Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Molecular Typing of Acinetobacter baumannii in Comparison with Orthogonal Methods.

Colonization and subsequent health care-associated infection (HCAI) with Acinetobacter baumannii are a concern for vulnerable patient groups within the hospital setting. Outbreaks involving multidrug-resistant strains are associated with increased patient morbidity and mortality and poorer overall outcomes. Reliable molecular typing methods can help to trace transmission routes and manage outbreaks. In addition to methods deployed by reference laboratories, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) may assist by making initial in-house judgments on strain relatedness. However, limited studies on method reproducibility exist for this application. We applied MALDI-TOF MS typing to A. baumannii isolates associated with a nosocomial outbreak and evaluated different methods for data analysis. In addition, we compared MALDI-TOF MS with whole-genome sequencing (WGS) and Fourier transform infrared spectroscopy (FTIR) as orthogonal methods to further explore their resolution for bacterial strain typing. A related subgroup of isolates consistently clustered separately from the main outbreak group by all investigated methods. This finding, combined with epidemiological data from the outbreak, indicates that these methods identified a separate transmission event unrelated to the main outbreak. However, the MALDI-TOF MS upstream approach introduced measurement variability impacting method reproducibility and limiting its reliability as a standalone typing method. Availability of in-house typing methods with well-characterized sources of measurement uncertainty could assist with rapid and dependable confirmation (or denial) of suspected transmission events. This work highlights some of the steps to be improved before such tools can be fully integrated into routine diagnostic service workflows for strain typing. IMPORTANCE Managing the transmission of antimicrobial resistance necessitates reliable methods for tracking outbreaks. We compared the performance of MALDI-TOF MS with orthogonal approaches for strain typing, including WGS and FTIR, for Acinetobacter baumannii isolates correlated with a health care-associated infection (HCAI) event. Combined with epidemiological data, all methods investigated identified a group of isolates that were temporally and spatially linked to the outbreak, yet potentially attributed to a separate transmission event. This may have implications for guiding infection control strategies during an outbreak. However, the technical reproducibility of MALDI-TOF MS needs to be improved for it to be employed as a standalone typing method, as different stages of the experimental workflow introduced bias influencing interpretation of biomarker peak data. Availability of in-house methods for strain typing of bacteria could improve infection control practices following increased reports of outbreaks of antimicrobial-resistant organisms during the COVID-19 pandemic, related to sessional usage of personal protective equipment (PPE).

Antimicrobial stewardship in solid organ transplant-Opportunities in the National Health Service.

BACKGROUND: Antimicrobial stewardship (AMS) is an intervention, which ensures the appropriateness of antimicrobial use to avoid in part the rising problem of antimicrobial resistance and negative effects of inappropriate antimicrobial use. In the solid organ transplant (SOT) population, which is prone to a particularly high risk of infection resulting from immunosuppression and anatomical issues with each type of SOT, the need for good stewardship has never been more important. This article looks at current AMS practice in SOT units in the United Kingdom and how things could be improved in the future. METHODS: The current practice of AMS alongside national antimicrobial resistance rates were reviewed using national mandatory reporting data. The background to the current practice and policies in place in the National Health Service (NHS) were also reviewed and possibilities for future approaches explored. RESULTS: AMS is a requirement within all NHS hospitals in the United Kingdom as per government policy. Mandatory reporting of specific bloodstream infections (BSIs) and antimicrobial consumption alongside financial incentives has been the approach nationwide. Gram-negative resistance rates in BSIs have been increasing prior to the COVID-19 pandemic. Little SOT-specific data on antimicrobial resistance exists, and the general approach to AMS in SOT units has generally modeled the national approach. CONCLUSION: Although there is a good, standardized approach to AMS in the NHS, there is a need for SOT-specific AMS approaches to be developed in the United Kingdom. More data is required on antimicrobial resistance rates, and studies are needed to investigate optimal antimicrobial prophylaxis regimens for each solid organ group. Tools to aid AMS efforts and novel treatment options for complex multiresistant infection must also be explored amongst transplant centers.

Comparative assessment of viral dynamic models for SARS-CoV-2 for pharmacodynamic assessment in early treatment trials.

Pharmacometric analyses of time series viral load data may detect drug effects with greater power than approaches using single time points. Because SARS-CoV-2 viral load rapidly rises and then falls, viral dynamic models have been used. We compared different modelling approaches when analysing Phase II-type viral dynamic data. Using two SARS-CoV-2 datasets of viral load starting within 7 days of symptoms, we fitted the slope-intercept exponential decay (SI), reduced target cell limited (rTCL), target cell limited (TCL) and TCL with eclipse phase (TCLE) models using nlmixr. Model performance was assessed via Bayesian information criterion (BIC), visual predictive checks (VPCs), goodness-of-fit plots, and parameter precision. The most complex (TCLE) model had the highest BIC for both datasets. The estimated viral decline rate was similar for all models except the TCL model for dataset A with a higher rate (median [range] day-1 : dataset A; 0.63 [0.56-1.84]; dataset B: 0.81 [0.74-0.85]). Our findings suggest simple models should be considered during pharmacodynamic model development.

Exclusion of bacterial co-infection in COVID-19 using baseline inflammatory markers and their response to antibiotics.

BACKGROUND: COVID-19 is infrequently complicated by bacterial co-infection, but antibiotic prescriptions are common. We used community-acquired pneumonia (CAP) as a benchmark to define the processes that occur in bacterial pulmonary infections, testing the hypothesis that baseline inflammatory markers and their response to antibiotic therapy could distinguish bacterial co-infection from COVID-19. METHODS: Retrospective cohort study of CAP (lobar consolidation on chest radiograph) and COVID-19 (PCR detection of SARS-CoV-2) patients admitted to Royal Free Hospital (RFH) and Barnet Hospital (BH), serving as independent discovery and validation cohorts. All CAP and >90% COVID-19 patients received antibiotics on hospital admission. RESULTS: We identified 106 CAP and 619 COVID-19 patients at RFH. Compared with COVID-19, CAP was characterized by elevated baseline white cell count (WCC) [median 12.48 (IQR 8.2-15.3) versus 6.78 (IQR 5.2-9.5) ×106 cells/mL, P < 0.0001], C-reactive protein (CRP) [median 133.5 (IQR 65-221) versus 86.0 (IQR 42-160) mg/L, P < 0.0001], and greater reduction in CRP 48-72 h into admission [median ΔCRP -33 (IQR -112 to +3.5) versus +14 (IQR -15.5 to +70.5) mg/L, P < 0.0001]. These observations were recapitulated in the independent validation cohort at BH (169 CAP and 181 COVID-19 patients). A multivariate logistic regression model incorporating WCC and ΔCRP discriminated CAP from COVID-19 with AUC 0.88 (95% CI 0.83-0.94). Baseline WCC >8.2 × 106 cells/mL or falling CRP identified 94% of CAP cases, and excluded bacterial co-infection in 46% of COVID-19 patients. CONCLUSIONS: We propose that in COVID-19, absence of both elevated baseline WCC and antibiotic-related decrease in CRP can exclude bacterial co-infection and facilitate antibiotic stewardship efforts.