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

Peer-assisted learning (PAL): An innovation aimed at engaged learning for undergraduate medical students

Objective: To evaluate the effectiveness of Peer Assisted Learning in teaching at undergraduate level and to assess its effects on Peer Leaders and Peer Learners.Methods: The cross-sectional study was conducted at the Aga Khan University, Karachi, from May to October 2017, and comprised Peer Learners who were trained by faculty members in workshops and pre-run of experiments. Students were divided into two groups; Group A had Peer Learners taught by Peer Leaders, and Group B had those taught by trained lab technologists. Knowledge of the groups was assessed by a quiz using Kahoot. Post-session feedback questionnaires were also filled by the participants. Data was analysed using SPSS 23.Results: There were 10 Peer Leaders with a mean age of 19.5±0.85 years, and 62 Peer Learners with a mean age of 19.08±0.81 years. Among the learners, there were 35(56.5%) males and 27(43.5%) females. Post-session assessment showed a significant difference in the test performance by the two groups (p\u3c0.05). Feedback indicated that the learners found Peer Leaders more accessible than lab staff, leading to enhanced understanding of the subject.Conclusions: Peer-Assisted Learning was found to promote learning by creating an informal student-friendly learning environment

Association between proton pump inhibitor therapy and clostridium difficile infection: a contemporary systematic review and meta-analysis.

Abstract Introduction Emerging epidemiological evidence suggests that proton pump inhibitor (PPI) acid-suppression therapy is associated with an increased risk of Clostridium difficile infection (CDI). Methods Ovid MEDLINE, EMBASE, ISI Web of Science, and Scopus were searched from 1990 to January 2012 for analytical studies that reported an adjusted effect estimate of the association between PPI use and CDI. We performed random-effect meta-analyses. We used the GRADE framework to interpret the findings. Results We identified 47 eligible citations (37 case-control and 14 cohort studies) with corresponding 51 effect estimates. The pooled OR was 1.65, 95% CI (1.47, 1.85), I2 = 89.9%, with evidence of publication bias suggested by a contour funnel plot. A novel regression based method was used to adjust for publication bias and resulted in an adjusted pooled OR of 1.51 (95% CI, 1.26–1.83). In a speculative analysis that assumes that this association is based on causality, and based on published baseline CDI incidence, the risk of CDI would be very low in the general population taking PPIs with an estimated NNH of 3925 at 1 year. Conclusions In this rigorously conducted systemic review and meta-analysis, we found very low quality evidence (GRADE class) for an association between PPI use and CDI that does not support a cause-effect relationship

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

A review of the molecular mechanisms of traumatic brain injury

Traumatic brain injury (TBI) refers to any insult to the brain resulting in primary (direct) and secondary (indirect) damage to the brain parenchyma. Secondary damage is often linked to the molecular mechanisms that occur post TBI and result in excitotoxicity, neuroinflammation and cytokine damage, oxidative damage, and eventual cell death as prominent mechanisms of cell damage. We present a review highlighting the relation of each of these mechanisms with TBI, their mode of damaging brain tissue, and therapeutic correlation. We also mention the long-term sequelae and their pathophysiology in relation to TBI focusing on Parkinson disease, Alzheimer disease, epilepsy, and chronic traumatic encephalopathy. Understanding of the molecular mechanisms is important in order to realize the secondary and long-term sequelae that follow primary TBI and to devise targeted therapy for quick recovery accordingly

Avascular Necrosis and time to surgery for unstable slipped capital femoral epiphysis: a systematic review and meta-analysis

Background: Avascular necrosis (AVN) is a well-known complication of unstable slipped capital femoral epiphysis (SCFE) and its cause is multifactorial. Higher AVN rates have been reported with surgery undertaken between 24 hours to 7 days from the onset of symptoms. The current evidence regarding time to surgery and AVN rate remains unclear. The aim of our study was to investigate the rate of AVN and time to surgery in unstable SCFE. Methods: A literature search of several databases was conducted. Eligibility criteria included all studies that reported AVN rates and time to surgery in unstable SCFE patients. We performed a meta-analysis using a random-effects model to pool the rate of AVN in unstable SCFE using different time to surgery subgroups (≤24 h, 24 h - 7 d and >7 d). Descriptive, quantitative and qualitative data were extracted. Results: Twelve studies matched our eligibility criteria. In total, there were 434 unstable SCFE of which 244 underwent closed reduction (CR). The pooled AVN rates were 24% [95% CI: 16%-35%] and 29% [95% CI: 16%-45%] for the total and CR groups, respectively. The highest AVN rates were with surgery between 24 hours to 7 days, 42% and 54% for the total and CR groups, respectively. The lowest rates of AVN were with time to surgery ≤24 hours (22% and 21% respectively) and >7 days (18% and 29% respectively). These differences were not statistically significant. There was significant subgroup heterogeneity which was highest in the 24 hours - 7 days subgroup and lowest in the >7 days subgroup. Conclusions: The cumulative evidence was not conclusive for an association between AVN rate and time to surgery. The overall AVN rates were lower in unstable SCFE patients who had surgery ≤24 hours and >7 days. However, treatment techniques were very variable and there was significant heterogeneity in the included studies. Multi-centre prospective studies are required with well-defined time to surgery outcomes. Level of Evidence: Level III/IV