Complex interplay between PRRSV-1 genetic diversity, coinfections and antimicrobial use influences performance parameters in post-weaning pigs

Porcine reproductive and respiratory syndrome (PRRS) is one of the main diseases of pigs, leading to large economic losses in swine production worldwide. PRRSV high mutation rate and low cross-protection between strains make PRRS control challenging. Through a semi-longitudinal approach, we analysed the relationships among performance parameters, PRRSV-1 genetic diversity, coinfections and antimicrobial use (AMU) in pig nurseries. We collected data over the course of five years in five PRRS-positive nurseries belonging to an Italian multisite operation, for a total of 86 batches and over 200,000 weaners involved. The farm experienced a severe PRRS outbreak in the farrowing unit at the onset of the study, but despite adopting vaccination of all sows, batch-level losses in nurseries in the following years remained constantly high (mean±SE: 11.3 ± 0.5 %). Consistently with previous studies, our phylogenetic analysis of ORF 7 sequences highlighted the peculiarity of strains circulating in Italy. Greater genetic distances between the strain circulating in a weaners' batch and strains from the farrowing unit and the previous batch were associated with increased mortality (p < 0.0001). All the respiratory and enteric coinfections contributed to an increase in losses (all p < 0.026), with secondary infections by Streptococcus suis and enteric bacteria also inducing an increase in AMU (both p < 0.041). Our findings highlight that relying solely on sows' vaccination is insufficient to contain PRRS losses, and the implementation of rigorous biosecurity measures is pivotal to limit PRRSV circulation among pig flows and consequently minimise the risk of exposure to genetically diverse strains that would increase production costs.

IL-6, IL-10, sFas, granulysin and indicators of intestinal permeability as early biomarkers for a fatal outcome in COVID-19

The clinical presentation of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ranges between mild respiratory symptoms and a severe disease that shares many of the features of sepsis. Sepsis is a deregulated response to infection that causes life-threatening organ failure. During sepsis, the intestinal epithelial cells are affected, causing an increase in intestinal permeability and allowing microbial translocation from the intestine to the circulation, which exacerbates the inflammatory response. Here we studied patients with moderate, severe and critical COVID-19 by measuring a panel of molecules representative of the innate and adaptive immune responses to SARS-CoV-2, which also reflect the presence of systemic inflammation and the state of the intestinal barrier. We found that non-surviving COVID-19 patients had higher levels of low-affinity anti-RBD IgA antibodies than surviving patients, which may be a response to increased microbial translocation. We identified sFas and granulysin, in addition to IL-6 and IL-10, as possible early biomarkers with high sensitivity (>73 %) and specificity (>51 %) to discriminate between surviving and non-surviving COVID-19 patients. Finally, we found that the microbial metabolite d-lactate and the tight junction regulator zonulin were increased in the serum of patients with severe COVID-19 and in COVID-19 patients with secondary infections, suggesting that increased intestinal permeability may be a source of secondary infections in these patients. COVID-19 patients with secondary infections had higher disease severity and mortality than patients without these infections, indicating that intestinal permeability markers could provide complementary information to the serum cytokines for the early identification of COVID-19 patients with a high risk of a fatal outcome.

Secondary respiratory early and late infections in mechanically ventilated patients with COVID-19

Background

Patients with COVID-19 receiving mechanical ventilation may become aggravated with a secondary respiratory infection. The aim of this study was to describe secondary respiratory infections, their predictive factors, and outcomes in patients with COVID-19 requiring mechanical ventilation.

Methods

A cohort study was carried out in a single tertiary hospital in Santiago, Chile, from 1st June to 31st July 2020. All patients with COVID-19 admitted to the intensive care unit that required mechanical ventilation were included.

