Harnessing Machine Learning in Early COVID-19 Detection and Prognosis: A Comprehensive Systematic Review.

During the early phase of the COVID-19 pandemic, reverse transcriptase-polymerase chain reaction (RT-PCR) testing faced limitations, prompting the exploration of machine learning (ML) alternatives for diagnosis and prognosis. Providing a comprehensive appraisal of such decision support systems and their use in COVID-19 management can aid the medical community in making informed decisions during the risk assessment of their patients, especially in low-resource settings. Therefore, the objective of this study was to systematically review the studies that predicted the diagnosis of COVID-19 or the severity of the disease using ML. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), we conducted a literature search of MEDLINE (OVID), Scopus, EMBASE, and IEEE Xplore from January 1 to June 31, 2020. The outcomes were COVID-19 diagnosis or prognostic measures such as death, need for mechanical ventilation, admission, and acute respiratory distress syndrome. We included peer-reviewed observational studies, clinical trials, research letters, case series, and reports. We extracted data about the study's country, setting, sample size, data source, dataset, diagnostic or prognostic outcomes, prediction measures, type of ML model, and measures of diagnostic accuracy. Bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO), with the number CRD42020197109. The final records included for data extraction were 66. Forty-three (64%) studies used secondary data. The majority of studies were from Chinese authors (30%). Most of the literature (79%) relied on chest imaging for prediction, while the remainder used various laboratory indicators, including hematological, biochemical, and immunological markers. Thirteen studies explored predicting COVID-19 severity, while the rest predicted diagnosis. Seventy percent of the articles used deep learning models, while 30% used traditional ML algorithms. Most studies reported high sensitivity, specificity, and accuracy for the ML models (exceeding 90%). The overall concern about the risk of bias was "unclear" in 56% of the studies. This was mainly due to concerns about selection bias. ML may help identify COVID-19 patients in the early phase of the pandemic, particularly in the context of chest imaging. Although these studies reflect that these ML models exhibit high accuracy, the novelty of these models and the biases in dataset selection make using them as a replacement for the clinicians' cognitive decision-making questionable. Continued research is needed to enhance the robustness and reliability of ML systems in COVID-19 diagnosis and prognosis.

Mental health impact of the first wave of COVID-19 pandemic on healthcare workers in 12 Arab countries.

Background: The COVID-19 pandemic has had a significant impact on public health, including healthcare workers and healthcare systems, worldwide. Aims: To investigate COVID-19-related psychological impact on healthcare workers in 12 Arab countries. Methods: This was a cross-sectional, hospital-based online survey conducted between 4 May and 8 June 2020. We evaluated stress, depression, anxiety, and insomnia using the Depression Anxiety Stress Scale and Insomnia Severity Index. Results: A total of 2879 respondents from 12 Arab countries completed the survey. Anxiety, depression, stress, and insomnia were reported by 48.9%, 50.6%, 41.4% and 72.1% of respondents, respectively. Lower-middle- and lower-income countries had a significantly higher prevalence of all the psychological outcomes than high-income countries. The prevalence of mental health symptoms was higher among healthcare workers aged 30-39 years, those who worked > 44 hours per week, and those in contact with COVID-19 cases, as well as healthcare workers who were not satisfied with the preventive measures. The prevalence of mental health symptoms was lower among male healthcare workers. Conclusion: COVID-19 had a considerable impact on the mental and psychological health of healthcare workers in Arab countries. This was aggravated by the geopolitical location of some Arab countries and social norms usually observed during the month of Ramadan. Being a physician or a young healthcare worker, and long working hours were risk factors for greater psychological impact of the outbreak.

International alliance and AGREE-ment of 71 clinical practice guidelines on the management of critical care patients with COVID-19: a living systematic review.

OBJECTIVE: We aimed to systematically identify and critically assess the clinical practice guidelines (CPGs) for the management of critically ill patients with COVID-19 with the AGREE II instrument. STUDY DESIGN AND SETTING: We searched Medline, CINAHL, EMBASE, CNKI, CBM, WanFang, and grey literature from November 2019 - November 2020. We did not apply language restrictions. One reviewer independently screened the retrieved titles and abstracts, and a second reviewer confirmed the decisions. Full texts were assessed independently and in duplicate. Disagreements were resolved by consensus. We included any guideline that provided recommendations on the management of critically ill patients with COVID-19. Data extraction was performed independently and in duplicate by two reviewers. We descriptively summarized CPGs characteristics. We assessed the quality with the AGREE II instrument and we summarized relevant therapeutic interventions. RESULTS: We retrieved 3,907 records and 71 CPGs were included. Means (Standard Deviations) of the scores for the 6 domains of the AGREE II instrument were 65%(SD19.56%), 39%(SD19.64%), 27%(SD19.48%), 70%(SD15.74%), 26%(SD18.49%), 42%(SD34.91) for the scope and purpose, stakeholder involvement, rigor of development, clarity of presentation, applicability, editorial independence domains, respectively. Most of the CPGs showed a low overall quality (less than 40%). CONCLUSION: Future CPGs for COVID-19 need to rely, for their development, on standard evidence-based methods and tools.

