Understanding the potential impact of different drug properties on SARS-CoV-2 transmission and disease burden : a modelling analysis

Q1Q1Background The unprecedented public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods and Findings develop a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care to explore the potential public-health impact of a range of different potential therapeutics, under a range of different scenarios varying: i) healthcare capacity, ii) epidemic trajectories; and iii) drug efficacy in the absence of supportive care. In each case, the outcome of interest was the number of COVID-19 deaths averted in scenarios with the therapeutic compared to scenarios without. We find the impact of drugs like dexamethasone (which are delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in highincome countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions There is a global asymmetry in who is likely to benefit from advances in the treatment of COVID-19 to date, which have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics that can feasibly be delivered to those earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priorityRevista Internacional - Indexad

Disseminated cryptococcosis in Crohn’s disease: a case report

Abstract Background Gastrointestinal (GI) cryptococcosis is rarely reported. Most cases were diagnosed during evaluation of comorbid conditions, incidental findings, or postmortem. Here, we present a case of Crohn’s disease with gastrointestinal cryptococcosis that resembled exacerbation of Crohn’s disease. Case presentation A 64-year-old woman with Crohn’s disease (CD) was referred to Siriraj Hospital due to worsening of abdominal pain and watery diarrhea for 2 weeks. The dose of immunosuppressive agents was increased for presumed exacerbation of CD. Pathologic examination of tissue obtained from polypoid mass at ileocecal valve and multiple clean-based ulcers at cecum revealed active ileitis and colitis with multiple round shape organisms with capsule, which was compatible with Cryptococcus species. Disseminated cryptococcosis was diagnosed due to gastrointestinal involvement and presumed pulmonary involvement regarding the presence of an oval-shaped cavitary lesion on chest X-ray and computed tomography of the lung. Patient was successfully treated with amphotericin B followed by fluconazole with satisfactory result. Conclusion Early diagnosis of gastrointestinal cryptococcosis in Crohn’s disease is difficult due to the lack of specific symptoms and sign or mimicking an exacerbation of Crohn’s disease. Seeking for other site of involvement in disseminated cryptococcosis including lung or central nervous system as well as detection of serum cryptococcal antigen would be helpful for early diagnosis and management

Distinguishing SARS-CoV-2 Infection and Non-SARS-CoV-2 Viral Infections in Adult Patients through Clinical Score Tools

This study aimed to determine distinguishing predictors and develop a clinical score to differentiate COVID-19 and common viral infections (influenza, respiratory syncytial virus (RSV), dengue, chikungunya (CKV), and zika (ZKV)). This retrospective study enrolled 549 adults (100 COVID-19, 100 dengue, 100 influenza, 100 RSV, 100 CKV, and 49 ZKV) during the period 2017–2020. CKV and ZKV infections had specific clinical features (i.e., arthralgia and rash); therefore, these diseases were excluded. Multiple binary logistic regression models were fitted to identify significant predictors, and two scores were developed differentiating influenza/RSV from COVID-19 (Flu-RSV/COVID) and dengue from COVID-19 (Dengue/COVID). The five independent predictors of influenza/RSV were age > 50 years, the presence of underlying disease, rhinorrhea, productive sputum, and lymphocyte count 3. Likewise, the five independent predictors of dengue were headache, myalgia, no cough, platelet count 3, and lymphocyte count 3. The Flu-RSV/COVID score (cut-off value of 4) demonstrated 88% sensitivity and specificity for predicting influenza/RSV (AUROC = 0.94). The Dengue/COVID score (cut-off value of 4) achieved 91% sensitivity and 94% specificity for differentiating dengue and COVID-19 (AUROC = 0.98). The Flu-RSV/COVID and Dengue/COVID scores had a high discriminative ability for differentiating influenza/RSV or dengue infection and COVID-19. The further validation of these scores is needed to ensure their utility in clinical practice

Demographics and clinical characteristics of patients with extensively drug-resistant <i>Pseudomonas aeruginosa</i> (XDR-PA) and non-XDR-PA infection.

<p>Demographics and clinical characteristics of patients with extensively drug-resistant <i>Pseudomonas aeruginosa</i> (XDR-PA) and non-XDR-PA infection.</p

Treatment, and clinical and microbiological outcomes, of patients with <i>Pseudomonas aeruginosa</i> infections.

