Background: Knowledge of infection prevention and control (IPC) procedures among healthcare workers (HCWs) is crucial for effective IPC. Compliance with IPC measures has critical implications for HCWs safety, patient protection and the care environment.Aims: To discuss the body of available literature regarding HCWs' knowledge of IPC and highlight potential factors that may influence compliance to IPC precautions.Design: A systematic review. A protocol was developed based on the Preferred Reporting Items for Systematic reviews and Meta-Analysis [PRISMA] statement.Data sources: Electronic databases (PubMed, CINAHL, Embase, Proquest, Wiley online library, Medline, and Nature) were searched from 1 January 2006 to 31 January 2021 in the English language using the following keywords alone or in combination:knowledge, awareness, healthcare workers, infection, compliance, comply, control, prevention, factors. 3417 papers were identified and 30 papers were included in the review.Results: Overall, the level of HCW knowledge of IPC appears to be adequate, good, and/or high concerning standard precautions, hand hygiene, and care pertaining to urinary catheters. Acceptable levels of knowledge were also detected in regards to IPC measures for specific diseases including TB, MRSA, MERS-CoV, COVID-19 and Ebola. However, gaps were identified in several HCWs' knowledge concerning occupational vaccinations, the modes of transmission of infectious diseases, and the risk of infection from needle stick and sharps injuries. Several factors for noncompliance surrounding IPC guidelines are discussed, as are recommendations for improving adherence to those guidelines.Conclusion: Embracing a multifaceted approach towards improving IPC-intervention strategies is highly suggested. The goal being to improve compliance among HCWs with IPC measures is necessary.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a severe pandemic of the current century. The vicious tentacles of the disease have been disseminated worldwide with unknown complications and repercussions. Advanced COVID-19 syndrome is characterized by the uncontrolled and elevated release of pro-inflammatory cytokines and suppressed immunity, leading to the cytokine storm. The uncontrolled and dysregulated secretion of inflammatory and pro-inflammatory cytokines is positively associated with the severity of the viral infection and mortality rate. The secretion of various pro-inflammatory cytokines such as TNF-α, IL-1, and IL-6 leads to a hyperinflammatory response by recruiting macrophages, T and B cells in the lung alveolar cells. Moreover, it has been hypothesized that immune cells such as macrophages recruit inflammatory monocytes in the alveolar cells and allow the production of large amounts of cytokines in the alveoli, leading to a hyperinflammatory response in severely ill patients with COVID-19. This cascade of events may lead to multiple organ failure, acute respiratory distress, or pneumonia. Although the disease has a higher survival rate than other chronic diseases, the incidence of complications in the geriatric population are considerably high, with more systemic complications. This review sheds light on the pivotal roles played by various inflammatory markers in COVID-19-related complications. Different molecular pathways, such as the activation of JAK and JAK/STAT signaling are crucial in the progression of cytokine storm; hence, various mechanisms, immunological pathways, and functions of cytokines and other inflammatory markers have been discussed. A thorough understanding of cytokines’ molecular pathways and their activation procedures will add more insight into understanding immunopathology and designing appropriate drugs, therapies, and control measures to counter COVID-19. Recently, anti-inflammatory drugs and several antiviral drugs have been reported as effective therapeutic drug candidates to control hypercytokinemia or cytokine storm. Hence, the present review also discussed prospective anti-inflammatory and relevant immunomodulatory drugs currently in various trial phases and their possible implications.

