Selecting appropriate empirical antibiotic regimens for paediatric bloodstream infections: application of a Bayesian decision model to local and pooled antimicrobial resistance surveillance data

Application of the Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the empiric antibiotic treatment of febrile neutropenia in oncological paediatric patients: experience from two paediatric hospitals in Northern Italy

BACKGROUND

Guidelines about febrile neutropenia in paediatric patients are not homogeneous; the best empiric treatment of this condition should be driven by local epidemiology. The Weighted-Incidence Syndromic Combination Antibiogram (WISCA) addresses the need for disease-specific local susceptibility evidence that could guide empiric antibiotic prescriptions based on outcome estimates of treatment regimens obtained as a weighted average of pathogen susceptibilities. This study developed a WISCA model to inform empirical antibiotic regimen selection for febrile neutropenia (FN) episodes in onco-haematological paediatric patients treated at two Italian paediatric tertiary centres.

METHODS

We included blood cultures from patients with a bloodstream infection and neutropenia admitted to the Paediatric Haematology-Oncology wards in Padua and Genoa Hospitals from 2016 to 2021. WISCAs were developed by estimating the coverage of 20 antibiotics as monotherapy and of 21 combined regimens with a Bayesian probability distribution.

RESULTS

We collected 350 blood cultures, including 196 g-negative and 154 g-positive bacteria. Considering the most used antibiotic combinations, such as piperacillin-tazobactam plus amikacin, the median coverage for the pool of bacteria collected in the study was 78%. When adding a glycopeptide, the median coverage increased to 89%, while the replacement of piperacillin-tazobactam with meropenem did not provide benefits. The developed WISCAs showed that no monotherapy offered an adequate coverage rate for the identified pathogens.

CONCLUSIONS

The application of WISCA offers the possibility of maximizing the clinical utility of microbiological surveillance data derived from large hospitals to inform the choice of the best empiric treatment while contributing to spare broad-spectrum antibiotics.

Why local antibiotic resistance data matters - Informing empiric prescribing through local data collation, app design and engagement in Zambia

BACKGROUND

Control of antimicrobial resistance (AMR) relies on local knowledge and local intervention implementation. Effective antibiotic stewardship requires locally-suitable prescribing guidelines. We aimed to use a novel digital tool (the ZARIApp) and a participatory approach to help develop locally-relevant empiric antibiotic prescribing guidelines for two hospitals in Lusaka, Zambia.

METHODS

We produced an AMR report using samples collected locally and routinely from adults within the prior two years (April 2020 - April 2022). We developed the ZARIApp, which provides prescribing recommendations based on local resistance data and antibiotic prescribing practices. We used qualitative evaluation of focus group discussions among healthcare professionals to assess the feasibility and acceptability of using the ZARIApp and identify the barriers to and enablers of this stewardship approach.

RESULTS

Resistance prevalence was high for many key pathogens: for example, 73% of 41 Escherichia coli isolates were resistant to ceftriaxone. We identified that high resistance rates were likely due to low levels of requesting and processing of microbiology samples from patients leading to insufficient and unrepresentative microbiology data. This emerged as the major barrier to generating locally-relevant guidelines. Through active stakeholder engagement, we modified the ZARIApp to better support users to generate empirical antibiotic guidelines within this context of unrepresentative microbiology data. Qualitative evaluation of focus group discussions suggested that the resulting ZARIApp was useful and easy to use. New antibiotic guidelines for key syndromes are now in place in the two study hospitals, but these have substantial residual uncertainty.

CONCLUSIONS

Tools such as the free online ZARIApp can empower local settings to better understand and optimise how sampling and prescribing can help to improve patient care and reduce future AMR. However, the usability of the ZARIApp is severely limited by unrepresentative microbiology data; improved routine microbiology surveillance is vitally needed.

Syndromic Antibiograms and Nursing Home Clinicians' Antibiotic Choices for Urinary Tract Infections

Importance

Empirical antibiotic prescribing in nursing homes (NHs) is often suboptimal. The potential for antibiograms to improve empirical antibiotic decision-making in NHs remains poorly understood.