Results

A total of 175 patients were enrolled, of which 71 (40.6%) developed at least one secondary respiratory infection during follow-up. Early and late secondary infections were diagnosed in 1.7% and 31.4% respectively. Within late secondary infections, 88% were bacterial, 10% were fungal, and 2% were of viral origin. One-third of isolated bacteria were multidrug-resistant. Bivariate analysis showed that the history of corticosteroids used before admission and the use of dexamethasone during hospitalization were associated with a higher risk of secondary infections (p = 0.041 and p = 0.019 respectively). Multivariate analysis showed that for each additional day of mechanical ventilation, the risk of secondary infection increases 1.1 times (_adOR = 1.07; 95% CI 1.02–1.13, p = 0.008)

Conclusions

Patients with COVID-19 admitted to the intensive care unit and requiring mechanical ventilation had a high rate of secondary infections during their hospital stay. The number of days on MV was a risk factor for acquiring secondary respiratory infections.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07743-2.

Effects of corticosteroids treatment in patients with Severe Fever with Thrombocytopenia Syndrome:A single-center retrospective cohort study

OBJECTIVES

To evaluate the effect and safety of corticosteroids(CS) treatment in patients with severe fever with thrombocytopenia syndrome(SFTS).

METHODS

Patients with and without CS were retrospectively compared by COX regression and 1:1 propensity score matching analysis to evaluate the effects of CS on mortality and secondary infections in patients with SFTS.

RESULTS

A total of 467 SFTS patients were enrolled in the cohort study, there were 52 fatal cases and 415 nonfatal cases,the overall fatality rate was 11.1%. The mortality were observed in 36/144 (25%) and 16/323 (5%) patients in the CS-treated and non-CS-treated groups,respectively (P<0.001).Multivariate cox regression analysis showed that the difference was not statistically significant for CS treatment in the fatality (P>0.05, aHR 1.003, 95%CI 0.49-2.06).Difference in survival time between CS-treated and non-CS-treated groups after propensity score matching had no statistically significant (Log-Rank test P=0.390),whereas there was a significant difference in secondary infections between the CS-treated and non-CS-treated groups (P=0.007).

CONCLUSIONS

Although the CS treatment had no influence on fatality in patients with SFTS, it increased the risk of secondary infections.Administration of CS in patients with SFTS should be carefully considered and take into account the balance between therapeutic efficacy and adverse effects.

Alternative Treatment Strategies for Secondary Bacterial and Fungal Infections Associated with COVID-19

Antimicrobials are essential for combating infectious diseases. However, an increase in resistance to them is a major cause of concern. The empirical use of drugs in managing COVID-19 and the associated secondary infections have further exacerbated the problem of antimicrobial resistance. Hence, the situation mandates exploring and developing efficient alternatives for the treatment of bacterial and fungal infections in patients suffering from COVID-19 or other viral infections. In this review, we have described the alternatives to conventional antimicrobials that have shown promising results and are at various stages of development. An acceleration of efforts to investigate their potential as therapeutics can provide more treatment options for clinical management of drug-resistant secondary bacterial and fungal infections in the current pandemic and similar potential outbreaks in the future. The alternatives include bacteriophages and their lytic enzymes, anti-fungal enzymes, antimicrobial peptides, nanoparticles and small molecule inhibitors among others. What is required at this stage is to critically examine the challenges in developing the listed compounds and biomolecules as therapeutics and to establish guidelines for their safe and effective application within a suitable time frame. In this review, we have attempted to highlight the importance of rational use of antimicrobials in patients suffering from COVID-19 and boost the deployment of alternative therapeutics.

Mucormycosis (black fungus) ensuing COVID-19 and comorbidity meets - Magnifying global pandemic grieve and catastrophe begins

