Exploring the potential of artificial intelligence and machine learning to combat COVID-19 and existing opportunities for LMIC: A scoping review

Background: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine Learning (ML) have a vast potential to exponentially optimize health care research. The use of AI-driven tools in LMIC can help in eradicating health inequalities and decrease the burden on health systems.Methods: The literature search for this Scoping review was conducted through the PubMed database using keywords: COVID-19, Artificial Intelligence (AI), Machine Learning (ML), and Low Middle-Income Countries (LMIC). Forty-three articles were identified and screened for eligibility and 13 were included in the final review. All the items of this Scoping review are reported using guidelines for PRISMA extension for scoping reviews (PRISMA-ScR).Results: Results were synthesized and reported under 4 themes. (a) The need of AI during this pandemic: AI can assist to increase the speed and accuracy of identification of cases and through data mining to deal with the health crisis efficiently, (b) Utility of AI in COVID-19 screening, contact tracing, and diagnosis: Efficacy for virus detection can a be increased by deploying the smart city data network using terminal tracking system along-with prediction of future outbreaks, (c) Use of AI in COVID-19 patient monitoring and drug development: A Deep learning system provides valuable information regarding protein structures associated with COVID-19 which could be utilized for vaccine formulation, and (d) AI beyond COVID-19 and opportunities for Low-Middle Income Countries (LMIC): There is a lack of financial, material, and human resources in LMIC, AI can minimize the workload on human labor and help in analyzing vast medical data, potentiating predictive and preventive healthcare.Conclusion: AI-based tools can be a game-changer for diagnosis, treatment, and management of COVID-19 patients with the potential to reshape the future of healthcare in LMIC

School-based interventions to promote personal and environmental hygiene practices among children in Pakistan: Protocol for a mixed methods study

Background: Poor personal hygiene and inadequate sanitation practices among young children leads to communicable diseases. There remains a gap in the holistic assessment of school children\u27s hygiene literacy, practices and effectiveness of school-based hygiene interventions in Pakistan. Therefore, a school-based intervention protocol has been designed to promote personal and environmental hygiene practices for primary school children. Towards improving children\u27s hygiene behaviors, the study will also focus on enhancing mothers\u27 hygiene knowledge and practices.Methods: Using quasi-experimental design with mixed methods data collection approaches, this study will be conducted in schools located in an urban squatter settlements in Pakistan. To assess primary grade children and their mothers\u27 hygiene status, a survey will be held in the pre-intervention phase. This phase also includes qualitative exploration of key stakeholders (mothers, teachers, health & education authorities representatives\u27) perceptions about the factors facilitating and impeding the adaption of hygiene behaviors among school children. In-depth guides and focus group discussion tools will be used for this purpose. This will be followed by multi-component intervention phase with behavior change strategies to improve children\u27s and mothers\u27 hygiene literacy and behaviors. The post-intervention phase will assess the intervention effectiveness in terms of enhancing hygiene knowledge and practices among school children and mothers, alongside exploration of mothers and teachers\u27 insights into whether or not the intervention has been effective in improving hygiene practices among children. Paired t-test will be applied pre and post-intervention to measure the differences between the mothers and children\u27s hygiene literacy and knowledge scores. Similar test will be performed to assess the differences in children\u27s hygiene knowledge and practice scores, pre and post-intervention (\u3c 50 = poor, 50-75 = good and \u3e 75 = excellent). Thematic analysis will be carried out for qualitative data.Discussion: Multi-component intervention aimed at improving personal and environmental hygiene among primary school children offers an opportunity to design and test various behavioral change strategies at school and in home settings. The study findings will be significant in assessing the intervention\u27s effectiveness in improving children\u27s overall hygiene

The difference in impact of direct versus interfacility transfers in predicting 30 day mortality among adult road traffic crash victims presenting to the ED settings of three tertiary care hospitals in Karachi