Objective

To determine whether providing NH clinicians with a urinary antibiogram improves empirical antibiotic treatment of urinary tract infections (UTIs).

Design, Setting, and Participants

This was a survey study using clinical vignettes. Participants were recruited via convenience sampling of professional organization listservs of NH clinicians practicing in the US from December 2021 through April 2022. Data were analyzed from July 2022 to June 2023.

Interventions

Respondents were randomized to complete vignettes using a traditional antibiogram (TA), a weighted-incidence syndromic combination antibiogram (WISCA), or no tool. Participants randomized to antibiogram groups were asked to use the antibiogram to empirically prescribe an antibiotic. Participants randomized to the no tool group functioned as controls.

Main Outcomes and Measures

Empirical antibiotic selections were characterized as microbiologically (1) active and (2) optimal according to route of administration and spectrum of activity.

Results

Of 317 responses, 298 (95%) were included in the analysis. Duplicate responses (15 participants), location outside the US (2 participants), and uninterpretable responses (2 participants) were excluded. Most respondents were physicians (217 respondents [73%]) and had over 10 years of NH practice experience (155 respondents [52%]). A mixed-effects logistic model found that use of the TA (odds ratio [OR], 1.41; 95% CI, 1.19-1.68; P < .001) and WISCA (OR, 1.54; 95% CI, 1.30-1.84; P < .001) were statistically superior to no tool when choosing an active empirical antibiotic. A similarly constructed model found that use of the TA (OR, 1.94; 95% CI, 1.42-2.66; P < .001) and WISCA (OR, 1.7; 95% CI, 1.24-2.33; P = .003) were statistically superior to no tool when selecting an optimal empirical antibiotic. Although there were differences between tools within specific vignettes, when compared across all vignettes, the TA and WISCA performed similarly for active (OR, 1.09; 95% CI, 0.92-1.30; P = .59) and optimal (OR, 0.87; 95% CI, 0.64-1.20; P = .69) antibiotics.

Conclusions and Relevance

Providing NH clinicians with a urinary antibiogram was associated with selection of active and optimal antibiotics when empirically treating UTIs under simulated conditions. Although the antibiogram format was not associated with decision-making in aggregate, context-specific effects may have been present, supporting further study of syndromic antibiograms in clinical practice.

Clinical utility of prior positive cultures to optimize empiric antibiotic therapy selection: A cross-sectional analysis

Background

Despite reduced infectious disease mortality and improved survival, infectious diseases continue to pose health threats due to their contagiousness, societal harm, and morbidity. Empiric antibiotic therapy, often prescribed without knowledge of the causative pathogen, faces challenges from rising antibiotic resistance. This study explores the potential of prior positive culture results to guide empiric antibiotic therapy.

Methods

Data from King Abdullah University Hospital (Jan 2014-Dec 2019) included adult patients with recurrent bacterial infections (pneumonia, sepsis, UTIs, wounds). Excluded cases included: mixed infections, transfers, <14 days or >12 months between episodes. The study compared bacterial growth and sensitivity patterns between previous and recent cultures.

Results

The study included 970 episodes from 650 patients, mainly UTIs (60.3%) and gram-negative bacteria (77.9%). The study found that (65.1%) of culture pairs matched. Empirical therapy was accurate in (71.8%) of cases. Further, accuracy of selected empiric antibiotic therapy was significantly predicted (p ​< ​0.001) by: type of infection, type of antibiotics, and concordance with prior microbiologic data. Multivariate logistic analysis showed blood culture as less predictive of pending identity (OR: 0.234, P ​< ​0.001) compared to urine culture; and prior affirmed gram negative bacterial culture was less predictive (OR: 0.606, P ​= ​0.021) compared to gram positive bacterial culture.

Conclusion

This study underscores the potential of prior positive culture results in guiding empiric antibiotic therapy, enhancing accuracy and identity agreement. Future research should explore this approach in different infection contexts and across multiple centers. Reducing the indiscriminate use of broad-spectrum antibiotics is essential to combat antibiotic resistance.

