Transdisciplinary approaches to addressing factors that influence antimicrobial use in dairy cattle:A scoping review

Interest in antimicrobial resistance (AMR) associated with livestock farming is increasing. During the 1990s, 30-40 academic papers a year on the use of antibiotics in dairy farming were indexed on the scientific database PubMed, but this has grown to more than 200 a year in the 2020s. Most (85%) of these papers are published in veterinary or livestock science journals. There has been a corresponding increase in social science interest in why responsible antibiotic stewardship in the livestock sector is so challenging. However, most social science insights are published in journals specific to the lead authors' field(s), missing opportunities for knowledge translation to veterinary and animal science. This threatens to inhibit the transdisciplinary One Health approaches required to tackle the problem. Between 1 June and 31 December 2021, we undertook a scoping review of papers on the use of antibiotics in dairy farming indexed in PubMed, Scopus and Web of Science. Our aim was to identify studies that incorporate social science approaches and methodologies, and to note the main field of the journal in which these studies are published. Papers were most likely to be published in veterinary science, dairy science and/or livestock science journals (61, 29 and 18 respectively out of 127 papers) and were most likely to be concerned with antibiotic use, prescribing practice, and/or diagnosis (94%, 39% and 33% of included papers respectively). Only 27% of papers meeting our inclusion criteria included a qualitative approach to understanding reasons for antibiotic use. Even fewer acknowledged underlying drivers of behaviour, whereas such reasons are frequently highlighted in social science literature. Thus, to address the global health threat from antibiotic resistance, more work is needed to bring together the disparate but equally valid disciplines, methodologies and researchers working on antibiotic use in the livestock sector.</p

Reducing defects in the datasets of clinical research studies: conformance with data quality metrics

Background A dataset is indispensable to answer the research questions of clinical research studies. Inaccurate data lead to ambiguous results, and the removal of errors results in increased cost. The aim of this Quality Improvement Project (QIP) was to improve the Data Quality (DQ) by enhancing conformance and minimizing data entry errors. Methods This is a QIP which was conducted in the Department of Biostatistics using historical datasets submitted for statistical data analysis from the department’s knowledge base system. Forty-five datasets received for statistical data analysis, were included at baseline. A 12-item checklist based on six DQ domains (i) completeness (ii) uniqueness (iii) timeliness (iv) accuracy (v) validity and (vi) consistency was developed to assess the DQ. The checklist was comprised of 12 items; missing values, un-coded values, miscoded values, embedded values, implausible values, unformatted values, missing codebook, inconsistencies with the codebook, inaccurate format, unanalyzable data structure, missing outcome variables, and missing analytic variables. The outcome was the number of defects per dataset. Quality improvement DMAIC (Define, Measure, Analyze, Improve, Control) framework and sigma improvement tools were used. Pre-Post design was implemented using mode of interventions. Pre-Post change in defects (zero, one, two or more defects) was compared by using chi-square test. Results At baseline, out of forty-five datasets; six (13.3%) datasets had zero defects, eight (17.8%) had one defect, and 31(69%) had ≥2 defects. The association between the nature of data capture (single vs. multiple data points) and defective data was statistically significant (p = 0.008). Twenty-one datasets were received during post-intervention for statistical data analysis. Seventeen (81%) had zero defects, two (9.5%) had one defect, and two (9.5%) had two or more defects. The proportion of datasets with zero defects had increased from 13.3 to 81%, whereas the proportion of datasets with two or more defects had decreased from 69 to 9.5% (p = < 0.001). Conclusion Clinical research study teams often have limited knowledge of data structuring. Given the need for good quality data, we recommend training programs, consultation with data experts prior to data structuring and use of electronic data capturing methods

Mental health outcomes amongst health care workers during COVID 19 pandemic in Saudi Arabia