Road traffic crashes are a leading cause of death globally among young people, and the main cause of death among those aged 15-29 years, currently Road Traffic Crashes are found to be the 9th leading cause of mortality amongst all age groups which is further predicted to become at the rh leading cause of mortality by year 2030. Health outcomes of Road Traffic Crash Victims are determined in 3 phases, Prevention of Crash, the crash phase, and after the crash(Post Crash Care). There exists gross disparity amongst low and middle income countries versus high income countries to the level of care received immediately post-crash. It is therefore important to Transfer the Crash Victims to the right hospital at the right time within the Golden Hour Of Trauma Care. In an immature and underdeveloped Trauma System, lack of Post-Crash Care and Delivery of Crash victims safely to Designated tertiary and Trauma Care facilities seem to be non -existent leading to delay in receiving post- crash care. STUDY OBJECTIVE: The objective of the study was to determine Mortality difference amongst Adult Road Traffic Crash patients who are directly transferred or indirectly gone,through various hospitals for definitive management of their injuries within the city of Karachi. METHODS: This was a multicenter, hospital based Prospective Cohort study held at three tertiary care hospitals in Karachi, world\u27s 5th largest populous city, for a period of five months, from April- August, 2016. All adult patients presenting with Serious Injuries (AIS\u3e=3), minimum one body Region were included in the study, excluding Dead On Arrivals(DOA\u27s). Those participants who had underwent interfacility transfers were considered as exposed and directly transferred were considered as unexposed arm. Data was collected through structured questionnaire capturing all information relevant to injury severity, demographics and transfer related information 24/7 in the Emergencies of all three Tertiary care facilities. Primary outcome of the study was 30 day 3 Mortality on Follow up. Survival Analysis was performed to find association of Factors associated with 30 days Mortality of RTC victims with respect to Exposure status. RES ULTS: Out of 201 participants (N=91 in exposed, N=110 in Unexposed group), 14.2% had events(mortality) in Exposed Arm and 15.4% had events in Unexposed arm. We found No difference in Mortality amongst the Exposed and Unexposed Groups(a HR:1.01,CI:0.41- 2.89) .The final Model Predicted significant association of age, GCS,ISS,SBP , victims mode of Tran ;port with 30 day Mortality. There was an increased Risk of Death with increased Age, and Decr easing GCS. Injury severity was associated with an increase in Hazards of death (a HR:1 .07,CI:1.01-1.13) as well. Motorcycle Riders, Pedestrians and pillion riders had a 3 times High er risk of death as compared to occupants of cars, and heavy vehicles(a HR:3.96,CI:1.28- I 2.24). CONCLUSION: We found no significant difference in 30day Mortality of Road Traffic Crash Victims, with respect Mode of Transfer( Direct vs Interfacility)(preliminary data analysis) , however through this study , we found various factors that are associated with 30 day Mortality of RTC Victims, that can be addressed in structuring Post-Crash Care along with Road Safety Policies to reduce Road Traffic Crash Related Mortalities

074 Perceptions, challenges, and experiences of healthcare providers in emergency departments regarding workplace violence during the COVID-19 pandemic: An exploratory qualitative study from an LMIC (a qualitative study protocol)

Statement of Purpose To determine the perceptions, challenges and experiences regarding Workplace Violence faced by ED healthcare providers (Doctors, nurses, and frontline staff) during the COVID-19 pandemic.Methods/Approach We aim to conduct a qualitative exploratory study at two major ED’s of the city namely Aga Khan University Hospital (AKUH) & Jinnah Postgraduate Medical Center (JPMC) involving emergency doctors, nurses, paramedics, admin staff and pharmacists. In-depth interviews will be conducted online using a structured IDI guide. Data will be analyzed using a thematic approach on NVivo computer software.Results This is an abstract for a study protocol. The results will be reported based on the consolidated criteria for reporting qualitative research (COREQ) guidelines.Significance Workplace violence (WPV) against healthcare workers (HCWs) has emerged out as a global issue. Emergency Department (ED) HCWs as front liners are more vulnerable to it due to their nature of work and their profound exposure to medical and social situations. The pandemic has not only brought up a health ordeal, alongside it serves as a challenge in social perspective to HCW’s; ever since fighting the stigmas related to the current pandemic which brought up a wave of antagonism from the patients and their attendants. Thus, an ED’s outcry not yet spoken of. Behind closed doors, what had been an infuriating factor for the population were outraged, irrational religious and social perspectives being quoted and referred to, repeatedly on all prominent medium. Thus, the vulnerable and already exposed population to pandemic, was hovered by societal stigmas to bring down their outrage on HCW’s and already battling ED. We anticipate that through this study we can establish basis of WPV amidst pandemic situation and evidence for future interventions to combat such issues