Estimating antibiotic coverage from linked microbiological and clinical data from the Swiss Paediatric Sepsis Study to support empiric antibiotic regimen selection

In light of rising antibiotic resistance, better methods for selection of empiric antibiotic treatment based on clinical and microbiological data are needed. Most guidelines target specific clinical infections, and variably adjust empiric antibiotic selection by certain patient characteristics. Coverage estimates reflect the probability that an antibiotic regimen will be active against the causative pathogen once confirmed and can provide an objective basis for empiric regimen selection. Coverage can be estimated for specific infections using a weighted incidence syndromic combination antibiograms (WISCAs) framework. However, no comprehensive data combining clinical and microbiological data for specific clinical syndromes are available in Switzerland. We therefore describe estimating coverage from semi-deterministically linked routine microbiological and cohort data of hospitalised children with sepsis. Coverage estimates were generated for each hospital and separately pooling data across ten contributing hospitals for five pre-defined patient risk groups. Data from 1,082 patients collected during the Swiss Paediatric Sepsis Study (SPSS) 2011-2015 were included. Preterm neonates were the most commonly represented group, and half of infants and children had a comorbidity. 67% of neonatal sepsis cases were hospital-acquired late-onset whereas in children 76% of infections were community-acquired. Escherichia coli, Coagulase-negative staphylococci (CoNS) and Staphylococcus aureus were the most common pathogens. At all hospitals, ceftazidime plus amikacin regimen had the lowest coverage, and coverage of amoxicillin plus gentamicin and meropenem were generally comparable. Coverage was improved when vancomycin was included in the regimen, reflecting uncertainty about the empirically targeted pathogen spectrum. Children with community-acquired infections had high coverage overall. It is feasible to estimate coverage of common empiric antibiotic regimens from linked data. Pooling data by patient risk groups with similar expected pathogen and susceptibility profiles may improve coverage estimate precision, supporting better differentiation of coverage between regimens. Identification of data sources, selection of regimens and consideration of pathogens to target for improved empiric coverage is important.

Resistance Trend Estimation Using Regression Analysis to Enhance Antimicrobial Surveillance: A Multi-Centre Study in London 2009-2016

In the last years, there has been an increase of antimicrobial resistance rates around the world with the misuse and overuse of antimicrobials as one of the main leading drivers. In response to this threat, a variety of initiatives have arisen to promote the efficient use of antimicrobials. These initiatives rely on antimicrobial surveillance systems to promote appropriate prescription practices and are provided by national or global health care institutions with limited consideration of the variations within hospitals. As a consequence, physicians' adherence to these generic guidelines is still limited. To fill this gap, this work presents an automated approach to performing local antimicrobial surveillance from microbiology data. Moreover, in addition to the commonly reported resistance rates, this work estimates secular resistance trends through regression analysis to provide a single value that effectively communicates the resistance trend to a wider audience. The methods considered for trend estimation were ordinary least squares regression, weighted least squares regression with weights inversely proportional to the number of microbiology records available and autoregressive integrated moving average. Among these, weighted least squares regression was found to be the most robust against changes in the granularity of the time series and presented the best performance. To validate the results, three case studies have been thoroughly compared with the existing literature: (i) Escherichia coli in urine cultures; (ii) Escherichia coli in blood cultures; and (iii) Staphylococcus aureus in wound cultures. The benefits of providing local rather than general antimicrobial surveillance data of a higher quality is two fold. Firstly, it has the potential to stimulate engagement among physicians to strengthen their knowledge and awareness on antimicrobial resistance which might encourage prescribers to change their prescription habits more willingly. Moreover, it provides fundamental knowledge to the wide range of stakeholders to revise and potentially tailor existing guidelines to the specific needs of each hospital.