Objectives: The study aimed to assess the mental health outcomes and associated factors among health care workers during COVID 19 in Saudi Arabia.Design, Setting, and Participants: We conducted a cross-sectional survey of health care workers from tertiary care and ministry of health Centers across the Central, Eastern, and Western regions of Saudi Arabia. There were 1,130 participants in the survey, and we collected demographic and mental health measurements from the participants.Primary Outcomes and Measures: The magnitude of symptoms of depression, anxiety, and insomnia was measured using the original version of 9-item patient health questionnaire (PHQ-9), the 7-item generalized anxiety disorder scale (GAD-7), and 7-item insomnia severity index (ISI). We use the multiple logistic regression analysis to identify the associated risk factors of individual outcomes.Results: The scores on the PHQ-9 showed that the largest proportion of health care workers (76.93%) experienced only normal to mild depression (50.83 and 26.1%, respectively). The scores on the GAD-7 showed that the largest proportion of health care workers (78.88%) experienced minimal to mild anxiety (50.41 and 28.47%, respectively). The scores on the ISI showed that the largest proportion of health care workers (85.83%) experienced absence to subthreshold insomnia (57.08 and 28.75%, respectively). The risk factors for depression in health care workers were Saudi, living with family, working from an isolated room at home and frontline worker. For anxiety, being female was risk factor and for insomnia, being frontline worker was risk factor.Conclusion: It was observed that the symptoms of depression, anxiety, and insomnia were reported in a lower proportion of health care workers in our study. The participants who were female, frontline workers, Saudi, living with family, and working from home in isolated rooms were predisposed to developing psychological disorders

Role of invasive mechanical ventilation and ECMO in the management of COVID-19: a systematic review

Objectives: This systematic review aims to provide insight into the outcome of extracorporeal membrane oxygenation (ECMO) and invasive mechanical ventilation use in critically ill COVID-19 patients. Data sources: Electronic databases PubMed Central and PubMed were searched from January 2020 to June 2020 for published studies about ECMO and/or invasive mechanical ventilation use in COVID-19 patients. Data Extraction and Study Selection: The search strategy retrieved 766 articles, of which 19 studies consisting of 204 patients fulfilled the inclusion criteria and were included in the analysis. Data synthesis: Primary outcomes evaluated were discharge and/or clinical improvement and mortality rate. Secondary outcomes evaluated included reported complications and the mean number of days of hospitalization for survivors. Weighted averages of included studies were calculated, and data were pooled in forest plots. Nearly, 68.1% of the patients received invasive mechanical ventilation without ECMO support, and 31.9% were placed on ECMO. Also, 22.5% of the patients were discharged and/or clinically improved and 51.5% died. Twenty-six percent of the study population deteriorated but remained alive or experienced no improvement in clinical condition. And 75.2% of those who died belonged to the non-ECMO group and 24.8% to the ECMO group. The mortality rate in the non-ECMO group was 56.8% compared to 40% in the ECMO group. Conclusion: The utility of ECMO during a pandemic is uncertain as it is a resource-intensive modality, especially when the mortality rate in severely ill patients infected with COVID-19 virus is already known to be high

The development and validation of a multivariable model to predict the bleeding risk score for patients with non-valvular atrial fibrillation using direct oral anticoagulants in the Arab population.

Background Frequently used models, such as the HAS-BLED, ATRIA, ORBIT, and GARFIELD-AF evaluate the risk of bleeding when using an anticoagulant, for example warfarin, in patients with non-valvular atrial fibrillation. Limited studies are available reporting a model with a good discriminative ability to predict the bleeding risk score when using direct oral anticoagulants. Methods Patient data were collected from King Abdulaziz Medical City, King Fahad Cardiac Center, and Prince Sultan Cardiac Center in Riyadh, from outpatients, inpatients, or primary care clinics. In total, 1722 patients with a prescription for a new oral anticoagulant, Dabigatran, Rivaroxaban, or Apixaban, were enrolled. A resampling approach for variable selection was used and a five-fold cross-validation to assess the model fit and misclassification probabilities. The analysis used the receiver operating characteristics curve (ROC) and the concordance (c) statistic to assess the validation models’ discriminative power. The final penalized likelihood parameters were used for the development of the risk prediction tool. The accuracy of a classification and the prediction are reported with the sensitivity, specificity, and Brier score. Results Bleeding occurred in 11.15% of cases, of which 23.08% required a blood transfusion and 51.65% had a reduction in haemoglobin of more than 2 gm. The variable selection model identified 15 predictors associated with major bleeding. The discriminative ability of the model was good (c-statistic 0.75, p = 0.035). The Brier score of the model was 0.095. With a fixed cut-off probability value of 0.12 for the logistic regression equation, the sensitivity was 72.7%, and the specificity 66.3%. Conclusion This model demonstrated a good performance in predicting the bleeding risk in Arab patients treated with novel oral anticoagulants. This easy to use bleeding risk score will allow the clinician to quickly classify patients according to their risk category, supporting close monitoring and follow-up for high-risk patients, without laboratory and radiological monitoring

