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: 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.

Human Parainfluenza Virus (HPIV) Type-1, which is an anti-sense ribonucleic acid (RNA) virus belonging to the paramyxoviridae family, induces upper and lower respiratory tract infections. The infections caused by the HPIV Type-1 virus are usually confined to northwestern regions of America. HPIV-1 causes infections through the virulence of the hemagglutinin-neuraminidase (HN) protein, which plays a key role in the attachment of the viral particle with the host’s receptor cells. To the best of our knowledge, there is no effective antiviral drugs or vaccines being developed to combat the infection caused by HPIV-1. In the current study, a multiple epitope-based vaccine was designed against HPIV-1 by taking the viral HN protein as a probable vaccine candidate. The multiple epitopes were selected in accordance with their allergenicity, antigenicity and toxicity scoring. The determined epitopes of the HN protein were connected simultaneously using specific conjugates along with an adjuvant to construct the subunit vaccine, with an antigenicity score of 0.6406. The constructed vaccine model was docked with various Toll-like Receptors (TLRs) and was computationally cloned in a pET28a (+) vector to analyze the expression of vaccine sequence in the biological system. Immune stimulations carried out by the C-ImmSim Server showed an excellent result of the body’s defense system against the constructed vaccine model. The AllerTop tool predicted that the construct was non-allergen with and without the adjuvant sequence, and the VaxiJen 2.0 with 0.4 threshold predicted that the construct was antigenic, while the Toxinpred predicted that the construct was non-toxic. Protparam results showed that the selected protein was stable with 36.48 instability index (II) scores. The Grand average of Hydropathicity or GRAVY score indicated that the constructed protein was hydrophilic in nature. Aliphatic index values (93.53) confirmed that the construct was thermostable. This integrated computational approach shows that the constructed vaccine model has a potential to combat laryngotracheobronchitis infections caused by HPIV-I.

The high rates of bacterial infections affect the economy worldwide by contributing to the increase in morbidity and treatment costs. The present cross-sectional study was carried out to evaluate the prevalence of bacterial infection in urinary tract infection (UTI) patients and to evaluate the antimicrobial resistance rate (AMR) in a Tertiary Care Hospital in Lahore, Pakistan. The study was conducted for the period of one year from January 2020 to December 2020. A total of 1899 different clinical samples were collected and examined for bacterial cultures using standard procedures. Samples were inoculated on different culture media to isolate bacterial isolates and for identification and susceptibility testing. A total of 1107/1899 clinical samples were positive for Staphylococcus aureus (S. aureus), Pseudomonas aeruginosa (P. aeruginosa), Escherichia coli (E. coli) and other bacterial isolates. Methicillin-resistant S. aureus (MRSA) prevalence was 16.93% from these positive cases. MRSA strains were found to be highly resistant to amikacin, clindamycin, fusidic acid, gentamicin and tobramycin, while highest sensitivity was noted against vancomycin (100%) and linezolid (100%). MRSA and high rates of multidrug resistance (MDR) pose a serious therapeutic burden to critically ill patients. A systematic and concerted effort is essential to rapidly identify high-risk patients and to reduce the burden of AMR.

