Zero or More: Methodological Challenges of Counting and Estimating Deaths Related to Antibiotic-resistant Infections

New methodology to assess the excess burden of antibiotic resistance using country-specific parameters: a case study regarding E. coli urinary tract infections

OBJECTIVES

Antimicrobial resistant (AMR) infections are a major public health problem and the burden on population level is not yet clear. We developed a method to calculate the excess burden of resistance which uses country-specific parameter estimates and surveillance data to compare the mortality and morbidity due to resistant infection against a counterfactual (the expected burden if infection was antimicrobial susceptible). We illustrate this approach by estimating the excess burden for AMR (defined as having tested positive for extended-spectrum beta-lactamases) urinary tract infections (UTIs) caused by E. coli in the Netherlands in 2018, which has a relatively low prevalence of AMR E. coli, and in Italy in 2016, which has a relatively high prevalence.

DESIGN

Excess burden was estimated using the incidence-based disability-adjusted life-years (DALYs) measure. Incidence of AMR E. coli UTI in the Netherlands was derived from ISIS-AR, a national surveillance system that includes tested healthcare and community isolates, and the incidence in Italy was estimated using data reported in the literature. A systematic literature review was conducted to find country-specific parameter estimates for disability duration, risks of progression to bacteraemia and mortality.

RESULTS

The annual excess burden of AMR E. coli UTI was estimated at 3.89 and 99.27 DALY/100 0000 population and 39 and 2786 excess deaths for the Netherlands and Italy, respectively.

CONCLUSIONS

For the first time, we use country-specific and pathogen-specific parameters to estimate the excess burden of resistant infections. Given the large difference in excess burden due to resistance estimated for Italy and for the Netherlands, we emphasise the importance of using country-specific parameters describing the incidence and disease progression following AMR and susceptible infections that are pathogen specific, and unfortunately currently difficult to locate.

Mortality Attributable to Bloodstream Infections Caused by Different Carbapenem-Resistant Gram-Negative Bacilli: Results From a Nationwide Study in Italy (ALARICO Network)

BACKGROUND

Our aim was to analyze mortality attributable to carbapenem-resistant (CR) gram-negative bacilli (GNB) in patients with bloodstream infections (BSIs).

METHODS

Prospective multicentric study including patients with GNB-BSI from 19 Italian hospitals (June 2018-January 2020). Patients were followed-up to 30 days. Primary outcomes were 30-day mortality and attributable mortality. Attributable mortality was calculated in the following groups: Klebsiella pneumoniae carbapenemase (KPC)-producing Enterobacterales, metallo-β-lactamases (MBL)-producing Enterobacterales, CR-Pseudomonas aeruginosa (CRPA), CR-Acinetobacter baumannii (CRAB). A multivariable analysis with hospital fixed-effect was built to identify factors associated with 30-day mortality. Adjusted OR (aORs) were reported. Attributable mortality was calculated according to the DRIVE-AB Consortium.

RESULTS

Overall, 1276 patients with monomicrobial GNB BSI were included: 723/1276 (56.7%) carbapenem-susceptible (CS)-GNB, 304/1276 (23.8%) KPC-, 77/1276 (6%) MBL-producing CRE, 61/1276 (4.8%) CRPA, and 111/1276 (8.7%) CRAB BSI. Thirty-day mortality in patients with CS-GNB BSI was 13.7% compared to 26.6%, 36.4%, 32.8% and 43.2% in patients with BSI by KPC-CRE, MBL-CRE, CRPA and CRAB, respectively (P < .001). On multivariable analysis, age, ward of hospitalization, SOFA score, and Charlson Index were factors associated with 30-day mortality, while urinary source of infection and early appropriate therapy resulted protective factors. Compared to CS-GNB, MBL-producing CRE (aOR 5.86, 95% CI 2.72-12.76), CRPA (aOR 1.99, 95% CI 1.48-5.95) and CRAB (aOR 2.65, 95% CI 1.52-4.61) were significantly associated with 30-day mortality. Attributable mortality rates were 5% for KPC-, 35% for MBL, 19% for CRPA, and 16% for CRAB.

CONCLUSIONS

In patients with BSIs, carbapenem-resistance is associated with an excess of mortality, with MBL-producing CRE carrying the highest risk of death.

Excess Mortality Attributable to Hospital-Acquired Antimicrobial-Resistant Infections: A 2-Year Prospective Surveillance Study in Northeast Thailand

Background

Quantifying the excess mortality attributable to antimicrobial-resistant (AMR) bacterial infections is important for assessing the potential benefit of preventive interventions and for prioritization of resources. However, there are few data from low- and middle-income countries.