Background: Coinfection with bacteria, fungi, and respiratory viruses in SARS-CoV-2 is of particular importance due to the possibility of increased morbidity and mortality. In this meta-analysis, we calculated the prevalence of such coinfections. Methods: Electronic databases were searched from 1 December 2019 to 31 March 2021. Effect sizes of prevalence were pooled with 95% confidence intervals (CIs). To minimize heterogeneity, we performed sub-group analyses. Results: Of the 6189 papers that were identified, 72 articles were included in the systematic review (40 case series and 32 cohort studies) and 68 articles (38 case series and 30 cohort studies) were included in the meta-analysis. Of the 31,953 SARS-CoV-2 patients included in the meta-analysis, the overall pooled proportion who had a laboratory-confirmed bacterial infection was 15.9% (95% CI 13.6–18.2, n = 1940, 49 studies, I² = 99%, p < 0.00001), while 3.7% (95% CI 2.6–4.8, n = 177, 16 studies, I² = 93%, p < 0.00001) had fungal infections and 6.6% (95% CI 5.5–7.6, n = 737, 44 studies, I² = 96%, p < 0.00001) had other respiratory viruses. SARS-CoV-2 patients in the ICU had higher co-infections compared to ICU and non-ICU patients as follows: bacterial (22.2%, 95% CI 16.1–28.4, I² = 88% versus 14.8%, 95% CI 12.4–17.3, I² = 99%), and fungal (9.6%, 95% CI 6.8–12.4, I² = 74% versus 2.7%, 95% CI 0.0–3.8, I² = 95%); however, there was an identical other respiratory viral co-infection proportion between all SARS-CoV-2 patients [(ICU and non-ICU) and the ICU only] (6.6%, 95% CI 0.0–11.3, I² = 58% versus 6.6%, 95% CI 5.5–7.7, I² = 96%). Funnel plots for possible publication bias for the pooled effect sizes of the prevalence of coinfections was asymmetrical on visual inspection, and Egger’s tests confirmed asymmetry (p values < 0.05). Conclusion: Bacterial co-infection is relatively high in hospitalized patients with SARS-CoV-2, with little evidence of S. aureus playing a major role. Knowledge of the prevalence and type of co-infections in SARS-CoV-2 patients may have diagnostic and management implications.

BACKGROUND: This narrative review aims to explore the current state and future perspective of artificial intelligence (AI) in respiratory care. The objective is to provide insights into the potential impact of AI in this field. METHODS: A comprehensive analysis of relevant literature and research studies was conducted to examine the applications of AI in respiratory care and identify areas of advancement. The analysis included studies on remote monitoring, early detection, smart ventilation systems, and collaborative decision-making. RESULTS: The obtained results highlight the transformative potential of AI in respiratory care. AI algorithms have shown promising capabilities in enabling tailored treatment plans based on patient-specific data. Remote monitoring using AI-powered devices allows for real-time feedback to health-care providers, enhancing patient care. AI algorithms have also demonstrated the ability to detect respiratory conditions at an early stage, leading to timely interventions and improved outcomes. Moreover, AI can optimize mechanical ventilation through continuous monitoring, enhancing patient comfort and reducing complications. Collaborative AI systems have the potential to augment the expertise of health-care professionals, leading to more accurate diagnoses and effective treatment strategies. CONCLUSION: By improving diagnosis, AI has the potential to revolutionize respiratory care, treatment planning, and patient monitoring. While challenges and ethical considerations remain, the transformative impact of AI in this domain cannot be overstated. By leveraging the advancements and insights from this narrative review, health-care professionals and researchers can continue to harness the power of AI to improve patient outcomes and enhance respiratory care practices. IMPROVEMENTS: Based on the findings, future research should focus on refining AI algorithms to enhance their accuracy, reliability, and interpretability. In addition, attention should be given to addressing ethical considerations, ensuring data privacy, and establishing regulatory frameworks to govern the responsible implementation of AI in respiratory care.