Ibuprofen and NSAID use in COVID-19 infected patients is not associated with worse outcomes: a prospective cohort sudy

Introduction Ibuprofen disappeared from the pharmacy shelves during the 2019 coronavirus (COVID-19) pandemic. However, a while later, information circulated that ibuprofen should be avoided as it could worsen COVID-19 symptoms. The aim of our study was to assess the association of acute and chronic use of nonsteroidal anti-inflammatory drugs (NSAIDs) with worse COVID-19 outcomes. Methods We did a prospective cohort study between April 12 and June 1, 2020. Adults consecutively diagnosed with COVID-19 were included. Information on NSAID use was collected through a telephone questionnaire, and patients were followed up for COVID-19 infection outcomes, including death, admission, severity, time to clinical improvement, oxygen requirement and length of stay. Results Acute use of ibuprofen was not associated with a greater risk of mortality relative to non-use (adjusted hazard ratio [HR] 0.632 [95% CI 0.073–5.441; P = 0.6758]). Chronic NSAID use was also not associated with a greater risk of mortality (adjusted HR 0.492 [95% CI 0.178–1.362; P = 0.1721]). Acute ibuprofen use was not associated with a higher risk of admission compared to non-NSAID users (adjusted odds ratio OR 1.271; 95% CI 0.548–2.953). NSAID users did not have a significantly longer time to clinical improvement or length of stay. Conclusion Acute or chronic use of ibuprofen and other NSAIDs was not associated with worse COVID-19 disease outcomes

Paternal postnatal depression among fathers of newborn in Saudi Arabia

Paternal postnatal depression (PPND) is not a commonly recognized phenomenon. The aim of the study was to identify the Edinburgh Postnatal Depression Scale (EPDS) cutoff for Saudi fathers, to estimate PPND prevalence and to determine the risk factors of PPND among fathers of newborn in Saudi Arabia. A cross-sectional study of fathers with babies born up to 6 months prior to the survey was conducted. Fathers were screened using EPDS and demographic questionnaire. The fathers were selected using systematic random sampling from visitors to the birth registration office. A subsample of participants from the postnatal wards in a tertiary care was invited for additional evaluation by a psychologist using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for major depressive disorders. Receiver operating characteristic curve was utilized to identify fathers with depression; a cutoff of 8/9 was optimal to achieve sensitivity 77.8% and specificity 81.3%. Adjusted prevalence of PPND was reported with corresponding Wilson 95% confidence interval. Two hundred and ninety fathers completed the EPDS and demographic questionnaire. Of 72 invited participants, 57 (79.16%) attended the diagnostic interview. The average age of fathers was 34.97 ± 8.56 years, the average maternal age was 29.18 ± 7.41 years, average age of the newborn was 43.13 ± 35.88 days. PPND adjusted prevalence was 16.6% (95% CI [8.5, 25.6]). Paternal mental health needs equal attention during and postdelivery of newborn. Fathers should receive perinatal and postnatal mental health assessment to prevent behavioral problems in their children and disruption of relationship with their spouse

Liraglutide effects on glycemic control and weight in patients with Type 2 Diabetes mellitus: a real-world, observational study and brief narrative review

Background Glycemic control and weight gain are two essential considerations in the pharmacological management of type 2 diabetes mellitus. Pharmacological agents are effective in lowering blood glucose levels but may result in significant weight gain. Liraglutide effectively maintains glycemic control while reducing weight. Methods This is a real-world study and brief narrative review of the effects of liraglutide on glycemic control and weight in adult patients with type 2 diabetes mellitus. The study uses data extracted from the electronic health record of the Ministry of National Guard-Health Affairs. Results In this study of 348 subjects, there was a statistically significant reduction in hemoglobin A1c of 0.9% (P < .0001) and weight of 2.3 kg (P < .0001). The majority (77.3%) were on concomitant insulin. Subjects with a baseline hemoglobin A1c greater than 9% had a significantly greater reduction than those below 9% (−0.7%; P < .0001). Those with a weight more than 100 kg had a significantly greater reduction than those below 100 kg (-0.9 kg; P = .0096). Conclusion In this real-world, observational study, liraglutide was shown to be effective in improving glycemic control and reducing weight in adult patients with type 2 diabetes mellitus