Methods

We conducted a 2-year prospective surveillance study to estimate the excess mortality attributable to AMR infections for all types of hospital-acquired infection (HAI), and included bacterial species that were both locally relevant and included in the World Health Organization priority list. Twenty-eight-day mortality was measured. Excess mortality and population attributable fraction (PAF) of mortality caused by AMR infections compared to antimicrobial-susceptible (AMS) infections, adjusted for predefined confounders, were calculated.

Results

We enrolled 2043 patients with HAIs. The crude 28-day mortality of patients with AMR and AMS infections was 35.5% (491/1385) and 23.1% (152/658), respectively. After adjusting for prespecified confounders, the estimated excess mortality attributable to AMR infections was 7.7 (95% confidence interval [CI], 2.2-13.2) percentage points. This suggests that 106 (95% CI, 30-182) deaths among 1385 patients with AMR infections might have been prevented if all of the AMR infections in this study were AMS infections. The overall PAF was 16.3% (95% CI, 1.2%-29.1%). Among the bacteria under evaluation, carbapenem-resistant Acinetobacter baumannii was responsible for the largest number of excess deaths. Among all types of infection, urinary tract infections were associated with the highest number of excess deaths, followed by lower respiratory tract infections and bloodstream infections.

Conclusions

Estimating and monitoring excess mortality attributable to AMR infections should be included in national action plans to prioritize targets of preventive interventions.

Clinical Trials Registration

NCT03411538.

Oxa-376 and Oxa-530 variants of β-lactamase: computational study uncovers potential therapeutic targets of Acinetobacter baumannii

Antimicrobial resistance is a major global health crisis, resulting in thousands of deaths each year. Antibiotics' effectiveness against microorganisms deteriorates over time as multidrug resistance (MDR) develops, which is exacerbated by irregular antibiotic use, poor disease management, and the evasive nature of bacteria. The World Health Organization has recognized multidrug resistance as a critical public health concern, and Acinetobacter baumannii has been at the center of attention due to its ability to develop multidrug resistance (MDR). It generally produces carbapenem-hydrolyzing oxacillinase, which has been identified as the primary source of beta-lactam resistance in MDR bacteria. Recently, point mutations in A. baumannii have been identified as a key factor of multidrug resistance, making them a prime concern for researchers. The goal of the current work was to establish a unique way of finding multidrug-resistant variants and identify the most damaging mutations in the existing databases. We characterized the deleterious variants of oxacillinases using several computational tools. Following a thorough analysis, Oxa-376 and Oxa-530 were found to be more damaging when compared with the wild-type Oxa-51. The mutants' 3D structures were then prepared and refined with RaptorX, GalaxyRefine, and SAVES servers. Our research incorporates seven antimicrobial agents to illustrate the resistance capability of the variants of oxacillinase by evaluating binding affinity in Autodock-vina and Schrodinger software. RMSD, RMSF, Radius of gyration analysis, the solvent-accessible surface area (SASA), hydrogen bonding analysis and MM-GBSA from Molecular Dynamics Simulation revealed the dynamic nature and stability of wild-type and Oxa-376 and Oxa-530 variants. Our findings will benefit researchers looking for the deleterious mutations of Acinetobacter baumannii and new therapeutics to combat those variants. However, further studies are necessary to evaluate the mechanism of hydrolyzing activity and antibiotic resistance of these variants.

Determining novel therapeutic targets of Acinetobacter baumannii. Deleterious variants, causing antibiotic resistance, were identified by molecular docking and molecular dynamics simulation suggesting new therapeutic targets Oxa-376 and Oxa-530.

A nationwide population-based study of Escherichia coli bloodstream infections: incidence, antimicrobial resistance and mortality

OBJECTIVES

Escherichia coli is the leading cause of bloodstream infection (BSI). The incidence of E. coli BSI caused by antibiotic-resistant strains is increasing. We aimed to describe the nationwide incidence and resistance profile of E. coli BSI in Israel and its impact on mortality, to compare E. coli BSI mortality to all-cause mortality, and community-onset to hospital-onset E. coli BSI.

METHODS

We used mandatory BSI surveillance reports submitted by all Israeli hospitals to the Ministry of Health and the national death registry. All E. coli BSI from January 1, 2018, to December 31, 2019 in patients ages 18 and over were included.

