Penicillin allergy as an instrumental variable for estimating antibiotic effects on resistance

Antibiotic resistance is influenced by prior antibiotic use, but precise causal estimates are limited. This study uses penicillin allergy as an instrumental variable (IV) to estimate the causal effect of antibiotics on resistance. A retrospective cohort of 36,351 individuals with E. coli positive urine cultures and prior outpatient antibiotic use, with outcomes assessed up to one year post-exposure, was analyzed using data from Maccabi Healthcare Services (MHS), the second-largest non-profit health fund in Israel. IV methods estimated risk differences (RD) and numbers needed to harm (NNH) for penicillin versus other antibiotics. The RD for resistance was 11.4% (95% CI: 7.6%, 15.4%) for amoxicillin/clavulanic acid, 14.1% (95% CI: 9.0%, 19.4%) for ampicillin, and 0.8% (95% CI: 0.2%, 1.4%) for piperacillin/tazobactam, with NNHs of 8.8, 7.1, and 122.0, respectively. Risks declined over time since exposure. Gentamicin, used as a negative control, showed no effect (95% CI: -2.4%, 1.8%). When directly comparing penicillin and quinolone effects on their respective AMR, penicillin use within 180 days increased resistance to amoxicillin/clavulanic acid by an RD of 17.8% (95% CI: 2.1%, 35.2%; NNH: 5.6), while quinolones raised ciprofloxacin resistance by 43.9% (95% CI: 29.9%, 59.4%; NNH: 2.3). These findings provide quantitative evidence of the impact of prior penicillin use on resistance, with implications for clinical practice and prescription policies.

Population pharmacokinetic meta-analysis of five beta-lactams antibiotics to support dosing regimens in dogs for surgical antimicrobial prophylaxis

The Pharmacokinetic/Pharmacodynamic (PK/PD) relationship of antimicrobial drugs (AMD) for surgical prophylaxis has been poorly studied, hampering evidence-based decision making around AMD dosing and timing. Our objective is to use PK/PD principles to inform (1) the timing of administration and (2) the interval for re-administration of AMD used peri-operatively in dogs. Raw plasma concentrations of cefazolin, cefuroxime, cefalexin, amoxicillin and ampicillin were retrieved from original intravenous studies performed in dogs. E. coli and methicillin-susceptible staphylococci were identified as possible intraoperative contaminants and their epidemiological cut-offs (ECOFF) were retrieved from the EUCAST database. Individual PK data were refitted with non-linear mixed effect models (Phoenix®). We performed Monte Carlo simulation to compute i) the 95th percentile of time of peak concentration in the peripheral compartment (informing timing between administration and first incision) and ii) the duration for which at least 90% of dogs maintain a free plasma concentration above ECOFF (informing timing of re-administration: 1.5-4 h). Cefazolin (22-25 mg/kg), cefuroxime (20 mg/kg), cefalexin (15 mg/kg) and amoxicillin (16.7 mg/kg) reached peak peripheral concentrations within 30 min, but ampicillin (20 mg/kg) required 82 min, respectively. For methicillin-susceptible staphylococci, cefazolin and cefuroxime require re-administration every 2 h, whereas cefalexin and both amoxicillin and ampicillin can be readministered every 3 and 4 h, respectively. For E. coli, only cefazolin provided adequate perioperative coverage with 2-hourly administration, where cefuroxime and cefalexin failed uniformly. Alternatively, ampicillin and amoxicillin (critically ill dogs) may cover E. coli contaminations, but only if readministered every 1.5 h. These PK-derived conclusions provide a rationale for perioperative AMD administration timing.