Predicting Patients’ Intention to Use a Personal Health Record Using an Adapted Unified Theory of Acceptance and Use of Technology Model: Secondary Data Analysis

BackgroundWith the rise in the use of information and communication technologies in health care, patients have been encouraged to use eHealth tools such as personal health records (PHRs) for better health and well-being services. PHRs support patient-centered care and patient engagement. To support the achievement of the Kingdom of Saudi Arabia's Vision 2030 ambitions, the National Transformation program provides a framework to use PHRs in meeting the triple aim for health care - increased access, reduced cost, and improved quality of care - and to provide patient- and person-centered care. However, there has been limited research on PHR uptake within the country.ObjectiveUsing the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, this study aims at identifying predictors of patient intention to utilize the Ministry of National Guard-Health Affairs (MNG-HA) PHR (MNGHA Care) application.MethodsUsing secondary data from a cross-sectional survey, data measuring intention to use the MNGHA Care application along with its predictors, were collected from adults (N=324) visiting MNG-HA facilities in Riyadh, Jeddah, Dammam, Madinah, Al Ahsa, and Qassim. The relationship of predictors (main theory constructs) and moderators (age, gender, experience with health applications) with the dependent variable (intention to use MNGHA Care) was tested using hierarchical multiple regression.ResultsOf the eligible population, a total of 261 adult patients were included in the analysis with a mean age of 35.07 years (± 9.61), male (n=132, 50.6%), university-educated (n=118, 45.2%), and at least one chronic medical condition (n=139, 53.3%). The model explained 48.9% of the variance in behavioral intention to use the PHR (P=.377). Performance expectancy, effort expectancy, and positive attitude were significantly associated with behavioral intention to use the PHR (PConclusionsThis research contributes to the existing literature on PHR adoption broadly as well as in the context of the Kingdom of Saudi Arabia. Understanding which factors are associated with patient adoption of PHRs can guide future development and support the country's aim of transforming the health care system. Similar to other studies on PHR adoption, performance expectancy, effort expectancy, and positive attitude are important factors, and practical consideration should be given supporting these areas.</p

Predicting patients' intention to use a personal health record using an adapted unified theory of acceptance and use of technology model : secondary data analysis

Background: With the rise in the use of information and communication technologies in health care, patients have been encouraged to use eHealth tools such as personal health records (PHRs) for better health and well-being services. PHRs support patient-centered care and patient engagement. To support the achievement of the Kingdom of Saudi Arabia’s Vision 2030 ambitions, the National Transformation program provides a framework to use PHRs in meeting the 3-fold aim for health care—increased access, reduced cost, and improved quality of care—and to provide patient- and person-centered care. However, there has been limited research on PHR uptake within the country. Objective: Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, this study aims at identifying predictors of patient intention to utilize the Ministry of National Guard-Health Affairs PHR (MNGHA Care) app. Methods: Using secondary data from a cross-sectional survey, data measuring the intention to use the MNGHA Care app, along with its predictors, were collected from among adults (n=324) visiting Ministry of National Guard-Health Affairs facilities in Riyadh, Jeddah, Dammam, Madinah, Al Ahsa, and Qassim. The relationship of predictors (main theory constructs) and moderators (age, gender, and experience with health apps) with the dependent variable (intention to use MNGHA Care) was tested using hierarchical multiple regression. Results: Of the eligible population, a total of 261 adult patients were included in the analysis. They had a mean age of 35.07 (SD 9.61) years, 50.6 % were male (n=132), 45.2% had university-level education (n=118), and 53.3% had at least 1 chronic medical condition (n=139). The model explained 48.9% of the variance in behavioral intention to use the PHR (P=.38). Performance expectancy, effort expectancy, and positive attitude were significantly associated with behavioral intention to use the PHR (P Conclusions: This study contributes to the existing literature on PHR adoption broadly as well as in the context of the Kingdom of Saudi Arabia. Understanding which factors are associated with patient adoption of PHRs can guide future development and support the country’s aim of transforming the health care system. Similar to previous studies on PHR adoption, performance expectancy, effort expectancy, and positive attitude are important factors, and practical consideration should be given to support these areas