Post COVID-19, mucormycosis occurred after the SARS-CoV-2 has rampaged the human population and is a scorching problem among the pandemic globally, particularly among Asian countries. Invasive mucormycosis has been extensively reported from mild to severe COVID-19 survivors. The robust predisposing factor seems to be uncontrolled diabetes mellitus, comorbidity and immunosuppression acquired through steroid therapy. The prime susceptive reason for the increase of mucormycosis cases is elevated iron levels in the serum of the COVID survivors. A panoramic understanding of the infection has been elucidated based on clinical manifestation, genetic and non- genetic mechanisms of steroid drug administration, biochemical pathways and immune modulated receptor associations. This review lime-lights and addresses the "What", "Why", "How" and "When" about the COVID-19 associated mucormycosis (CAM) in a comprehensive manner with a pure intention to bring about awareness to the common public as the cases are inevitably and exponentially increasing in India and global countries as well. The article also unearthed the pathogenesis of mucormycosis and its association with the COVID-19 sequela, the plausible routes of entry, diagnosis and counter remedies to keep the infection at bay. Cohorts of case reports were analysed to spotlight the link between the pandemic COVID-19 and the nightmare-mucormycosis.

Risk factors for severe infections in secondary immunodeficiency: a retrospective US administrative claims study in patients with hematological malignancies

Real-world data are lacking to identify patients with secondary immunodeficiency (SID) who may benefit most from anti-infective interventions. This retrospective analysis used the IQVIA PharMetrics® Plus database to assess baseline characteristics associated with risk of severe infections post-SID diagnosis in patients with hematological malignancies. In 4066 patients included, the mean number of any and severe infections per patient in the one-year pre-SID diagnosis period was 9.5 and 0.7, respectively. Post-SID diagnosis, the mean annualized number of any and severe infections was 19.1 and 1.5, respectively. Receiver operating characteristic curve analysis identified a threshold (cutoff) of three bacterial infections at baseline as optimally predictive of severe infections post-SID diagnosis. Multivariate analysis indicated that hospitalizations, infections (≥3), or antibiotic use pre-SID diagnosis were predictive of severe infections post-SID diagnosis. Evaluation of these risk factors could inform clinical decisions regarding which patients may benefit from prophylactic anti-infective treatment, including immunoglobulin replacement if warranted.

Modelling Immune Memory Development

The cellular adaptive immune response to influenza has been analyzed through several recent mathematical models. In particular, Zarnitsyna et al. (Front Immunol 7:1-9, 2016) show how central memory CD8+ T cells reach a plateau after repeated infections, and analyze their role in the immune response to further challenges. In this paper, we further investigate the theoretical features of that model by extracting from the infection dynamics a discrete map that describes the build-up of memory cells. Furthermore, we show how the model by Zarnitsyna et al. (Front Immunol 7:1-9, 2016) can be viewed as a fast-scale approximation of a model allowing for recruitment of target epithelial cells. Finally, we analyze which components of the model are essential to understand the progressive build-up of immune memory. This is performed through the analysis of simplified versions of the model that include some components only of immune response. The analysis performed may also provide a theoretical framework for understanding the conditions under which two-dose vaccination strategies can be helpful.

Immature granulocytes can help the diagnosis of pulmonary bacterial infections in patients with severe COVID-19 pneumonia

During COVID-19, immature granulocyte (IG) concentration is heterogeneous with higher concentrations than those found in bacterial sepsis. We investigated the relationship between IG levels at ICU admission and on days 7 (± 2) and 15 (± 2) and associated pulmonary bacterial infections in intensive care unit (ICU) patients hospitalized for an acute respiratory distress syndrome (ARDS) related to SARS-CoV-2. Patients with associated pulmonary bacterial infection had a peak of IGs. IG thresholds of 18% or 2 G/L allowed discriminating patients with ventilator associated pneumonia with 100% sensitivity and specificity. Our study supports that IGs could help identifying pulmonary bacterial infections in this population.