Perfecting temporary pacemakers in a developing country

Introduction: Transvenous pacemakers are used to temporarily pace heart rhythms in emergent situations or during surgical procedures. This study was conducted to analyze the current success rate of temporary pacemaker insertion in our institution and discover causes for failure to improve the technique.Methodology: : A retrospective cohort study was conducted of 263 patients from 2006 to 2016 who underwent TPM insertion at Aga Khan University Hospital, Karachi.Results: Of 263 patients, 54% were males with a mean age of 63 years. The femoral vein was the preferred site of access with the fluoroscopic approach. The success rate for the study was 97.7%, with one mortality caused by the pacemaker. No significant risk factor was found for the failure of TPM.Discussion: The common site of access used globally for TPM is jugular with the fluoroscopic approach as it is described as the safest approach. However, the data showed no increase in complications for the femoral approach and no case was reported of venous thrombosis.Conclusion: There was no significant effect of anatomical site or technique on the failure of TPM insertion. However, with better training and higher experience of the residents, the complications and rate of failures can be reduced

Predicting mortality in SARS-COV-2 (COVID-19) positive patients in the inpatient setting using a novel deep neural network

Background: The nextwave of COVID-19 pandemic is anticipated to be worse than the initial one and will strain the healthcare systems even more during the winter months. Our aim was to develop a novel machine learning-based model to predict mortality using the deep learning Neo-V framework. We hypothesized this novel machine learning approach could be applied to COVID-19 patients to predict mortality successfully with high accuracy.Methods: We collected clinical and laboratory data prospectively on all adult patients (≥18 years of age) that were admitted in the inpatient setting at Aga Khan University Hospital between February 2020 and September 2020 with a clinical diagnosis of COVID-19 infection. Only patients with a RT-PCR (reverse polymerase chain reaction) proven COVID-19 infection and complete medical records were included in this study. A Novel 3-phase machine learning framework was developed to predict mortality in the inpatients setting. Phase 1 included variable selection that was done using univariate and multivariate Cox-regression analysis; all variables that failed the regression analysis were excluded from the machine learning phase of the study. Phase 2 involved new-variables creation and selection. Phase 3 and final phase applied deep neural networks and other traditional machine learning models like Decision Tree Model, k-nearest neighbor models, etc. The accuracy of these models were evaluated using test-set accuracy, sensitivity, specificity, positive predictive values, negative predictive values and area under the receiver-operating curves.Results: After application of inclusion and exclusion criteria (n=)1214 patients were selected from a total of 1228 admitted patients. We observed that several clinical and laboratory-based variables were statistically significant for both univariate and multivariate analyses while others were not. With most significant being septic shock (hazard ratio [HR], 4.30; 95% confidence interval [CI], 2.91-6.37), supportive treatment (HR, 3.51; 95% CI, 2.01-6.14), abnormal international normalized ratio (INR) (HR, 3.24; 95% CI, 2.28-4.63), admission to the intensive care unit (ICU) (HR, 3.24; 95% CI, 2.22-4.74), treatment with invasive ventilation (HR, 3.21; 95% CI, 2.15-4.79) and laboratory lymphocytic derangement (HR, 2.79; 95% CI, 1.6-4.86). Machine learning results showed our deep neural network (DNN) (Neo-V) model outperformed all conventional machine learning models with test set accuracy of 99.53%, sensitivity of 89.87%, and specificity of 95.63%; positive predictive value, 50.00%; negative predictive value, 91.05%; and area under the receiver-operator curve of 88.5.Conclusion: Our novel Deep-Neo-V model outperformed all other machine learning models. The model is easy to implement, user friendly and with high accuracy

Perceptions, challenges and experiences of frontline healthcare providers in emergency departments regarding workplace violence during the COVID-19 pandemic: A protocol for an exploratory qualitative study from an LMIC