Background: Currently there is no systematic review and meta-analysis of the global incidence rates of anaphylactic and nonanaphylactic reactions to SARS-CoV-2 vaccines in the general adult population.Objectives: To estimate the incidence rates of anaphylactic and nonanaphylactic reactions after COVID-19 vaccines and describe the demographic and clinical characteristics, triggers, presenting signs and symptoms, treatment and clinical course of confirmed cases.Design: A systematic review and meta-analysis. Preferred Reporting Items for Systematic Reviews and Meta-Analyses [PRISMA] statement was followed.Methods: Electronic databases (Proquest, Medline, Embase, Pubmed, CINAHL, Wiley online library, and Nature) were searched from 1 December 2020 to 31 May 2021 in the English language using the following keywords alone or in combination:anaphylaxis,non-anaphylaxis,anaphylactic reaction,nonanaphylactic reaction,anaphylactic/anaphylactoid shock,hypersensitivity,allergy reaction,allergic reaction,immunology reaction,immunologic reaction,angioedema,loss of consciousness,generalized erythema,urticaria,urticarial rash,cyanosis,grunting,stridor,tachypnoea,wheezing,tachycardia,abdominal pain,diarrhea,nausea,vomitingandtryptase. We included studies in adults of all ages in all healthcare settings. Effect sizes of prevalence were pooled with 95% confidence intervals (CIs). To minimize heterogeneity, we performed sub-group analyses.Results: Of the 1,734 papers that were identified, 26 articles were included in the systematic review (8 case report, 5 cohort, 4 case series, 2 randomized controlled trial and 1 randomized cross-sectional studies) and 14 articles (1 cohort, 2 case series, 1 randomized controlled trial and 1 randomized cross-sectional studies) were included in meta-analysis. Studies involving 26,337,421 vaccine recipients [Pfizer-BioNTech (n = 14,505,399) and Moderna (n = 11,831,488)] were analyzed. The overall pooled prevalence estimate of anaphylaxis to both vaccines was 5.0 (95% CI 2.9 to 7.2,I² = 81%,p = < 0.0001), while the overall pooled prevalence estimate of nonanaphylactic reactions to both vaccines was 53.9 (95% CI 0.0 to 116.1,I² = 99%,p = < 0.0001). Vaccination with Pfizer-BioNTech resulted in higher anaphylactic reactions compared to Moderna (8.0, 95% CI 0.0 to 11.3,I² = 85% versus 2.8, 95% CI 0.0 to 5.7,I² = 59%). However, lower incidence of nonanaphylactic reactions was associated with Pfizer-BioNTech compared to Moderna (43.9, 95% CI 0.0 to 131.9,I² = 99% versus 63.8, 95% CI 0.0 to 151.8,I² = 98%). The funnel plots for possible publication bias for the pooled effect sizes to determine the incidence of anaphylaxis and nonanaphylactic reactions associated with mRNA COVID-19 immunization based on mRNA vaccine type appeared asymmetrical on visual inspection, and Egger’s tests confirmed asymmetry by producingpvalues < 0.05. Across the included studies, the most commonly identified risk factors for anaphylactic and nonanaphylactic reactions to SARS-CoV-2 vaccines were female sex and personal history of atopy. The key triggers to anaphylactic and nonanaphylactic reactions identified in these studies included foods, medications, stinging insects or jellyfish, contrast media, cosmetics and detergents, household products, and latex. Previous history of anaphylaxis; and comorbidities such as asthma, allergic rhinitis, atopic and contact eczema/dermatitis and psoriasis and cholinergic urticaria were also found to be important.Conclusion: The prevalence of COVID-19 mRNA vaccine-associated anaphylaxis is very low; and nonanaphylactic reactions occur at higher rate, however, cutaneous reactions are largely self-limited. Both anaphylactic and nonanaphylactic reactions should not discourage vaccination.

Fungal infections are becoming one of the main causes of morbidity and mortality in people with weakened immune systems. Mycoses are becoming more common, despite greater knowledge and better treatment methods, due to the regular emergence of resistance to the antifungal medications used in clinical settings. Antifungal therapy is the mainstay of patient management for acute and chronic mycoses. However, the limited availability of antifungal drug classes limits the range of available treatments. Additionally, several drawbacks to treating mycoses include unfavourable side effects, a limited activity spectrum, a paucity of targets, and fungal resistance, all of which continue to be significant issues in developing antifungal drugs. The emergence of antifungal drug resistance has eliminated accessible drug classes as treatment choices, which significantly compromises the clinical management of fungal illnesses. In some situations, the emergence of strains resistant to many antifungal medications is a major concern. Although new medications have been developed to address this issue, antifungal drug resistance has grown more pronounced, particularly in patients who need long-term care or are undergoing antifungal prophylaxis. Moreover, the mechanisms that cause resistance must be well understood, including modifications in drug target affinities and abundances, along with biofilms and efflux pumps that diminish intracellular drug levels, to find novel antifungal drugs and drug targets. In this review, different classes of antifungal agents, and their resistance mechanisms, have been discussed. The latter part of the review focuses on the strategies by which we can overcome this serious issue of antifungal resistance in humans.