Improving empiric antibiotic prescribing in pediatric bloodstream infections: a potential application of weighted-incidence syndromic combination antibiograms (WISCA)

Background: Increasing antibiotic resistance to WHO-recommended first- and second-line treatments of pediatric sepsis requires adaptation of prescribing guidelines. We discuss the potential and limitations of a weighted-incidence syndromic combination antibiogram (WISCA) as a practical tool for incorporating local microbiology data when assessing empiric coverage of commonly used antibiotics.Research design and methods: A brief questionnaire of 18 clinically significant isolates from pediatric blood cultures (Jan-Dec 2018) was sent to a global network of pediatric hospitals in July 2019. Weighted coverage estimates of non-antipseudomonal third-generation cephalosporins (3GC) and meropenem were estimated using Monte-Carlo simulation for each site reporting >100 isolates.Results: 52 hospitals in 23 countries in 5 WHO regions responded to the questionnaire; 13 sites met the sample size requirement. The most common isolates were S. aureus, Klebsiella spp., E. coli and Enterococcus spp. Coverage of 3GC ranged from 39% [95%CrI: 34-43%] to 73% (two sites: [95%CrI: 65-80%]; [95%CrI: 68-86%]) and meropenem coverage ranged from 54% [95%CrI: 47-60%] to 88% [95%CrI:84-91%].Conclusions: A WISCA is a data-driven, clinically intuitive tool that can be used to compare empiric antibiotic regimens for pediatric sepsis using existing large datasets. The estimates can be further refined using more complex meta-analytical methods and patient characteristics.

Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach

BACKGROUND

To evaluate the ability of Weighted-Incidence Syndromic Combination Antibiograms (WISCA) to inform the selection of empirical antibiotic regimens for suspected paediatric community-acquired urinary tract infections.

METHODS

Data were collected from outpatients (< 15 years) accessing the emergency rooms of Padua University-Hospital and Mestre Dell' Angelo-Hospital (Venice) between January 1st, 2016, and December 31st, 2018. WISCAs were developed by estimating the coverage of eight regimens using a Bayesian hierarchical model adjusted for age, sex, and previous antibiotic treatment or renal/urological comorbidities.

RESULTS

385 of 620 urine culture requests were included in the model analysis. The most frequently observed bacterium was E. coli (85% and 87%, Centre A and B). No centre effect on coverage estimates was found, and data were successfully pooled together. Coverage ranged from 77.8% (Co-trimoxazole) to 97.6% (Carbapenems). Complex cases and males had significantly lower odds of being covered by a regimen than non-complex cases and females (odds ratio (OR) 0.49 [95% HDI, 0.38-0.65], and OR: 0.73 [95% HDIs, 0.56-0.96] respectively). Children aged 3-5 years had lower odds of being covered by a regimen than other age groups, except for neonates.

CONCLUSIONS

The developed WISCAs provide highly informative estimates on coverage patterns overcoming the limitation of combination antibiograms and expanding the framework of previous Bayesian WISCA algorithm.

Laboratory informatics capacity for effective antimicrobial resistance surveillance in resource-limited settings

Antimicrobial resistance (AMR) is a major threat to human health globally. Surveillance is a key activity to determine AMR burden, impacts, and trends and to monitor effects of interventions. Surveillance systems require efficient capture and onward sharing of high-quality laboratory data. Substantial investment is being made to improve laboratory capacity, particularly in low-income and middle-income countries (LMICs) with high disease burdens. However, building capacity for effective laboratory data management remains an under-resourced area, which, unless addressed, will limit progress towards comprehensive AMR surveillance in LMICs. The lack of a fit-for-purpose and open-source laboratory information management system software is of particular concern. In this Personal View, we summarise the technical requirements for microbiology laboratory data management, provide a snapshot of laboratory data management in LMIC laboratories, and describe the key steps required to improve the situation. Without action to improve information technology infrastructure and data management systems in microbiology laboratories, the ongoing efforts to develop capacity for AMR surveillance in LMICs might not realise their full potential.

Digital microbiology

BACKGROUND

Digitalization and artificial intelligence have an important impact on the way microbiology laboratories will work in the near future. Opportunities and challenges lie ahead to digitalize the microbiological workflows. Making efficient use of big data, machine learning, and artificial intelligence in clinical microbiology requires a profound understanding of data handling aspects.

OBJECTIVE

This review article summarizes the most important concepts of digital microbiology. The article gives microbiologists, clinicians and data scientists a viewpoint and practical examples along the diagnostic process.

SOURCES

We used peer-reviewed literature identified by a PubMed search for digitalization, machine learning, artificial intelligence and microbiology.