RLIM: a recursive and latent infection model for the prediction of US COVID-19 infections and turning points

Initially found in Hubei, Wuhan, and identified as a novel virus of the coronavirus family by the WHO, COVID-19 has spread worldwide at exponential speed, causing millions of deaths and public fear. Currently, the USA, India, Brazil, and other parts of the world are experiencing a secondary wave of COVID-19. However, the medical, mathematical, and pharmaceutical aspects of its transmission, incubation, and recovery processes are still unclear. The classical susceptible-infected-recovered model has limitations in describing the dynamic behavior of COVID-19. Hence, it is necessary to introduce a recursive, latent model to predict the number of future COVID-19 infection cases in the USA. In this article, a dynamic recursive and latent infection model (RLIM) based on the classical SEIR model is proposed to predict the number of COVID-19 infections. Given COVID-19 infection and recovery data for a certain period, the RLIM is able to fit current values and produce an optimal set of parameters with a minimum error rate according to actual reported numbers. With these optimal parameters assigned, the RLIM model then becomes able to produce predictions of infection numbers within a certain period. To locate the turning point of COVID-19 transmission, an initial value for the secondary infection rate is given to the RLIM algorithm for calculation. RLIM will then calculate the secondary infection rates of a continuous time series with an iterative search strategy to speed up the convergence of the prediction outcomes and minimize the maximum square errors. Compared with other forecast algorithms, RLIM is able to adapt the COVID-19 infection curve faster and more accurately and, more importantly, provides a way to identify the turning point in virus transmission by searching for the equilibrium between recoveries and new infections. Simulations of four US states show that with the secondary infection rate ω initially set to 0.5 within the selected latent period of 14 days, RLIM is able to minimize this value at 0.07 and reach an equilibrium condition. A successful forecast is generated using New York state's COVID-19 transmission, in which a turning point is predicted to emerge on January 31, 2021.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11071-021-06520-1.

Autoptic identification of disseminated mucormycosis in a young male presenting with cerebrovascular event, multi-organ dysfunction and COVID-19 infection

Among the secondary fungal infections in Coronavirus-19 (COVID-19) infection, Aspergillosis has been reported more often than Mucormycosis. Disseminated mucormycosis is almost always a disease of severely immunosuppressed hosts. We report a young obese Asian male who was admitted with an acute anterior cerebral artery (ACA) territory infarct and severe COVID-19 pneumonitis to the intensive care unit (ICU). He had a complicated stay with recurrent episodes of vasoplegic shock and multi-organ dysfunction. At autopsy, he was confirmed to have disseminated mucormycosis. We believe this to be the first documented case of disseminated mucormycosis in an immunocompetent host with COVID-19 infection. The lack of sensitive non-invasive modalities and biomarkers to diagnose mucormycosis, along with the extremely high mortality in untreated cases, present a unique challenge to clinicians dealing with critically ill patients with COVID-19.

Profile of co-infections & secondary infections in COVID-19 patients at a dedicated COVID-19 facility of a tertiary care Indian hospital: Implication on antimicrobial resistance

BACKGROUND

The COVID-19 pandemic has raised concerns over secondary infections because it has limited treatment options and empiric antimicrobial treatment poses serious risks of aggravating antimicrobial resistance (AMR). Studies have shown that COVID-19 patients are predisposed to develop secondary infections. This study was conducted to ascertain the prevalence and profiles of co- & secondary infections in patients at the COVID-19 facility in North India.

METHODS

We studied the profile of pathogens isolated from 290 clinical samples. Bacterial and fungal pathogens were identified, and antimicrobial susceptibility was determined by the Vitek2® system. Additionally, respiratory samples were tested for any viral/atypical bacterial co-infections and the presence of AMR genes by FilmArray test. The clinical and outcome data of these patients were also recorded for demographic and outcome measures analyses.

RESULTS

A total of 151 (13%) patients had secondary infections, and most got infected within the first 14 days of hospital admission. Patients aged >50 years developed severe symptoms (p = 0.0004) and/or had a fatal outcome (p = 0.0005). In-hospital mortality was 33%.K.pneumoniae (33.3%) was the predominant pathogen, followed by A. baumannii (27.1%). The overall resistance was up to 84%.Majority of the organisms were multidrug-resistant (MDR) harbouring MDR genes.

CONCLUSION

A high rate of secondary infections with resistant pathogens in COVID-19 patients highlights the importance of antimicrobial stewardship programs focussing on supporting the optimal selection of empiric treatment and rapid-de-escalation, based on culture reports.

