On Oct 22, 2015, WHO launched the Global Antimicrobial Resistance Surveillance System (GLASS), the first global collaborative effort to standardise antimicrobial resistance surveillance.1 GLASS ...supports the strategic objective of WHO's Global Action Plan on antimicrobial resistance to strengthen the evidence base.2 GLASS provides a standardised approach to the collection, analysis, and sharing of antimicrobial resistance data by countries, and seeks to document the status of existing or newly developed national surveillance systems.3 GLASS is supported by WHO Collaborating Centres, involving strong commitment from participating countries and close collaborations with regional networks. Acinetobacter spp, Escherichia coli, Klebsiella pneumoniae, Neisseria gonorrhoeae, Salmonella spp, Shigella spp, Staphylococcus aureus, and Streptococcus pneumoniae.3 These data are collected through a case-finding surveillance system, which collates results of priority specimens from blood, urine, stool, as well as cervical and urethral specimens, that have been sent routinely to laboratories for clinical purposes. Five countries also submitted data for the total sampled population; this denominator allowed for the calculation of antimicrobial resistance incidence in tested patients, a metric so far not often used to measure resistance, and in some cases, to stratify it for sex, age, and infection origin. Because this submission was the first year of GLASS data collection, great variability was expected in the completeness and quality of antimicrobial resistance data, and differences were addressed to promote a harmonised representation of the results and to show country efforts.
Gonorrhoea and antimicrobial resistance (AMR) in Neisseria gonorrhoeae are major health concerns globally. Increased global surveillance of gonococcal AMR is essential. We aimed to describe the ...2017–18 data from WHO's global gonococcal AMR surveillance, and to discuss priorities essential for the effective management and control of gonorrhoea.
We did a retrospective observational study of the AMR data of gonococcal isolates reported to WHO by 73 countries in 2017–18. WHO recommends that each country collects at least 100 gonococcal isolates per year, and that quantitative methods to determine the minimum inhibitory concentration of antimicrobials, interpreted by internationally standardised resistance breakpoints, are used.
In 2017–18, 73 countries provided AMR data for one or more drug. Decreased susceptibility or resistance to ceftriaxone was reported by 21 (31%) of 68 reporting countries and to cefixime by 24 (47%) of 51 reporting countries. Resistance to azithromycin was reported by 51 (84%) of 61 reporting countries and to ciprofloxacin by all 70 (100%) reporting countries. The annual proportion of decreased susceptibility or resistance across countries was 0–21% to ceftriaxone and 0–22% to cefixime, and that of resistance was 0–60% to azithromycin and 0–100% to ciprofloxacin. The number of countries reporting gonococcal AMR and resistant isolates, and the number of examined isolates, have increased since 2015–16. Surveillance remains scarce in central America and the Caribbean and eastern Europe, and in the WHO African, Eastern Mediterranean, and South-East Asian regions.
In many countries, ciprofloxacin resistance was exceedingly high, azithromycin resistance was increasing, and decreased susceptibility or resistance to ceftriaxone and cefixime continued to emerge. WHO's global surveillance of gonococcal AMR needs to expand internationally to provide imperative data for national and international management guidelines and public health policies. Improved prevention, early diagnosis, treatment of index patients and partners, enhanced surveillance (eg, infection, AMR, treatment failures, and antimicrobial use or misuse), and increased knowledge on antimicrobial selection, stewardship, and pharmacokinetics or pharmacodynamics are essential. The development of rapid, accurate, and affordable point-of-care gonococcal diagnostic tests, new antimicrobials, and gonococcal vaccines is imperative.
None.
Leptospirosis is a neglected zoonosis affecting mainly tropical and subtropical regions worldwide, particularly South America and the Caribbean. As in many other countries, under-reporting of cases ...was suspected in the French West Indies because of inadequate access to diagnostic tests for the general population.
In order to estimate the real incidence of leptospirosis in Guadeloupe and Martinique, a study was performed in 2011 using the three prevailing available biological tests for diagnosis: Microscopic Agglutination Test (MAT), IgM ELISA and PCR. The study investigated inpatients and outpatients and used active case ascertainment from data provided by a general practitioners' sentinel network. The epidemiology of the disease was also described in terms of severity and demographic characteristics. Leptospirosis incidence was estimated at 69.4 (95%CI 47.6-91.1) and 60.6 (95%CI 36.3-85.0) annual cases per 100,000 inhabitants in Guadeloupe and Martinique, respectively, which was 3 and 4 times higher than previous estimations.
Inclusion of PCR and IgM ELISA tests for diagnosis of leptospirosis resulted in improved sensitivity in comparison with MAT alone. Our results highlighted the substantial health burden of the disease in these two territories and the importance of access to appropriate laboratory tests. Based on our results, PCR and IgM ELISA tests have now been included in the list of tests reimbursed by the national system of social security insurance in France. Our results also underline the relevance of implementing an integrated strategy for the surveillance, prevention and control of leptospirosis in the French West Indies.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of ...the world's largest international, standardized data sets concerning hospitalized patients.