Background: Coinfection with bacteria, fungi, and respiratory viruses has been described as a factor associated with more severe clinical outcomes in children with COVID-19. Such coinfections in children with COVID-19 have been reported to increase morbidity and mortality. Objectives: To identify the type and proportion of coinfections with SARS-CoV-2 and bacteria, fungi, and/or respiratory viruses, and investigate the severity of COVID-19 in children. Methods: For this systematic review and meta-analysis, we searched ProQuest, Medline, Embase, PubMed, CINAHL, Wiley online library, Scopus, and Nature through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for studies on the incidence of COVID-19 in children with bacterial, fungal, and/or respiratory coinfections, published from 1 December 2019 to 1 October 2022, with English language restriction. Results: Of the 169 papers that were identified, 130 articles were included in the systematic review (57 cohort, 52 case report, and 21 case series studies) and 34 articles (23 cohort, eight case series, and three case report studies) were included in the meta-analysis. Of the 17,588 COVID-19 children who were tested for co-pathogens, bacterial, fungal, and/or respiratory viral coinfections were reported (n = 1633, 9.3%). The median patient age ranged from 1.4 months to 144 months across studies. There was an increased male predominance in pediatric COVID-19 patients diagnosed with bacterial, fungal, and/or viral coinfections in most of the studies (male gender: n = 204, 59.1% compared to female gender: n = 141, 40.9%). The majority of the cases belonged to White (Caucasian) (n = 441, 53.3%), Asian (n = 205, 24.8%), Indian (n = 71, 8.6%), and Black (n = 51, 6.2%) ethnicities. The overall pooled proportions of children with laboratory-confirmed COVID-19 who had bacterial, fungal, and respiratory viral coinfections were 4.73% (95% CI 3.86 to 5.60, n = 445, 34 studies, I² 85%, p < 0.01), 0.98% (95% CI 0.13 to 1.83, n = 17, six studies, I² 49%, p < 0.08), and 5.41% (95% CI 4.48 to 6.34, n = 441, 32 studies, I² 87%, p < 0.01), respectively. Children with COVID-19 in the ICU had higher coinfections compared to ICU and non-ICU patients, as follows: respiratory viral (6.61%, 95% CI 5.06–8.17, I² = 0% versus 5.31%, 95% CI 4.31–6.30, I² = 88%) and fungal (1.72%, 95% CI 0.45–2.99, I² = 0% versus 0.62%, 95% CI 0.00–1.55, I² = 54%); however, COVID-19 children admitted to the ICU had a lower bacterial coinfection compared to the COVID-19 children in the ICU and non-ICU group (3.02%, 95% CI 1.70–4.34, I² = 0% versus 4.91%, 95% CI 3.97–5.84, I² = 87%). The most common identified virus and bacterium in children with COVID-19 were RSV (n = 342, 31.4%) and Mycoplasma pneumonia (n = 120, 23.1%). Conclusion: Children with COVID-19 seem to have distinctly lower rates of bacterial, fungal, and/or respiratory viral coinfections than adults. RSV and Mycoplasma pneumonia were the most common identified virus and bacterium in children infected with SARS-CoV-2. Knowledge of bacterial, fungal, and/or respiratory viral confections has potential diagnostic and treatment implications in COVID-19 children.

Background: One possible reason for increased mortality due to SARS-CoV-2 in patients with diabetes is from the complication of diabetic ketoacidosis (DKA). Objectives: To re-evaluate the association of SARS-CoV-2 and development of DKA and analyse the demographic and biochemical parameters and the clinical outcomes in COVID-19 patients with DKA. Design: A systematic review and meta-analysis. Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement was followed. Methods: Electronic databases (Proquest, Medline, Embase, Pubmed, CINAHL, Wiley online library, Scopus and Nature) were searched from 1 December 2019 to 30 June 2021 in the English language using the following keywords alone or in combination: COVID-19 OR SARS-CoV-2 AND diabetic ketoacidosis OR DKA OR ketosis OR ketonemia OR hyperglycaemic emergency OR hyperglycaemic crisis. We included studies in adults and children of all ages in all healthcare settings. Binary logistic regression model was used to explore the effect of various demographic and biochemical parameters variables on patient’s final treatment outcome (survival or death). Results: Of the 484 papers that were identified, 68 articles were included in the systematic review and meta-analysis (54 case report, 10 case series, and 4 cohort studies). Studies involving 639 DKA patients with confirmed SARS-CoV-2 [46 (7.2%) were children and 334 (52.3%) were adults] were analyzed. The median or mean patient age ranged from < 1 years to 66 years across studies. Most of the patients (n = 309, 48.3%) had pre-existing type 2 diabetes mellitus. The majority of the patients were male (n = 373, 58.4%) and belonged to Hispanic (n = 156, 24.4%) and black (n = 98, 15.3%) ethnicity. The median random blood glucose level, HbA1c, pH, bicarbonate, and anion gap in all included patients at presentation were 507 mg/dl [IQR 399–638 mg/dl], 11.4% [IQR 9.9–13.5%], 7.16 [IQR 7.00–7.22], 10 mmol/l [IQR 6.9–13 mmol/l], and 24.5 mEq/l [18–29.2 mEq/l]; respectively. Mortality rate was [63/243, 25.9%], with a majority of death in patients of Hispanic ethnicity (n = 17, 27%; p = 0.001). The odd ratios of death were significantly high in patients with pre-existing diabetes mellitus type 2 [OR 5.24, 95% CI 2.07–15.19; p = 0.001], old age (≥ 60 years) [OR 3.29, 95% CI 1.38–7.91; p = 0.007], and male gender [OR 2.61, 95% CI 1.37–5.17; p = 0.004] compared to those who survived. Conclusion: DKA is not uncommon in SARS-CoV-2 patients with diabetes mellitus and results in a mortality rate of 25.9%. Mortality key determinants in DKA patients with SARS-CoV-2 infection are individuals with pre-existing diabetes mellitus type 2, older age [≥ 60 years old], male gender, BMI ≥ 30, blood glucose level > 1000 mg/dl, and anion gap ≥ 30 mEq/l.