Towards Uniform Gene Bank Documentation In Europe – The Experience From The EFABISnet Project

In the EFABISnet project, a collaborative effort of EAAP, FAO and partners from 14 European countries, in cooperation with the European Regional Focal Point for Animal Genetic Resources (ERFP), national information systems for monitoring the animal genetic resources on breed level were established in Austria, Cyprus, Estonia, Georgia, Iceland, Ireland, Italy, Netherlands, Slovakia, Slovenia, Switzerland, and United Kingdom. The network was soon extended beyond the project plans, with the establishment of EFABIS databases in Finland, Greece, and Hungary. The network was then complemented by a set of inventories of national gene bank collections to strengthen the documentation of ex situ conservation programmes. These documentation systems were established by the National Focal Points for management of farm animal genetic resources. Here we present the experience gained in establishment of these national inventories of gene banks and their relevance to the Strategic Priority Areas of the Global Plan of Action which could be useful for other areas in the world

The hospital environment versus carriage: transmission pathways for third-generation cephalosporin-resistant bacteria in blood in neonates in a low-resource country healthcare setting

Neonatal bloodstream infections (BSI) can lead to sepsis, with high morbidity and mortality, particularly in low-income settings. The high prevalence of third-generation cephalosporin-resistant organisms (3GC-RO) complicates the management of BSI. Whether BSI is linked to carriage of 3GC-RO, or to acquisition from the hospital environment is important for infection prevention and control, but the relationship remains unclear, especially in low-income settings. At a tertiary hospital in Mwanza, Tanzania, we screened neonatal blood and rectal samples from 200 neonates, and 400 (hospital) environmental samples. We used logistic regression to identify risk factors, and Kolmogorov–Smirnov tests and randomisation analyses to compare distributions of species and resistance patterns to assess potential routes of transmission. We found that BSIs caused by 3GC-RO were frequent (of 59 cases of BSI, 55 were caused by 3GC-RO), as was carriage of 3GC-RO, particularly Escherichia coli, Klebsiella pneumoniae, and Acinetobacter species. In the 28 infants with both a carriage and blood isolate, there were more (4 of 28) isolate pairs of the same species and susceptibility profile than expected by chance (p < 0.05), but most pairs were discordant (24 of 28). Logistic regression models found no association between BSI and carriage with either 3GC-RO or only 3GC-R K. pneumoniae. These analyses suggest that carriage of 3GC-RO is not a major driver of BSI caused by 3GC-RO in this setting. Comparison with environmental isolates showed very similar distributions of species and resistance patterns in the carriage, BSI, and the environment. These similar distributions, a high frequency of Acinetobacter spp. isolations, the lack of strong association between carriage and BSI, together with the high proportion of 3GC-RO in BSI all suggest that these neonates acquire multidrug-resistant carriage and blood isolates directly from the hospital environment

Developing practical clinical tools for predicting neonatal mortality at a neonatal intensive care unit in Tanzania

Background: Neonatal mortality remains high in Tanzania at approximately 20 deaths per 1000 live births. Low birthweight, prematurity, and asphyxia are associated with neonatal mortality; however, no studies have assessed the value of combining underlying conditions and vital signs to provide clinicians with early warning of infants at risk of mortality. The aim of this study was to identify risk factors (including vital signs) associated with neonatal mortality in the neonatal intensive care unit (NICU) in Bugando Medical Centre (BMC), Mwanza, Tanzania; to identify the most accurate generalised linear model (GLM) or decision tree for predicting mortality; and to provide a tool that provides clinically relevant cut-offs for predicting mortality that is easily used by clinicians in a low-resource setting. Methods: In total, 165 neonates were enrolled between November 2019 and March 2020, of whom 80 (48.5%) died. We competed the performance of GLMs and decision trees by resampling the data to create training and test datasets and comparing their accuracy at correctly predicting mortality. Results: GLMs always outperformed decision trees. The best fitting GLM showed that (for standardised risk factors) temperature (OR 0.61, 95% CI 0.40–0.90), birthweight (OR 0.33, 95% CI 0.20–0.52), and oxygen saturation (OR 0.66, 95% CI 0.45–0.94) were negatively associated with mortality, while heart rate (OR 1.59, 95% CI 1.10–2.35) and asphyxia (OR 3.23, 95% 1.25–8.91) were risk factors. To identify the tool that balances accuracy and with ease of use in a low-resource clinical setting, we compared the best fitting GLM with simpler versions, and identified the three-variable GLM with temperature, heart rate, and birth weight as the best candidate. For this tool, cut-offs were identified using receiver operator characteristic (ROC) curves with the optimal cut-off for mortality prediction corresponding to 76.3% sensitivity and 68.2% specificity. The final tool is graphical, showing cut-offs that depend on birthweight, heart rate, and temperature. Conclusions: Underlying conditions and vital signs can be combined into simple graphical tools that improve upon the current guidelines and are straightforward to use by clinicians in a low-resource setting

Staphylococcal bacteremia in cancer patients: Risk factors and outcome in 134 episodes prior to and after introduction of quinolones into infection prevention in neutropenia

A total of 134 episodes of staphylococcal bacteremia (SBE) appearing among 9987 admissions, and 979 episodes of bacteremia in cancer patients within 5 years, were analyzed for risk factors, clinical course and outcome; 64 were monomicrobial and 70 polymicrobial. The most frequent risk factors were acute leukemia, catheter insertion, long-lasting neutropenia, and prior prophylaxis with quinolones. There was no significant difference between polymicrobial and monomicrobial SBE in risk factors. The two groups differed only in the source of bacteremia (gastrointestinal and respiratory-tract infections were more common in monomicrobial SBE) and etiology - Staphylococcus aureus appeared more frequently in monomicrobial than in polymicrobial bacteremia (20.3% compared to 4.3%, P<0.05). More complications (14.3%) such as abscesses, endocarditis, etc. appeared in the group of polymicrobial SBE (P<0.05). No difference was observed in clinical course and outcome between monomicrobial and polymicrobial SBE. The incidence of SBE has increased since 1991, when quinolones were first used in prophylaxis in afebrile neutropenia at our center; however, the infection-associated mortality in monomicrobial SBE was low (4.3%)