Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates.

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI's applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor's prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains.

Safety and Efficacy of Convalescent Plasma for Severe COVID-19: Interim Report of a Multicenter Phase II Study from Saudi Arabia.

OBJECTIVE: To present the interim findings from a national study investigating the safety and efficacy of convalescent plasma (CP) containing detectable IgG antibodies as a treatment strategy for severe coronavirus disease 2019 (COVID-19). TRIAL DESIGN AND PARTICIPANTS: An open label, two-arm, phase-II clinical trial conducted across 22 hospitals from Saudi Arabia. The intervention group included 40 adults (aged ≥18 years) with confirmed severe COVID-19 and the control group included 124 patients matched using propensity score for age, gender, intubation status, and history of diabetes and/or hypertension. Intervention group included those (a) with severe symptoms (dyspnea; respiratory rate, ≥30/min; SpO2, ≤93%, PaO2/FiO2 ratio, <300; and/or lung infiltrates >50% within 24-48 h), (b) requiring intensive care unit (ICU) care or (c) experiencing life-threatening conditions. The control group included confirmed severe COVID-19 patients of similar characteristics who did not consent for CP infusion or were not able to receive CP due to its nonavailability. INTERVENTIONS: The intervention group participants were infused 300 ml (200-400 ml/treatment dose) CP at least once, and if required, daily for up to 5 sessions, along with receiving the best standard of care. The control group only received the best standard of care. OUTCOMES: The primary endpoints were safety and ICU length of stay (LOS). The secondary endpoints included 30-day mortality, days on mechanical ventilation and days to clinical recovery. RESULTS: CP transfusion did not result in any adverse effects. There was no difference in the ICU LOS (median 8 days in both groups). The mortality risk was lower in the CP group: 13% absolute risk reduction (P = 0.147), hazard ratio (95% confidence interval): 0.554 (0.299-1.027; P = 0.061) by log-rank test. There was no significant difference in the days on mechanical ventilation and days to clinical recovery. CONCLUSION: CP containing detectable antibodies is a safe strategy and may result in a decrease in mortality in patients with severe COVID-19. The results of the completed trial with a larger study sample would provide more clarity if this difference in mortality is significant. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04347681; Saudi Clinical Trials Registry No.: 20041102.

The impact of the coexistence of mycobacterium avium with mycobacterium tuberculosis on the result of GeneXpert and MGIT susceptibility test.

Rapid tests to diagnose tuberculosis relies on molecular detection of the M. tuberculosis. GeneXpert MTB/RIF test identifies M. tuberculosis and rifampicin resistance. We present a case of simultaneous coinfection with M. tuberculosis and M. avium. M. tuberculosis was detected in the sputum by PCR GeneXpert method. Unrecognized coexistence of M. tuberculosis and M. avium modified the results of drug susceptibility tests making the primary identification of M. tuberculosis as multi-drug resistant strain. We performed in vitro experiments to investigate the effect of the coexistence of M. avium with M. tuberculosis on the results of GeneXpert method, and drug susceptibility test.