CONTENT

We describe the opportunities and challenges of digitalization in microbiological diagnostic processes with various examples. We also provide in this context key aspects of data structure and interoperability, as well as legal aspects. Finally, we outline the way for applications in a modern microbiology laboratory.

IMPLICATIONS

We predict that digitalization and the usage of machine learning will have a profound impact on the daily routine of laboratory staff. Along the analytical process, the most important steps should be identified, where digital technologies can be applied and provide a benefit. The education of all staff involved should be adapted to prepare for the advances in digital microbiology.

Evaluation of the Coverage of 3 Antibiotic Regimens for Neonatal Sepsis in the Hospital Setting Across Asian Countries

IMPORTANCE

High levels of antimicrobial resistance in neonatal bloodstream isolates are being reported globally, including in Asia. Local hospital antibiogram data may include too few isolates to meaningfully examine the expected coverage of antibiotic regimens.

OBJECTIVE

To assess the coverage offered by 3 antibiotic regimens for empirical treatment of neonatal sepsis in Asian countries.

DESIGN, SETTING, AND PARTICIPANTS

A decision analytical model was used to estimate coverage of 3 prespecified antibiotic regimens according to a weighted-incidence syndromic combination antibiogram. Relevant data to parameterize the models were identified from a systematic search of Ovid MEDLINE and Embase. Data from Asian countries published from 2014 onward were of interest. Only data on blood culture isolates from neonates with sepsis, bloodstream infection, or bacteremia reported from the relevant setting were included. Data analysis was performed from April 2019 to July 2019.

EXPOSURES

The prespecified regimens of interest were aminopenicillin-gentamicin, third-generation cephalosporins (cefotaxime or ceftriaxone), and meropenem. The relative incidence of different bacteria and their antimicrobial susceptibility to antibiotics relevant for determining expected concordance with these regimens were extracted.

MAIN OUTCOMES AND MEASURES

Coverage was calculated on the basis of a decision-tree model incorporating relative bacterial incidence and antimicrobial susceptibility of relevant isolates. Data on 7 bacteria most commonly reported in the included studies were used for estimating coverage, which was reported at the country level.

RESULTS

Data from 48 studies reporting on 10 countries and 8376 isolates were used. Individual countries reported 51 (Vietnam) to 6284 (India) isolates. Coverage varied considerably between countries. Meropenem was generally estimated to provide the highest coverage, ranging from 64.0% (95% credible interval [CrI], 62.6%-65.4%) in India to 90.6% (95% CrI, 86.2%-94.4%) in Cambodia, followed by aminopenicillin-gentamicin (from 35.9% [95% CrI, 27.7%-44.0%] in Indonesia to 81.0% [95% CrI, 71.1%-89.7%] in Laos) and cefotaxime or ceftriaxone (from 17.9% [95% CrI, 11.7%-24.7%] in Indonesia to 75.0% [95% CrI, 64.8%-84.1%] in Laos). Aminopenicillin-gentamicin coverage was lower than that of meropenem in all countries except Laos (81.0%; 95% CrI, 71.1%-89.7%) and Nepal (74.3%; 95% CrI, 70.3%-78.2%), where 95% CrIs for aminopenicillin-gentamicin and meropenem were overlapping. Third-generation cephalosporin coverage was lowest of the 3 regimens in all countries. The coverage difference between aminopenicillin-gentamicin and meropenem for countries with nonoverlapping 95% CrIs ranged from -15.9% in China to -52.9% in Indonesia.

CONCLUSIONS AND RELEVANCE

This study's findings suggest that noncarbapenem antibiotic regimens may provide limited coverage for empirical treatment of neonatal sepsis in many Asian countries. Alternative regimens must be studied to limit carbapenem consumption.