Predictors of healthcare workers' intention to vaccinate against COVID-19: A cross sectional study from Saudi Arabia.

BACKGROUND: Vaccination is considered the best way to prevent the spread of COVID-19 and to prevent the complications of the disease. Nevertheless, no awareness campaigns were conducted in Saudi Arabia until March 1, 2021, when the Vaxzevria, or ChAdOx1 nCoV-19 (AZD1222), vaccine became available. OBJECTIVES: This study aims to determine the factors that can predict healthcare workers' acceptance of the COVID-19 vaccine. METHODS: A cross-sectional study was conducted from July to September 2021, in our university tertiary hospital (King Saud University Medical City [KSUMC]), Riyadh, Saudi Arabia. The study targeted potential participants among healthcare workers at KSUMC. We assessed healthcare workers' perceptions and beliefs about the COVID-19 vaccine via a questionnaire that was distributed via social media applications such as WhatsApp, Twitter, and Google. Participants were informed about the questionnaire before they filled it out, and they were asked to respond to three screening questions before beginning the main questionnaire. These screening questions ensured that the participants met the inclusion criteria. Included participants were over the age of 18, agreed to answer the questions, and were residents of Saudi Arabia. The participants filled out the self-administered questionnaire. RESULTS: A total of 529 participants completed the questionnaires. All participants were vaccinated, 68% were female, 55% were married, 35% had been working for less than five years, and 65% had a bachelor's degree. More than half of participants had not previously been infected with COVID-19, and most did not interact with COVID-19 patients. More convenient access to the vaccine increased the odds ratio of participant vaccination by 0.39. An increase in the number of vaccinated friends and family members increased the odds ratio of participant vaccination by 0.30. However, COVID- 19 vaccination mandates decreased the odds ratio of participant vaccination by 0.27. The fitted linear regression model explained 32% of the variation observed in the dependent variable, acceptance of the COVID-19 vaccine, and the adjusted R squared was 0.32. The fitted regression model was statistically significant at a 95% confidence interval; the p-value was 0.00001. CONCLUSION: In Saudi Arabia, there is an immense need to increase uptake of the COVID-19 vaccine. This requires encouraging more positive beliefs and attitudes regarding vaccination in general and the COVID-19 vaccine in particular.

Effects of Computerised Clinical Decision Support on Adherence to VTE Prophylaxis Clinical Practice Guidelines among Hospitalised Patients.

OBJECTIVE: Venous thromboembolism (VTE) is an important patient safety concern. VTE leads to significant mortality and morbidity and a burden on healthcare resources. Despite the widespread availability of evidence-based clinical practice guidelines on VTE prophylaxis, we found that only 50.9% of our patients were receiving appropriate prophylaxis. The purpose of this study was to evaluate the impact of automation of an adapted VTE prophylaxis CPG using a clinical decision support system (the VTE-CDSS) on VTE prevention among hospitalised adult patients. DESIGN AND SETTING: A quasi-experimental study (pre- and post-implementation) was conducted at a large 900-bed tertiary teaching multi-specialty hospital in Riyadh, Saudi Arabia. PARTICIPANTS: The 1809 adult patients in the study included 871 enrolled during the pre-implementation stage and 938 enrolled during the post-implementation stage. INTERVENTION: Multi-faceted implementation interventions were utilised, including leadership engagement and support, quality and clinical champions, staff training and education and regular audit and feedback. MAIN OUTCOME MEASURE: Two rate-based process measures were calculated for each admission cohort (i.e. pre- and post-implementation): the percentage of inpatients who were assessed for VTE risk on admission and the percentage of inpatients who received appropriate VTE prophylaxis. Two outcome measures were calculated: the prevalence of hospital-acquired VTE (HA-VTE) events and the in-hospital all-cause mortality. RESULTS: The percentage of inpatients risk assessed for VTE on admission increased from 77.4% to 93.3% (P < 0.01). The percentage of patients who received appropriate VTE prophylaxis increased from 50.9% to 81.4% (P < 0.01). The HA-VTE events decreased by 50% from 0.33% to 0.15% (P < 0.01).All-cause in-hospital mortality did not significantly change after implementation of the VTE-CDSS compared with pre-implementation mortality (P > 0.05). CONCLUSION: The VTE-CDSS improved patient safety by enhancing adherence to the VTE prophylaxis best practice and adapted CPG. The multi-faceted implementation strategies approach improved the compliance rate of risk assessment and the adherence to prophylaxis recommendations and substantially reduced the HA-VTE prevalence. A successful CDSS requires a set of critical components to ensure better user compliance and positive patient outcomes.

