2 95% confidence interval, CI 2.5– 7.2); p< 0.001] with preexisting cardiovascular [HR=4.1 (CI 2.5– 6.7); p< 0.001] or respiratory [HR=4.0 (CI 2.0– 8.1); p=0.010] diseases were at significantly higher risk for mortality among the positive patients. There were no significant differences in mortality rates or ICU admissions among males and females, and across different age groups, BMIs and nationalities. Hospitalized patients with cardiovascular comorbidity had the highest risk of death (HR=2.9, CI 1.7– 5.0; p=0.020). Conclusion: Independent risk factors for critical outcomes among COVID-19 in KSA include cardiovascular, respiratory and renal comorbidities

Burden of disease scenarios by state in the USA, 2022–50: a forecasting analysis for the Global Burden of Disease Study 2021

Background: The capacity to anticipate future health issues is important for both policy makers and practitioners in the USA, as such insights can facilitate effective planning, investment, and implementation strategies. Forecasting trends in disease and injury burden is not only crucial for policy makers but also garners substantial interest from the general populace and leads to a better-informed public. Through the integration of new data sources, the refinement of methodologies, and the inclusion of additional causes, we have improved our previous forecasting efforts within the scope of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to produce forecasts at the state and national levels for the USA under various possible scenarios. Methods: We developed a comprehensive framework for forecasting life expectancy, healthy life expectancy (HALE), cause-specific mortality, and disability-adjusted life-years (DALYs) due to 359 causes of disease and injury burden from 2022 to 2050 for the USA and all 50 states and Washington, DC. Using the GBD 2021 Future Health Scenarios modelling framework, we forecasted drivers of disease, demographic drivers, risk factors, temperature and particulate matter, mortality and years of life lost (YLL), population, and non-fatal burden. In addition to a reference scenario (representing the most probable future trajectory), we explored various future scenarios and their potential impacts over the next several decades on human health. These alternative scenarios comprised four risk elimination scenarios (including safer environment, improved behavioural and metabolic risks, improved childhood nutrition and vaccination, and a combined scenario) and three USA-specific scenarios based on risk exposure or attributable burden in the best-performing US states (improved high adult BMI and high fasting plasma glucose [FPG], improved smoking, and improved drug use [encompassing opioids, cocaine, amphetamine, and others]). Findings: Life expectancy in the USA is projected to increase from 78·3 years (95% uncertainty interval 78·1–78·5) in 2022 to 79·9 years (79·5–80·2) in 2035, and to 80·4 years (79·8–81·0) in 2050 for all sexes combined. This increase is forecasted to be modest compared with that in other countries around the world, resulting in the USA declining in global rank over the 2022–50 forecasted period among the 204 countries and territories in GBD, from 49th to 66th. There is projected to be a decline in female life expectancy in West Virginia between 1990 and 2050, and little change in Arkansas and Oklahoma. Additionally, after 2023, we projected almost no change in female life expectancy in many states, notably in Oklahoma, South Dakota, Utah, Iowa, Maine, and Wisconsin. Female HALE is projected to decline between 1990 and 2050 in 20 states and to remain unchanged in three others. Drug use disorders and low back pain are projected to be the leading Level 3 causes of age-standardised DALYs in 2050. The age-standardised DALY rate due to drug use disorders is projected to increase considerably between 2022 and 2050 (19·5% [6·9–34·1]). Our combined risk elimination scenario shows that the USA could gain 3·8 additional years (3·6–4·0) of life expectancy and 4·1 additional years (3·9–4·3) of HALE in 2050 versus the reference scenario. Using our USA-specific scenarios, we forecasted that the USA could gain 0·4 additional years (0·3–0·6) of life expectancy and 0·6 additional years (0·5–0·8) of HALE in 2050 under the improved drug use scenario relative to the reference scenario. Life expectancy and HALE are likewise projected to be 0·4–0·5 years higher in 2050 under the improved adult BMI and FPG and improved smoking scenarios compared with the reference scenario. However, the increases in these scenarios would not substantially improve the USA's global ranking in 2050 (from 66th of 204 in life expectancy in the reference scenario to 63rd–64th in each of the three USA-specific scenarios), indicating that the USA's best-performing states are still lagging behind other countries in their rank throughout the forecasted period. Regardless, an estimated 12·4 million (11·3–13·5) deaths could be averted between 2022 and 2050 if the USA were to follow the combined scenario trajectory rather than the reference scenario. There would also be 1·4 million (0·7–2·2) fewer deaths over the 28-year forecasted period with improved adult BMI and FPG, 2·1 million (1·3–2·9) fewer deaths with improved exposure to smoking, and 1·2 million (0·9–1·5) fewer deaths with lower rates of drug use deaths. Interpretation: Our findings highlight the alarming trajectory of health challenges in the USA, which, if left unaddressed, could lead to a reversal of the health progress made over the past three decades for some US states and a decline in global health standing for all states. The evidence from our alternative scenarios along with other published studies suggests that through collaborative, evidence-based strategies, there are opportunities to change the trajectory of health outcomes in the USA, such as by investing in scientific innovation, health-care access, preventive health care, risk exposure reduction, and education. Our forecasts clearly show that the time to act is now, as the future of the country's health and wellbeing—as well as its prosperity and leadership position in science and innovation—are at stake. Funding: Bill & Melinda Gates Foundation