Adjunctive therapy to treat neonatal sepsis

Introduction: Neonatal sepsis (NS) is a very severe condition that causes significant morbidity and mortality.Areas covered: To overcome the limits of antibiotic therapy and improve NS outcomes, measures chosen among those theoretically able to improve host defenses or positively interfere with deleterious immune responses could be suggested. This paper discusses the mechanisms of action of these measures, whether their efficacy in prophylaxis justifies use in NS therapy and their impact.Expert opinion: NS remains a relevant problem despite the availability of antibiotics effective against the most common agents and the introduction of effective preventive measures such as group B Streptococcus prenatal screening and intrapartum antibiotic prophylaxis. This explains why attempts to introduce new prophylactic and therapeutic measures have been made. Unfortunately, none of the measures suggested and tested to date can be considered a definitive advance. It is highly likely that in the future, new measures will be proposed according to the increase in the knowledge of the characteristics of immune system function in preterm infants and the methods to modulate unproper immune responses.

Condition-specific surveillance in health care-associated urinary tract infections as a strategy to improve empirical antibiotic treatment: an epidemiological modelling study

Background

Health care-associated urinary tract infection (HAUTI) consists of unique conditions (cystitis, pyelonephritis and urosepsis). These conditions could have different pathogen diversity and antibiotic resistance impacting on the empirical antibiotic choices. The aim of this study is to compare the estimated chances of coverage of empirical antibiotics between conditions (cystitis, pyelonephritis and urosepsis) in urology departments from Europe.

Methods

A mathematical modelling based on antibiotic susceptibility data from a point prevalence study was carried. Data were obtained for HAUTI patients from multiple urology departments in Europe from 2006 to 2017. The primary outcome of the study is the Bayesian weighted incidence syndromic antibiogram (WISCA) and Bayesian factor. Bayesian WISCA is the estimated chance of an antibiotic to cover the causative pathogens when used for first-line empirical treatment. Bayesian factor is used to compare if HAUTI conditions did or did not impact on empirical antibiotic choices.

Results

Bayesian WISCA of antibiotics in European urology departments from 2006 to 2017 ranged between 0.07 (cystitis, 2006, Amoxicillin) to 0.89 (pyelonephritis, 2009, Imipenem). Bayesian WISCA estimates were lowest in urosepsis. Clinical infective conditions had an impact on the Bayesian WISCA estimates (Bayesian factor > 3 in 81% of studied antibiotics). The main limitation of the study is the lack of local data.

Conclusions

Our estimates illustrate that antibiotic choices can be different between HAUTI conditions. Findings can improve empirical antibiotic selection towards a personalized approach but should be validated in local surveillance studies.

Electronic supplementary material

The online version of this article (10.1007/s00345-019-02963-9) contains supplementary material, which is available to authorized users.

Appropriate empiric antibiotic choices in health care associated urinary tract infections in urology departments in Europe from 2006 to 2015: A Bayesian analytical approach applied in a surveillance study

BACKGROUND

Health care associated urinary tract infections (HAUTI) is a common complicating factor of urological practice. It is unclear what the appropriate empirical antibiotic choices are and how infection control policies (ICP) influence this. The aim of this study is to use probabilistic approaches towards the problem. That is to determine the chances of coverage of empirical antibiotic choices in HAUTIs and their annual trends in Europe. In addition, the impact of departmental self-reported compliance with catheter management and regulated usage of prophylactic antibiotics policies was tested. The estimated chances of coverage of antibiotics and further probabilistic calculations are carried out using the Global Prevalence of Infections in Urology (GPIU) annual surveillance study European data.

METHODS

GPIU is a multi-state annual prevalence study conducted in urology departments to detect patients with HAUTIs, using the Center for Disease Control (CDC) definitions and antimicrobial resistance (AMR). In this analysis; the European cohort from 2005 to 2015 was used. The estimated chance of coverage for each antibiotic choice in HAUTIs was calculated using the Bayesian Weighted Incidence Syndromic Antibiogram (WISCA) approach. Annual trend of the overall cohort and number of appropriate antibiotic choices were estimated. Departments were compared according to their self-reported compliance to ICPs to determine if there was an impact on chances of coverage and appropriate antibiotic choices.

RESULTS

We estimated that in most study years less than half of the single agent antibiotics and all combination options were appropriate for empirical treatment of HAUTIs. Departments with compliance to both ICPs were estimated to have 66%(2006) to 44% (2015) more antibiotic choices compared to departments with complete lack of compliance to the ICPs. In our estimates departments with adherence to a single policy was not superior to departments with complete lack of adherence to ICPs.

