Impact of Gram-Negative Bacilli Resistance Rates on Risk of Death in Septic Shock and Pneumonia.

Background: Sepsis is a major cause of morbidity and mortality worldwide. When selecting empiric antibiotics for sepsis, clinicians are encouraged to use local resistance rates, but their impact on individual outcomes is unknown. Improved methods to predict outcomes are needed to optimize treatment selection and improve antibiotic stewardship. Methods: We expanded on a previously developed theoretical model to estimate the excess risk of death in gram-negative bacilli (GNB) sepsis due to discordant antibiotics using 3 factors: the prevalence of GNB in sepsis, the rate of antibiotic resistance in GNB, and the mortality difference between discordant and concordant antibiotic treatments. We focused on ceftriaxone, cefepime, and meropenem as the anti-GNB treatment backbone in sepsis, pneumonia, and urinary tract infections. We analyzed both publicly available data and data from a large urban hospital. Results: Publicly available data were weighted toward culture-positive cases. Excess risk of death with discordant antibiotics was highest in septic shock and pneumonia. In septic shock, excess risk of death was 4.53% (95% confidence interval [CI], 4.04%-5.01%), 0.6% (95% CI, .55%-.66%), and 0.19% (95% CI, .16%-.21%) when considering resistance to ceftriaxone, cefepime, and meropenem, respectively. Results were similar in pneumonia. Local data, which included culture-negative cases, showed an excess risk of death in septic shock of 0.75% (95% CI, .57%-.93%) for treatment with discordant antibiotics in ceftriaxone-resistant infections and 0.18% (95% CI, .16%-.21%) for cefepime-resistant infections. Conclusions: Estimating the excess risk of death for specific sepsis phenotypes in the context of local resistance rates, rather than relying on population resistance data, may be more informative in deciding empiric antibiotics in GNB infections.

Assessment of antibodies in the upper and lower human respiratory tract at steady state and after respiratory viral infection.

Objectives: There is an increasing appreciation for the need to study mucosal antibody responses in humans. Our aim was to determine the utility of different types of samples from the human respiratory tract, specifically nasopharyngeal (NP) swabs obtained for diagnostic purposes and bronchoalveolar lavage (BAL) obtained in outpatient and inpatient settings. Methods: We analysed antibody levels in plasma and NP swabs from 67 individuals with acute influenza as well as plasma and BAL from individuals undergoing bronchoscopy, including five control subjects as well as seven moderately and seven severely ill subjects with a respiratory viral infection. Levels of α2-macroglobulin were determined in BAL and plasma to assess plasma exudation. Results: IgG and IgA were readily detectable in BAL and NP swabs, albeit at different ratios, while IgM levels were low. The total amount of antibody recovered from NP swabs varied greatly between study participants. Accordingly, the levels of influenza HA-specific antibodies varied, and individuals with lower amounts of total Ig in NP swabs had undetectable levels of HA-specific Ig. Similarly, the total amount of antibody recovered from BAL varied between study participants. However, severely ill patients showed evidence of increased plasma exudation, which may confound analysis of their BAL samples for mucosal antibodies. Conclusion: Nasopharyngeal swabs collected for diagnostic purposes may have utility in assessing antibodies from the human nasal mucosa, but variability in sampling should be accounted for. BAL samples can be utilised to study antibodies from the lower respiratory tract, but the possibility of plasma exudation should be excluded.

Addition of aminoglycosides reduces recurrence of infections with multidrug-resistant Gram-negative bacilli in patients with sepsis and septic shock.

OBJECTIVES: Aminoglycosides and ß-lactams have been recommended for treatment of sepsis/septic shock despite a lack of mortality benefit. Previous studies have examined resistance emergence for the same bacterial isolate using old dosing regimens and during a narrow follow-up window. We hypothesised that combination regimens employing aminoglycosides will decrease the cumulative incidence of infections due to multidrug-resistant (MDR) Gram-negative bacilli (GNB) compared with ß-lactams alone. METHODS: All adult patients admitted to Barnes Jewish Hospital between 2010 and 2017 with a diagnosis of sepsis/septic shock were included in this retrospective cohort study. Patients were divided into two treatment groups, with and without aminoglycosides. Patient demographics, severity of presentation, administered antibiotics, follow-up cultures with susceptibility results for a period of 4-60 days, and mortality were extracted. After propensity score matching, a Fine-Gray subdistribution proportional hazards model summarised the estimated incidence of subsequent infections with MDR-GNB in the presence of all-cause death as a competing risk. RESULTS: A total of 10 212 septic patients were included, with 1996 (19.5%) treated with at least two antimicrobials including one aminoglycoside. After propensity score matching, the cumulative incidence of MDR-GNB infections between 4-60 days was lower in the combination group (incidence at 60 days 0.073, 95% CI 0.062-0.085) versus patients not receiving aminoglycosides (0.116, 95% CI 0.102-0.130). Patients aged ≤65 years and with haematological malignancies had a larger treatment effect in subgroup analyses. CONCLUSION: Addition of aminoglycosides to ß-lactams may protect against subsequent infections due to MDR-GNB in patients with sepsis/septic shock.

Antibiotic Decision-Making in the ICU.