Introduction: Workplace violence (WPV) against Healthcare Workers (HCWs) has emerged as a global issue. Emergency Department (ED) HCWs as front liners are more vulnerable to it due to the nature of their work and exposure to unique medical and social situations. COVID-19 pandemic has led to a surge in the number of cases of WPV against HCWs, especially against ED HCWs. In most cases, the perpetrators of these acts of violence are the patients and their attendants as families. The causes of this rise are multifactorial; these include the inaccurate spread of information and rumours through social media, certain religious perspectives, propaganda and increasing anger and frustration among the general public,ED overcrowding, staff shortages etc. We aim to conduct a qualitative exploratory study among the ED frontline care providers at the two major EDs of Karachi city. The purpose of this study is to determine the perceptions, challenges and experiences regarding WPV faced by ED healthcare providers during the COVID-19 pandemic. Methods and analysis: For this research study, a qualitative exploratory research design will be employed using in-depth interviews and a purposive sampling approach. Data will be collected using in-depth interviews from study participants working at the EDs of Jinnah Postgraduate Medical Centre (JPMC) and the Aga Khan University Hospital(AKUH) Karachi, Pakistan. Thestudy data will be analysed thematically using NVivo V.12 Plus software. Ethics and dissemination: The ethical approval for this study was obtained from the Aga Khan University Ethical Review Committee and from Jinnah postgraduate Medical Center (JPMC). The results of the study will be disseminated to the scientific community and to the research subjects participating in the study.The findings of this study will help to explore the perceptions of ED healthcare providers regarding WPV during the COVID-19 pandemic and provide a better understanding of study participant\u27s\u27 challenges concerning WPV during the COVID-19 pandemic

A slight variability in anthropometric parameters but a significant delay in sexual maturation rating and decreased hormonal parameters in patients with delayed puberty

Objectives: The present study was designed to compare anthropometric parameters, sexual maturation rating (SMR) and plasma follicle stimulating hormone (FSH), luteinizing hormone (LH) and testosterone (T) levels in male delayed puberty patients and age matched healthy controls and determine whether a difference exists between these parameters before and after 18 years of age in delayed puberty patients. Methodology: Anthropometric parameters (height, weight, body mass index (BMI), bone age), SMR (penile length, testicular volume, pubic and facial hair stage) and plasma concentrations of FSH, LH and T were determined through respective ELISA in 37 sporadic delayed puberty male patients of 14-23 years and 55 age matched controls visiting Shifa International Hospitals Ltd., Islamabad, Pakistan Institute of Medical Sciences, Islamabad and Military Hospital, Rawalpindi, Pakistan. Data were interpreted using Student’s t-test and ANOVA. Results: The height of delayed puberty patients was lower than controls from 14-17 years, whereas weight of delayed puberty patients was slightly more than controls from 17-23 years; most of patients were in over-weight category. Bone age of most of patients was slightly delayed than chronological age.&nbsp

A Slight Variability in Anthropometric Parameters But A Significant Delay in Sexual Maturation Rating and Decreased Hormonal Parameters in Patients with Delayed Puberty

Objectives: The present study was designed to compare anthropometric parameters, sexual maturation rating (SMR) and plasma follicle stimulating hormone (FSH), luteinizing hormone (LH) and testosterone (T) levels in male delayed puberty patients and age matched healthy controls and determine whether a difference exists between these parameters before and after 18 years of age in delayed puberty patients. Methodology: Anthropometric parameters (height, weight, body mass index (BMI), bone age), SMR (penile length, testicular volume, pubic and facial hair stage) and plasma concentrations of FSH, LH and T were determined through respective ELISA in 37 sporadic delayed puberty male patients of 14-23 years and 55 age matched controls visiting Shifa International Hospitals Ltd., Islamabad, Pakistan Institute of Medical Sciences, Islamabad and Military Hospital, Rawalpindi, Pakistan. Data were interpreted using Student's t-test and ANOVA. Results: The height of delayed puberty patients was lower than controls from 14-17 years, whereas weight of delayed puberty patients was slightly more than controls from 17-23 years; most of patients were in over-weight category. Bone age of most of patients was slightly delayed than chronological age.&nbsp

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population