CONCLUSIONS

Most single agent choices had limited coverage for HAUTIs and combination choices had improved chance of coverage. Optimal antibiotic selection decision should be part of decision experiments and tested in local surveillance studies. Departments with self-reported compliance to ICPs have more antibiotic choices and details of the compliance should be evaluated in future studies. The analysis herein showed that over the 10-year course there was no clear time trend in the chances of coverage of antibiotics (Bayesian WISCA) in European urology departments.

Using risk adjustment to improve the interpretation of global inpatient pediatric antibiotic prescribing

Objectives

Assessment of regional pediatric last-resort antibiotic utilization patterns is hampered by potential confounding from population differences. We developed a risk-adjustment model from readily available, internationally used survey data and a simple patient classification to aid such comparisons.

Design

We investigated the association between pediatric conserve antibiotic (pCA) exposure and patient / treatment characteristics derived from global point prevalence surveys of antibiotic prescribing, and developed a risk-adjustment model using multivariable logistic regression. The performance of a simple patient classification of groups with different expected pCA exposure levels was compared to the risk model.

Setting

226 centers in 41 countries across 5 continents.

Participants

Neonatal and pediatric inpatient antibiotic prescriptions for sepsis/bloodstream infection for 1281 patients.

Results

Overall pCA exposure was high (35%), strongly associated with each variable (patient age, ward, underlying disease, community acquisition or nosocomial infection and empiric or targeted treatment), and all were included in the final risk-adjustment model. The model demonstrated good discrimination (c-statistic = 0.83) and calibration (p = 0.38). The simple classification model demonstrated similar discrimination and calibration to the risk model. The crude regional pCA exposure rates ranged from 10.3% (Africa) to 67.4% (Latin America). Risk adjustment substantially reduced the regional variation, the adjusted rates ranging from 17.1% (Africa) to 42.8% (Latin America).

Conclusions

Greater comparability of pCA exposure rates can be achieved by using a few easily collected variables to produce risk-adjusted rates.

Fifteen-minute consultation: the complexities of empirical antibiotic selection for serious bacterial infections-a practical approach

Potentially life-threatening infections require immediate antibiotic therapy. Most early stage antibiotic treatment for these infections is empirical, that is, covering a range of possible target bacteria while awaiting culture results. Empirical antibiotic regimens need to reflect the epidemiology of most likely causative bacteria, type of infection and patient risk factors. Summary data from relevant isolates in similar patients help to identify appropriate empirical regimens. At present, such data are mostly presented as hospital or other aggregate antibiograms, showing antimicrobial susceptibility testing results by bacterial species. However, a more suitable method is to calculate weighted incidence syndromic combination antibiograms for different types of infections and regimens, allowing head-to-head comparisons of empirical regimens. Once there is confirmatory or negative microbiological evidence of infection, empirical regimens should be adapted to the identified bacterial species and susceptibilities or discontinued.

Surveillance of Gram-negative bacteria: impact of variation in current European laboratory reporting practice on apparent multidrug resistance prevalence in paediatric bloodstream isolates

This study evaluates whether estimated multidrug resistance (MDR) levels are dependent on the design of the surveillance system when using routine microbiological data. We used antimicrobial resistance data from the Antibiotic Resistance and Prescribing in European Children (ARPEC) project. The MDR status of bloodstream isolates of Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa was defined using European Centre for Disease Prevention and Control (ECDC)-endorsed standardised algorithms (non-susceptible to at least one agent in three or more antibiotic classes). Assessment of MDR status was based on specified combinations of antibiotic classes reportable as part of routine surveillance activities. The agreement between MDR status and resistance to specific pathogen-antibiotic class combinations (PACCs) was assessed. Based on all available antibiotic susceptibility testing, the proportion of MDR isolates was 31% for E. coli, 30% for K. pneumoniae and 28% for P. aeruginosa isolates. These proportions fell to 9, 14 and 25%, respectively, when based only on classes collected by current ECDC surveillance methods. Resistance percentages for specific PACCs were lower compared with MDR percentages, except for P. aeruginosa. Accordingly, MDR detection based on these had low sensitivity for E. coli (2-41%) and K. pneumoniae (21-85%). Estimates of MDR percentages for Gram-negative bacteria are strongly influenced by the antibiotic classes reported. When a complete set of results requested by the algorithm is not available, inclusion of classes frequently tested as part of routine clinical care greatly improves the detection of MDR. Resistance to individual PACCs should not be considered reflective of MDR percentages in Enterobacteriaceae.