Spread of OXA-48-producing Klebsiella pneumoniae among COVID-19-infected patients: The storm after the storm

The impact of secondary infections by multidrug-resistant bacteria in COVID-19- infected patients has yet to be evaluated. Here, we report the clinical and molecular features of an outbreak of seven patients carrying CTX-M-15- and OXA-48-producing Klebsiella pneumoniae belonging to ST326 during COVID-19 pandemic in an ICU in northern Spain. Those patients were admitted to beds close to each other, two of them developed ventilator-associated pneumonia (VAP), one exhibited primary bacteremia and the remaining four were considered to be colonized. None of them was colonized prior to admission to the ICU an all, except one of those who developed VAP, were discharged. Hydroxychloroquine and lopinavir/ritonavir were administered to all of them as COVID-19 therapy and additionally, three of them received tocilizumab and corticosteroids, respectively. Reusing of personal protective equipment due to its initial shortage, relaxation in infection control measures and negative-pressure air in ICU rooms recommended for the protection of health care workers (HCWs), could have contributed to this outbreak. Maximization of infection control measures is essential to avoid secondary infections by MDR bacteria in COVID-infected patients.

Predictors and outcomes of healthcare-associated infections in COVID-19 patients

Introduction

Healthcare-associated infections (HAI) after viral illnesses are important sources of morbidity and mortality. This has not been extensively studied in hospitalized COVID-19 patients.

Methods

This study included all COVID-19-positive adult patients (≥18 years) hospitalized between 01 March and 05 August 2020 at the current institution. The Centers for Disease Control and Prevention definition of HAI in the acute care setting was used. The outcomes that were studied were rates and types of infections and in-hospital mortality. Several multivariable logistic regression models were constructed to examine characteristics associated with development of HAI.

Results

Fifty-nine (3.7%) of 1565 patients developed 140 separate HAIs from 73 different organisms: 23 were Gram-positive, 39 were Gram-negative and 11 were fungal. Patients who developed HAI did not have higher odds of death (OR 0.85, 95% CI 0.40–1.81, p =  0.69). HAIs were associated with the use of tocilizumab (OR 5.04, 95% CI 2.4–10.6, p <  0.001), steroids (OR 3.8, 95% CI 1.4–10, p =  0.007), hydroxychloroquine (OR 3.0, 95% CI 1.0–8.8, p =  0.05), and acute kidney injury requiring hemodialysis (OR 3.7, 95% CI 1.1–12.8, p =  0.04).

Conclusions

HAI were common in hospitalized Covid-19 patients. Tocilizumab and steroids were associated with increased risk of HAIs.

Secondary infections in patients hospitalized with COVID-19: incidence and predictive factors

Objectives

The aim of our study was to describe the incidence and predictive factors of secondary infections in patients with coronavirus disease 2019 (COVID-19).

Methods

This was a cohort study of patients hospitalized with COVID-19 at IRCCS San Raffaele Hospital between 25th February and 6th April 2020 (NCT04318366). We considered secondary bloodstream infections (BSIs) or possible lower respiratory tract infections (pLRTIs) occurring 48 hours after hospital admission until death or discharge. We calculated multivariable Fine–Gray models to assess factors associated with risk of secondary infections.

Results

Among 731 patients, a secondary infection was diagnosed in 68 patients (9.3%); 58/731 patients (7.9%) had at least one BSI and 22/731 patients (3.0%) at least one pLRTI. The overall 28-day cumulative incidence was 16.4% (95%CI 12.4–21.0%). Most of the BSIs were due to Gram-positive pathogens (76/106 isolates, 71.7%), specifically coagulase-negative staphylococci (53/76, 69.7%), while among Gram-negatives (23/106, 21.7%) Acinetobacter baumanii (7/23, 30.4%) and Escherichia coli (5/23, 21.7%) predominated. pLRTIs were caused mainly by Gram-negative pathogens (14/26, 53.8%). Eleven patients were diagnosed with putative invasive aspergillosis. At multivariable analysis, factors associated with secondary infections were low baseline lymphocyte count (≤0.7 versus >0.7 per 10⁹/L, subdistribution hazard ratios (sdHRs) 1.93, 95%CI 1.11–3.35), baseline PaO₂/FiO₂ (per 100 points lower: sdHRs 1.56, 95%CI 1.21–2.04), and intensive-care unit (ICU) admission in the first 48 hours (sdHR 2.51, 95%CI 1.04–6.05).