Systematic review and meta-analysis of the effectiveness of pre-pregnancy care for women with diabetes for improving maternal and perinatal outcomes.

BACKGROUND: Pre-gestational diabetes mellitus is associated with increased risk of maternal and perinatal adverse outcomes. This systematic review was conducted to evaluate the effectiveness and safety of pre-conception care (PCC) in improving maternal and perinatal outcomes. METHODS: Databases from MEDLINE, EMBASE, WEB OF SCIENCE, and Cochrane Library were searched, including the CENTRAL register of controlled trials, and CINHAL up until March 2019, without any language restrictions, for any pre-pregnancy care aiming at health promotion, glycemic control, and screening and treatment of diabetes complications in women with type I or type II pre-gestational diabetes. Trials and observational studies were included in the review. Newcastle-Ottawa scale and the Cochrane collaboration methodology for data synthesis and analysis were used, along with the GRADE tool to evaluate the body of evidence. RESULTS: The search identified 8500 potentially relevant citations of which 40 reports of 36 studies were included. The meta-analysis results show that PCC reduced congenital malformations risk by 71%, (Risk ratio (RR) 0.29; 95% CI: 0.21-0.40, 25 studies; 5903 women; high-certainty evidence). The results also show that PCC may lower HbA1c in the first trimester of pregnancy by an average of 1.27% (Mean difference (MD) 1.27; 95% CI: 1.33-1.22; 4927 women; 24 studies, moderate-certainty evidence). Furthermore, the results suggest that PCC may lead to a slight reduction in the risk of preterm delivery of 15%, (RR 0.85; 95% CI: 0.73-0.99; nine studies, 2414 women; moderate-certainty evidence). Moreover, PCC may result in risk reduction of perinatal mortality by 54%, (RR 0.46; 95% CI: 0.30-0.73; ten studies; 3071 women; moderate-certainty evidence). There is uncertainty about the effects of PCC on the early booking for antenatal care (MD 1.31; 95% CI: 1.40-1.23; five studies, 1081 women; very low-certainty evidence) and maternal hypoglycemia in the first trimester, (RR 1.38; 95% CI: 1.07-1.79; three studies; 686 women; very low- certainty evidence). In addition, results of the meta-analysis indicate that PCC may lead to 48% reduction in the risk of small for gestational age (SGA) (RR 0.52; 95% CI: 0.37-0.75; six studies, 2261 women; moderate-certainty evidence). PCC may reduce the risk of neonatal admission to intensive care unit (NICU) by 25% (RR 0.75; 95% CI: 0.67-0.84; four studies; 1322 women; moderate-certainty evidence). However, PCC may have little or no effect in reducing the cesarean section rate (RR 1.02; 95% CI: 0.96-1.07; 14 studies; 3641 women; low-certainty evidence); miscarriage rate (RR 0.86; 95% CI: 0.70-1.06; 11 studies; 2698 women; low-certainty evidence); macrosomia rate (RR 1.06; 95% CI: 0.97-1.15; nine studies; 2787 women, low-certainty evidence); neonatal hypoglycemia (RR 0.93; 95% CI: 0.74-1.18; five studies; 880 women; low-certainty evidence); respiratory distress syndrome (RR 0.78; 95% CI: 0.47-1.29; four studies; 466 women; very low-certainty evidence); or shoulder dystocia (RR 0.28; 95% CI: 0.07-1.12; 2 studies; 530 women; very low-certainty evidence). CONCLUSION: PCC for women with pre-gestational type 1 or type 2 diabetes mellitus is effective in improving rates of congenital malformations. In addition, it may improve the risk of preterm delivery and admission to NICU. PCC probably reduces maternal HbA1C in the first trimester of pregnancy, perinatal mortality and SGA. There is uncertainty regarding the effects of PCC on early booking for antenatal care or maternal hypoglycemia during the first trimester of pregnancy. PCC has little or no effect on other maternal and perinatal outcomes.

Adapting evidence-based clinical practice guidelines at university teaching hospitals: A model for the Eastern Mediterranean Region.