It is well established that Intensive Care Units (ICUs) are a focal point in antimicrobial consumption with a major influence on the ecological consequences of antibiotic use. With the high prevalence and mortality of infections in critically ill patients, and the clinical challenges of treating patients with septic shock, the impact of real life clinical decisions made by intensivists becomes more significant. Both under- and over-treatment with unnecessarily broad spectrum antibiotics can lead to detrimental outcomes. Even though substantial progress has been made in developing rapid diagnostic tests that can help guide antibiotic use, there is still a time window when clinicians must decide the empiric antibiotic treatment with insufficient clinical data. The continuous streams of data available in the ICU environment make antimicrobial optimization an ongoing challenge for clinicians but at the same time can serve as the input for sophisticated models. In this review, we summarize the evidence to help guide antibiotic decision-making in the ICU. We focus on 1) deciding IF: to start antibiotics, 2) choosing the spectrum of the empiric agents to use, and 3) de-escalating the chosen empiric antibiotics. We provide a perspective on the role of machine learning and artificial intelligence models for clinical decision support systems that can be incorporated seamlessly into clinical practice in order to improve the antibiotic selection process and, more importantly, current and future patients' outcomes.

Impact of Baseline Characteristics on Future Episodes of Bloodstream Infections: Multistate Model in Septic Patients With Bloodstream Infections.

BACKGROUND: Looking only at the index infection, studies have described risk factors for infections caused by resistant bacteria. We hypothesized that septic patients with bloodstream infections may transition across states characterized by different microbiology and that their trajectory is not uniform. We also hypothesized that baseline risk factors may influence subsequent blood culture results. METHODS: All adult septic patients with positive blood cultures over a 7-year period were included in the study. Baseline risk factors were recorded. We followed all survivors longitudinally and recorded subsequent blood culture results. We separated states into bacteremia caused by gram-positive cocci, susceptible gram-negative bacilli (sGNB), resistant GNB (rGNB), and Candida spp. Detrimental transitions were considered when transitioning to a culture with a higher mortality risk (rGNB and Candida spp.). A multistate Markov-like model was used to determine risk factors associated with detrimental transitions. RESULTS: A total of 990 patients survived and experienced at least 1 transition, with a total of 4282 transitions. Inappropriate antibiotics, previous antibiotic exposure, and index bloodstream infection caused by either rGNB or Candida spp. were associated with detrimental transitions. Double antibiotic therapy (beta-lactam plus either an aminoglycoside or a fluoroquinolone) protected against detrimental transitions. CONCLUSION: Baseline characteristics that include prescribed antibiotics can identify patients at risk for subsequent bloodstream infections caused by resistant bacteria. By altering the initial treatment, we could potentially influence future bacteremic states.

Novel Approaches to Hasten Detection of Pathogens and Antimicrobial Resistance in the Intensive Care Unit.

Antibiotic resistance is recognized as a key determinant of outcome in patients with serious infections influencing empiric antibiotic practices especially for critically ill patients. Within the intensive care unit (ICU), nosocomial infections and increasingly community-onset infections are caused by multidrug-resistant bacteria. Escalating rates of antibiotic resistance adds substantially to the morbidity, mortality, and cost related to infections treated in the ICU. Both gram-positive organisms, such as methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci, and gram-negative bacteria, including Pseudomonas aeruginosa, Acinetobacter species, carbapenem-resistant Enterobacteriaceae, and extended spectrum ß-lactamase producing organisms, are urgent threats. The rising rates of antimicrobial resistance have resulted in routine empiric administration of broad-spectrum antibiotics by clinicians to critically ill patients even when bacterial infection is microbiologically absent. Moreover, new broad-spectrum antibiotics are a challenge to use effectively while avoiding emergence of further resistance. Use of rapid diagnostic technologies (RDTs) will likely provide an important methodology for achieving this important balance. There is an urgent need for integrating the administration of new and existing antibiotics with RDTs in a way that is safe, cost-effective, applicable in all countries, and sustainable.

Host-Pathogen-Treatment Triad: Host Factors Matter Most in Methicillin-Resistant Staphylococcus aureus Bacteremia Outcomes.

Previous studies have separately emphasized the importance of host, pathogen, and treatment characteristics in determining short-term or in-hospital mortality rates for patients with methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections. Less is known about the relative importance of these factors and their interactions in determining short-, medium-, and long-term mortality rates. This is an observational cohort study in which data for all patients admitted to the University of New Mexico (UNM) Health Sciences Center (HSC) between July 2002 and August 2013 with MRSA-positive blood cultures were recorded. We collected patients' demographics and treatment data, as well as data on genetic markers of the MRSA isolates. Outcomes of interest were determinants of short-term (within 30 days), medium-term (30 to 90 days), and long-term (>90 days) mortality rates. This study included 273 patients with MRSA bacteremia. Short-, medium-, and long-term mortality rates were 18.7%, 26.4%, and 48%, respectively. Thirty-day mortality rates were influenced by host variables and host-pathogen interaction characteristics. Pitt bacteremia scores, malignancy, and health care exposure contributed to 30- to 90-day mortality rates, while treatment duration of >4 weeks had a protective effect. Age remained a significant risk factor for death at >90 days, while admission leukocytosis was protective. Infection represented the most frequent cause of death for all three time frames; rates varied from 72.6% in the first 30 days and 60% for 30 to 90 days to 35.7% for >90 days (P = 0.003). Host characteristics affect short-, medium-, and long-term mortality rates for MRSA bloodstream infections more than do pathogen genetic markers and treatment factors.