How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices

OBJECTIVES

We aimed to construct widely useable summary measures of the net impact of antibiotic resistance on empiric therapy. Summary measures are needed to communicate the importance of resistance, plan and evaluate interventions, and direct policy and investment.

DESIGN, SETTING AND PARTICIPANTS

As an example, we retrospectively summarised the 2011 cumulative antibiogram from a Toronto academic intensive care unit.

OUTCOME MEASURES

We developed two complementary indices to summarise the clinical impact of antibiotic resistance and drug availability on empiric therapy. The Empiric Coverage Index (ECI) measures susceptibility of common bacterial infections to available empiric antibiotics as a percentage. The Empiric Options Index (EOI) varies from 0 to 'the number of treatment options available', and measures the empiric value of the current stock of antibiotics as a depletable resource. The indices account for drug availability and the relative clinical importance of pathogens. We demonstrate meaning and use by examining the potential impact of new drugs and threatening bacterial strains.

CONCLUSIONS

In our intensive care unit coverage of device-associated infections measured by the ECI remains high (98%), but 37-44% of treatment potential measured by the EOI has been lost. Without reserved drugs, the ECI is 86-88%. New cephalosporin/β-lactamase inhibitor combinations could increase the EOI, but no single drug can compensate for losses. Increasing methicillin-resistant Staphylococcus aureus (MRSA) prevalence would have little overall impact (ECI=98%, EOI=4.8-5.2) because many Gram-positives are already resistant to β-lactams. Aminoglycoside resistance, however, could have substantial clinical impact because they are among the few drugs that provide coverage of Gram-negative infections (ECI=97%, EOI=3.8-4.5). Our proposed indices summarise the local impact of antibiotic resistance on empiric coverage (ECI) and available empiric treatment options (EOI) using readily available data. Policymakers and drug developers can use the indices to help evaluate and prioritise initiatives in the effort against antimicrobial resistance.

Antimicrobial stewardship in paediatrics

BACKGROUND

Antibiotics are among the drugs most commonly prescribed to children in hospitals and communities. Unfortunately, a great number of these prescriptions are unnecessary or inappropriate. Antibiotic abuse and misuse have several negative consequences, including drug-related adverse events, the emergence of multidrug resistant bacterial pathogens, the development of Clostridium difficile infection, the negative impact on microbiota, and undertreatment risks. In this paper, the principle of and strategies for paediatric antimicrobial stewardship (AS) programs, the effects of AS interventions and the common barriers to development and implementation of AS programs are discussed.

DISCUSSION

Over the last few years, there have been significant shortages in the development and availability of new antibiotics; therefore, the implementation of strategies to preserve the activity of existing antimicrobial agents has become an urgent public health priority. AS is one such approach. The need for formal AS programs in paediatrics was officially recognized only recently, considering the widespread use of antibiotics in children and the different antimicrobial resistance patterns that these subjects exhibit in comparison to adult and elderly patients. However, not all problems related to the implementation of AS programs among paediatric patients are solved. The most important remaining problems involve educating paediatricians, creating a multidisciplinary interprofessional AS team able to prepare guidelines, monitoring antibiotic prescriptions and defining corrective measures, and the availability of administrative consensuses with adequate financial support. Additionally, the problem of optimizing the duration of AS programs remains unsolved. Further studies are needed to solve the above mentioned problems.

CONCLUSIONS

In paediatric patients, as in adults, the successful implementation of AS strategies has had a significant impact on reducing targeted- and nontargeted-antimicrobial use by improving the quality of care for hospitalized patients and preventing the emergence of resistance. Considering that rationalization of antibiotic misuse and abuse is the basis for reducing emergence of bacterial resistance and several clinical problems, all efforts must be made to develop multidisciplinary paediatric AS programs in hospital and community settings.