<p>Treatment, and clinical and microbiological outcomes, of patients with <i>Pseudomonas aeruginosa</i> infections.</p

Epidemiology and risk factors of extensively drug-resistant <i>Pseudomonas aeruginosa</i> infections

<div><p>Background</p><p>The incidence of nosocomial infections from extensively drug-resistant <i>Pseudomonas aeruginosa</i> (XDR-PA) has been increasing worldwide. We investigated the prevalence and factors associated with XDR-PA infections, including the factors that predict mortality.</p><p>Methods</p><p>We retrospectively studied a cohort of adult, hospitalized patients with <i>P</i>. <i>aeruginosa</i> (PA) infections between April and December 2014.</p><p>Results</p><p>Of the 255 patients with PA infections, 56 (22%) were due to XDR-PA, 32 (12.5%) to multidrug resistant <i>Pseudomonas aeruginosa</i> (MDR-PA), and 167 (65.5%) to non-MDR PA. Receiving total parenteral nutrition (adjusted OR [aOR] 6.21; 95% CI 1.05–36.70), prior carbapenem use (aOR 4.88; 95% CI 2.36–10.08), and prior fluoroquinolone use (aOR 3.38; 95% CI 1.44–7.97) were independently associated with the XDR-PA infections. All XDR-PA remained susceptible to colistin. Factors associated with mortality attributable to the infections were the presence of sepsis/septic shock (aOR 11.60; 95% CI 4.66–28.82), admission to a medical department (aOR 4.67; 95% CI 1.81–12.06), receiving a central venous catheter (aOR 3.78; 95% CI 1.50–9.57), and XDR-PA infection (aOR 2.73; 95% CI 1.05–7.08).</p><p>Conclusion</p><p>The prevalence of XDR-PA infections represented almost a quarter of <i>Pseudomonas aeruginosa</i> hospital-acquired infections and rendered a higher mortality. The prompt administration of an appropriate empirical antibiotic should be considered when an XDR-PA infection is suspected.</p></div

Clinical outcome and laboratory markers for predicting disease activity in patients with disseminated opportunistic infections associated with anti-interferon-γ autoantibodies.

BackgroundClinical courses and treatment outcomes are largely unknown in patients with adult-onset immunodeficiency associated with anti-interferon-gamma autoantibodies due to the fact that it was recently recognized and anti-IFN-γ auto-Abs detection is not widely available.Methods and findingsNon-HIV-infected adult patients with detectable anti-IFN-γ auto-Abs diagnosed and followed at Siriraj Hospital, Bangkok, Thailand during January 2013 to November 2016 were prospectively studied. At each follow-up visit, patients were classified as stable or active disease according to symptoms and signs, and all proven OIs were recorded. Laboratory parameters, including erythrocyte sedimentation rate, C-reactive protein, and anti-IFN-γ auto-Abs level, were compared between active and stable disease episodes. We identified 80 patients with this clinical syndrome and followed them up during study period. Seventy-nine patients developed overall 194 proven opportunistic infections. Mycobacterium abscessus (34.5%) and Salmonella spp. (23.2%) were the two most common pathogens identified among these patients. Sixty-three patients were followed for a median of 2.7 years (range 0.6-4.8 years). Eleven (17.5%) patients achieved the drug-free remission period for at least 9 months. Four patients died. Anti-IFN-γ auto-Abs concentration was significantly lower at baseline and decreased over time in the drug-free remission group compared to another group (p = 0.001). C-reactive protein, erythrocyte sedimentation rate and white cell count were found to be useful biomarkers for determining disease activity during follow-up.ConclusionsReinfection or relapse of OIs is common despite long-term antimicrobial treatment in patients with anti-IFN-γ auto-Abs. Treatment to modify anti-IFN-γ auto-Abs production may improve long-term outcomes in this patient population

Independent predictors of mortality attributable to infection.

<p>Independent predictors of mortality attributable to infection.</p

Independent predictors of XDR-PA infections.

<p>Independent predictors of XDR-PA infections.</p

A Risk Prediction Model and Risk Score of SARS-CoV-2 Infection Following Healthcare-Related Exposure

Hospital workers are at high risk of contact with COVID-19 patients. Currently, there is no evidence-based, comprehensive risk assessment tool for healthcare-related exposure; so, we aimed to identify independent factors related to COVID-19 infection in hospital workers following workplace exposure(s) and construct a risk prediction model. We analyzed the COVID-19 contact tracing dataset from 15 July to 31 December 2021 using multiple logistic regression analysis, considering exposure details, demographics, and vaccination history. Of 7146 included exposures to confirmed COVID-19 patients, 229 (4.2%) had subsequently tested positive via RT-PCR. Independent risk factors for a positive test were having symptoms (adjusted odds ratio 4.94, 95%CI 3.83–6.39), participating in an unprotected aerosol-generating procedure (aOR 2.87, 1.66–4.96), duration of exposure >15 min (aOR 2.52, 1.82–3.49), personnel who did not wear a mask (aOR 2.49, 1.75–3.54), exposure to aerodigestive secretion (aOR 1.5, 1.03–2.17), index patient not wearing a mask (aOR 1.44, 1.01–2.07), and exposure distance <1 m without eye protection (aOR 1.39, 1.02–1.89). High-potency vaccines and high levels of education protected against infection. A risk model and scoring system with good discrimination power were built. Having symptoms, unprotected exposure, lower education level, and receiving low potency vaccines increased the risk of laboratory-confirmed COVID-19 following healthcare-related exposure events