Methods
The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV).
Results
Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49) and male sex 1.23 (1.21, 1.24) were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%.
Conclusions
Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death.
To describe the use of antimicrobials in a veterinary teaching hospital for companion animals in Italy, with particular regard to the agreement with recommendations of prudent use
The study was ...conducted with a retrospective, cross-sectional design. The population under investigation included 18,905 cats and dogs that were referred to the hospital between 2000 and 2007. Two different samples of the clinical paper forms were randomly selected to estimate the prevalence of animals receiving an antimicrobial prescription and to describe the pattern of antimicrobials used in relation to the condition being treated. The proportion of antimicrobials prescribed accomplishing recommendations of prudent use was also estimated, as well as the level of agreement with specific, diagnosis-based guidelines for antimicrobial use.
Broad-spectrum antimicrobials, including penicillins with β-lactamase inhibitors, first-generation cephalosporins and fluoroquinolones, were the most frequently prescribed compounds. Antimicrobials prescribed with the support of microbiological analyses and susceptibility testing were less than 5%. Among the recommendation of prudent use, the availability of information from laboratory testing had the poorest degree of agreement, while the other evaluated items were accomplished in most of the cases.
Our results highlight the need to improve the procedures of antimicrobial prescription in the study setting. This can be achieved by supporting the guidance for antimicrobial use at the local level, with the adoption of specific guidelines, and at the national level with a further implementation of the policies of prudent prescriptions.
Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ...ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs).
This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support.
A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR 95%CI; 5.86 4.83-7.10), treatment in an LMIC (OR 95%CI; 2.04 1.97-2.11), and tachypnoea at hospital admission (OR 95%CI; 1.16 1.14-1.18). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR 95%CI; 1.27 1.25-1.30).
In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.
Using a large dataset, we evaluated prevalence and severity of alterations in liver enzymes in COVID-19 and association with patient-centred outcomes.
We included hospitalized patients with confirmed ...or suspected SARS-CoV-2 infection from the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) database. Key exposure was baseline liver enzymes (AST, ALT, bilirubin). Patients were assigned Liver Injury Classification score based on 3 components of enzymes at admission: Normal; Stage I) Liver injury: any component between 1-3x upper limit of normal (ULN); Stage II) Severe liver injury: any component ≥3x ULN. Outcomes were hospital mortality, utilization of selected resources, complications, and durations of hospital and ICU stay. Analyses used logistic regression with associations expressed as adjusted odds ratios (OR) with 95% confidence intervals (CI).
Of 17,531 included patients, 46.2% (8099) and 8.2% (1430) of patients had stage 1 and 2 liver injury respectively. Compared to normal, stages 1 and 2 were associated with higher odds of mortality (OR 1.53 1.37-1.71; OR 2.50 2.10-2.96), ICU admission (OR 1.63 1.48-1.79; OR 1.90 1.62-2.23), and invasive mechanical ventilation (OR 1.43 1.27-1.70; OR 1.95 (1.55-2.45). Stages 1 and 2 were also associated with higher odds of developing sepsis (OR 1.38 1.27-1.50; OR 1.46 1.25-1.70), acute kidney injury (OR 1.13 1.00-1.27; OR 1.59 1.32-1.91), and acute respiratory distress syndrome (OR 1.38 1.22-1.55; OR 1.80 1.49-2.17).
Liver enzyme abnormalities are common among COVID-19 patients and associated with worse outcomes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, ...however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients.
In 2013/2014, Italy experienced one of the largest community-wide prolonged outbreaks of hepatitis A virus (HAV) throughout the country. The article provides a comprehensive description of the ...outbreak and the investigation carried out by a multidisciplinary National Task Force, in collaboration with regional and local public health authorities. Control strategies of food-borne HAV infection in both the human and food sectors are also described.
Enhanced human epidemiological and microbiological surveillance together with microbiological monitoring of HAV in food and trace-back investigation were conducted.
A total of 1803 HAV cases were identified from 1 January 2013 to 31 August 2014, in Italy. Sequencing was possible for 368 cases (20.4 %), mostly collected between 1 January 2013 and 28 February 2014, and 246 cases (66.8 %) harboured an HAV outbreak strain. Imported frozen berries contaminated with HAV were identified as the vehicle of the outbreak which also involved many other European countries in 2013 and 2014. Epidemiological evidence obtained through a case-control study was supported by the finding of a 100 % nucleotide similarity of the VP1/2A sequences of HAVs detected in human and food samples. Trace-back investigation revealed an extremely complex supplying network with no possibility for a point source potentially explaining the vast contamination of berries found in Italy.
The investigation benefited from an excellent collaboration among different sectors who shared proactively the available information. Our findings highlight the importance of considering frozen berries among the highest risk factors for HAV.
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