RATIONALE, AIMS, AND OBJECTIVES: Clinical practice guidelines (CPGs) are significant tools for evidence-based health care quality improvement. The CPG program at King Saud University was launched as a quality improvement program to fulfil the international accreditation standards. This program was a collaboration between the Research Chair for Evidence-Based Healthcare and Knowledge Translation and the Quality Management Department. This study aims to develop a fast-track method for adaptation of evidence-based CPGs and describe results of the program. METHODS: Twenty-two clinical departments participated in the program. Following a CPGs awareness week directed to all health care professionals (HCPs), 22 teams were trained to set priorities, search, screen, assess, select, and customize the best available CPGs. The teams were technically supported by the program's CPG advisors. To address the local health care context, a modified version of the ADAPTE was used where recommendations were either accepted or rejected but not changed. A strict peer-review process for clinical content and methodology was employed. RESULTS: In addition to raising awareness and building capacity, 35 CPGs were approved for implementation by March 2018. These CPGs were integrated with other existing projects such as accreditation, electronic medical records, performance management, and training and education. Preliminary implementation audits suggest a positive impact on patient outcomes. Leadership commitment was a strength, but the high turnover of the team members required frequent and extensive training for HCPs. CONCLUSION: This model for CPG adaptation represents a quick, practical, economical method with a sense of ownership by staff. Using this modified version can be replicated in other countries to assess its validity.

Quality assessment of recent evidence-based clinical practice guidelines for management of type 2 diabetes mellitus in adults using the AGREE II instrument.

RATIONALE, AIMS AND OBJECTIVES: Type 2 diabetes mellitus (T2DM) is a worldwide and national public health problem that has a great impact on the population in Saudi Arabia. High-quality clinical practice guidelines (CPGs) are cornerstones in improving the health care provided for patients with diabetes. This study evaluated the methodological rigour, transparency, and applicability of recently published CPGs. METHODS: Our group conducted a systematic search for recently published CPGs for T2DM. The searching and screening for Source CPGs were guided by tools from the ADAPTE methods with specific inclusion/exclusion criteria. Five reviewers using the second version of the Appraisal of Guidelines for Research and Evaluation (AGREE II) Instrument independently assessed the quality of the retrieved Source CPGs. RESULTS: Domains of Scope and purpose and Clarity of presentation received the highest scores in all CPGs. Most of the assessed CPGs (86%) were considered with high overall quality and were recommended for use. Rigour of development and applicability domains were together highest in 3 CPGs (43%). The overall high quality of DM CPGs published in the last 3 years demonstrated the continuous development and improvement in CPG methodologies and standards. CONCLUSIONS: Health care professionals should consider the quality of any CPG for T2DM before deciding to use it in their daily clinical practice. Three CPGs have been identified, using the AGREE criteria, as high-quality and trustworthy. Ideally, the resources provided by the AGREE trust including the AGREE II Instrument should be used by a clinician to scan through the large number of published T2DM CPGs to identify the CPGs with high methodological quality and applicability.

Failure Mode and Effect Analysis (FMEA) may enhance implementation of clinical practice guidelines: An experience from the Middle East.

RATIONALE, AIMS, AND OBJECTIVES: Implementation of clinical practice guidelines (CPGs) has been shown to reduce variation in practice and improve health care quality and patients' safety. There is a limited experience of CPG implementation (CPGI) in the Middle East. The CPG program in our institution was launched in 2009. The Quality Management department conducted a Failure Mode and Effect Analysis (FMEA) for further improvement of CPGI. METHODS: This is a prospective study of a qualitative/quantitative design. Our FMEA included (1) process review and recording of the steps and activities of CPGI; (2) hazard analysis by recording activity-related failure modes and their effects, identification of actions required, assigned severity, occurrence, and detection scores for each failure mode and calculated the risk priority number (RPN) by using an online interactive FMEA tool; (3) planning: RPNs were prioritized, recommendations, and further planning for new interventions were identified; and (4) monitoring: after reduction or elimination of the failure mode. The calculated RPN will be compared with subsequent analysis in post-implementation phase. RESULTS: The data were scrutinized from a feedback of quality team members using a FMEA framework to enhance the implementation of 29 adapted CPGs. The identified potential common failure modes with the highest RPN (≥ 80) included awareness/training activities, accessibility of CPGs, fewer advocates from clinical champions, and CPGs auditing. Actions included (1) organizing regular awareness activities, (2) making CPGs printed and electronic copies accessible, (3) encouraging senior practitioners to get involved in CPGI, and (4) enhancing CPGs auditing as part of the quality sustainability plan. CONCLUSION: In our experience, FMEA could be a useful tool to enhance CPGI. It helped us to identify potential barriers and prepare relevant solutions.