RESULTS

A total of 11 113 E. coli BSI occurred in 10 218 patients; 85% (9012/10 583) were community onset. Median age was 76 (IQR 65-85), and 57% (6304/11 113) of cases occurred in women. The annual incidence was 92.5 per 100,000 population. Antibiotic resistance was frequent and significantly more common in hospital-onset than in community-onset BSI; 65% (1021/1571) vs 45% (4049/9012) were multidrug-resistant (MDR) (p<0.001). The case-fatality rate (CFR) was higher following hospital-onset BSI than community-onset: 23% (276/1214) vs 12% (926/7620) at 14 days, 31% (378/1214) vs 16% (1244/7620) at 30 days, and 55% (418/766) vs 34% (1645/4903) at 1 year (p<0.001 for all comparisons). The 1-year-CFR was 47% (1258/2707) for MDR vs 28% (928/3281) for non-MDR (p<0.001). The annual mortality rate was 31.0 per 100,000 population, comprising 4.2% (31.0/734.8) of all causes of deaths.

CONCLUSIONS

E. coli BSI carries a high burden, with a large proportion of MDR isolates, which are associated with increased incidence and CFR.

Burden of Antimicrobial Resistance: Compared to What?

The increased focus on the public health burden of antimicrobial resistance (AMR) raises conceptual challenges, such as determining how much harm multidrug-resistant organisms do compared to what, or how to establish the burden. Here, we present a counterfactual framework and provide guidance to harmonize methodologies and optimize study quality. In AMR-burden studies, 2 counterfactual approaches have been applied: the harm of drug-resistant infections relative to the harm of the same drug-susceptible infections (the susceptible-infection counterfactual); and the total harm of drug-resistant infections relative to a situation where such infections were prevented (the no-infection counterfactual). We propose to use an intervention-based causal approach to determine the most appropriate counterfactual. We show that intervention scenarios, species of interest, and types of infections influence the choice of counterfactual. We recommend using purpose-designed cohort studies to apply this counterfactual framework, whereby the selection of cohorts (patients with drug-resistant, drug-susceptible infections, and those with no infection) should be based on matching on time to infection through exposure density sampling to avoid biased estimates. Application of survival methods is preferred, considering competing events. We conclude by advocating estimation of the burden of AMR by using the no-infection and susceptible-infection counterfactuals. The resulting numbers will provide policy-relevant information about the upper and lower bound of future interventions designed to control AMR. The counterfactuals should be applied in cohort studies, whereby selection of the unexposed cohorts should be based on exposure density sampling, applying methods avoiding time-dependent bias and confounding.

Healthcare resources attributable to methicillin-resistant Staphylococcus aureus orthopedic surgical site infections

The number of orthopedic surgeries is increasing as populations steadily age, but surgical site infection (SSI) rates remain relatively consistent. This study aimed to quantify the healthcare resources attributable to methicillin-resistant Staphylococcus aureus (MRSA) SSIs in orthopedic surgical patients. The analysis was conducted using a national claims database comprising data from almost all Japanese residents. We examined patients who underwent any of the following surgeries between April 2012 and March 2018: amputation (AMP), spinal fusion (FUSN), open reduction of fracture (FX), hip prosthesis (HPRO), knee prosthesis (KPRO), and laminectomy (LAM). Propensity score matching was performed to identify non-SSI control patients, and generalized estimating equations were used to estimate the differences in outcomes between the case and control groups. The numbers of MRSA SSI cases (infection rates) ranged from 64 (0.03%) to 1,152 (2.33%). MRSA SSI-attributable increases in healthcare expenditure ranged from $11,630 ($21,151 vs. $9,521) for LAM to $35,693 ($50,122 vs. $14,429) for FX, and increases in hospital stay ranged from 40.6 days (59.2 vs. 18.6) for LAM to 89.5 days (122.0 vs. 32.5) for FX. In conclusion, MRSA SSIs contribute to substantial increases in healthcare resource utilization, emphasizing the need to implement effective infection prevention measures for orthopedic surgeries.

Quantification and interpretation of attributable mortality in core clinical infectious disease journals

Attributable mortality is an important metric that mirrors the public health effect of a potentially harmful infection by accounting not only for the effect of infection on mortality, but also for its prevalence within the target population. We did a systematic literature review to identify how attributable deaths were quantified and interpreted in core clinical infectious diseases journals between Jan 1, 2013, and April 6, 2020. Of the 1591 abstracts screened, 234 entered the primary analysis. Our summary of the epidemiological measures used in these articles reveals fundamental shortcomings in the conception of attributable mortality. Because of its importance as a basis for decision making on public health matters, it is essential to correctly quantify and report on attributable mortality. Our recommendation for quantification and reporting of attributable deaths aids clinical researchers in the correct statistical assessment of the burden of infections. Fictional as well as real data is used to illustrate these issues.