Conclusions

Patients hospitalized with COVID-19 had a high incidence of secondary infections. At multivariable analysis, early need for ICU, respiratory failure, and severe lymphopenia were identified as risk factors for secondary infections.

Monocytic HLA-DR expression kinetics in septic shock patients with different pathogens, sites of infection and adverse outcomes

Background

Decreased monocytic (m)HLA-DR expression is the most studied biomarker of sepsis-induced immunosuppression. To date, little is known about the relationship between sepsis characteristics, such as the site of infection, causative pathogen, or severity of disease, and mHLA-DR expression kinetics.

Methods

We evaluated mHLA-DR expression kinetics in 241 septic shock patients with different primary sites of infection and pathogens. Furthermore, we used unsupervised clustering analysis to identify mHLA-DR trajectories and evaluated their association with outcome parameters.

Results

No differences in mHLA-DR expression kinetics were found between groups of patients with different sites of infection (abdominal vs. respiratory, p = 0.13; abdominal vs. urinary tract, p = 0.53) and between pathogen categories (Gram-positive vs. Gram-negative, p = 0.54; Gram-positive vs. negative cultures, p = 0.84). The mHLA-DR expression kinetics differed between survivors and non-survivors (p < 0.001), with an increase over time in survivors only. Furthermore, we identified three mHLA-DR trajectories (‘early improvers’, ‘delayed or non-improvers’ and ‘decliners’). The probability for adverse outcome (secondary infection or death) was higher in the delayed or non-improvers and decliners vs. the early improvers (delayed or non-improvers log-rank p = 0.03, adjusted hazard ratio 2.0 [95% CI 1.0–4.0], p = 0.057 and decliners log-rank p = 0.01, adjusted hazard ratio 2.8 [95% CI 1.1–7.1], p = 0.03).

Conclusion

Sites of primary infection or causative pathogens are not associated with mHLA-DR expression kinetics in septic shock patients. However, patients showing delayed or no improvement in or a declining mHLA-DR expression have a higher risk for adverse outcome compared with patients exhibiting a swift increase in mHLA-DR expression. Our study signifies that changes in mHLA-DR expression over time, and not absolute values or static measurements, are of clinical importance in septic shock patients.

Old World cutaneous leishmaniasis treatment response varies depending on parasite species, geographical location and development of secondary infection

BACKGROUND

In the Kingdom of Saudi Arabia (KSA), Leishmania major and L. tropica are the main causative agents of Old World cutaneous leishmaniasis (CL). The national CL treatment regimen consists of topical 1% clotrimazole/2% fusidic acid cream followed by 1-2 courses of intralesional sodium stibogluconate (SSG); however, treatment efficacy is highly variable and the reasons for this are not well understood. In this study, we present a complete epidemiological map of CL and determined the efficacy of the standard CL treatment regime in several endemic regions of KSA.

RESULTS

Overall, three quarters of patients in all CL-endemic areas studied responded satisfactorily to the current treatment regime, with the remaining requiring only an extra course of SSG. The majority of unresponsive cases were infected with L. tropica. Furthermore, the development of secondary infections (SI) around or within the CL lesion significantly favoured the treatment response of L. major patients but had no effect on L. tropica cases.

CONCLUSIONS

The response of CL patients to a national treatment protocol appears to depend on several factors, including Leishmania parasite species, geographical location and occurrences of SI. Our findings suggest there is a need to implement alternative CL treatment protocols based on these parameters.