The straight and narrow: A game theory model of broad- and narrow-spectrum empiric antibiotic therapy

Physicians prescribe empiric antibiotic treatment when definitive knowledge of the pathogen causing an infection is lacking. The options of empiric treatment can be largely divided into broad- and narrow-spectrum antibiotics. Prescribing a broad-spectrum antibiotic increases the chances of covering the causative pathogen, and hence benefits the current patient's recovery. However, prescription of broad-spectrum antibiotics also accelerates the expansion of antibiotic resistance, potentially harming future patients. We analyse the social dilemma using game theory. In our game model, physicians choose between prescribing broad and narrow-spectrum antibiotics to their patients. Their decisions rely on the probability of an infection by a resistant pathogen before definitive laboratory results are available. We prove that whenever the equilibrium strategies differ from the socially optimal policy, the deviation is always towards a more excessive use of the broad-spectrum antibiotic. We further show that if prescribing broad-spectrum antibiotics only to patients with a high probability of resistant infection is the socially optimal policy, then decentralization of the decision making may make this policy individually irrational, and thus sabotage its implementation. We discuss the importance of improving the probabilistic information available to the physician and promoting centralized decision making.

Prediction of ciprofloxacin resistance in hospitalized patients using machine learning

BACKGROUND

Ciprofloxacin is a widely used antibiotic that has lost efficiency due to extensive resistance. We developed machine learning (ML) models that predict the probability of ciprofloxacin resistance in hospitalized patients.

METHODS

Data were collected from electronic records of hospitalized patients with positive bacterial cultures, during 2016-2019. Susceptibility results to ciprofloxacin (n = 10,053 cultures) were obtained for Escherichia coli, Klebsiella pneumoniae, Morganella morganii, Pseudomonas aeruginosa, Proteus mirabilis and Staphylococcus aureus. An ensemble model, combining several base models, was developed to predict ciprofloxacin resistant cultures, either with (gnostic) or without (agnostic) information on the infecting bacterial species.

RESULTS

The ensemble models' predictions are well-calibrated, and yield ROC-AUCs (area under the receiver operating characteristic curve) of 0.737 (95%CI 0.715-0.758) and 0.837 (95%CI 0.821-0.854) on independent test-sets for the agnostic and gnostic datasets, respectively. Shapley additive explanations analysis identifies that influential variables are related to resistance of previous infections, where patients arrived from (hospital, nursing home, etc.), and recent resistance frequencies in the hospital. A decision curve analysis reveals that implementing our models can be beneficial in a wide range of cost-benefits considerations of ciprofloxacin administration.

CONCLUSIONS

This study develops ML models to predict ciprofloxacin resistance in hospitalized patients. The models achieve high predictive ability, are well calibrated, have substantial net-benefit across a wide range of conditions, and rely on predictors consistent with the literature. This is a further step on the way to inclusion of ML decision support systems into clinical practice.

The time-varying association between previous antibiotic use and antibiotic resistance

OBJECTIVES

The objective of the study was to estimate how the time elapsed from previous antibiotic use is associated with antibiotic resistance.

METHODS

Data comprised electronic medical records of all patients in an Israeli hospital who had a positive bacterial culture from 2016 to 2019. These included susceptibility testing results and clinical and demographic data. Mixed-effects time-varying logistic models were fitted to estimate the association between the time elapsed since the last use of aminoglycosides and gentamicin resistance (n = 13 095), cephalosporins and ceftazidime resistance (n = 13 051), and fluoroquinolones and ciprofloxacin resistance (n = 15 364) while adjusting for multiple covariates.

RESULTS

For all examined antibiotics, previous antibiotic use had a statistically significant association with resistance (p < 0.001). These associations exhibited a clear decreasing pattern over time, which we present as a flexible function of time. Nonetheless, previous antibiotic use remained a significant risk factor for resistance for at least 180 days when the adjusted ORs were 1.94 (95% CI, 1.40-2.69), 1.33 (95% CI, 1.10-1.61), and 2.25 (95% CI, 1.49-3.41) for gentamicin, ceftazidime, and ciprofloxacin, respectively.

DISCUSSION

The association between prior antibiotic use and resistance decreases over time. Commonly used cut-offs for prior antibiotic use can either misclassify patients still at higher risk when too recent or provide a diluted estimate of the effects of antibiotic use on future resistance when too distant. Hence, prior antibiotic use should be considered a time-dependent risk factor for resistance in both epidemiological research and clinical practice.

Beta-lactam induced morphological changes in serum of extended-spectrum beta-lactamase-producing Klebsiella pneumoniae blood isolates

Klebsiella pneumoniae is an opportunistic pathogen, which frequently causes bacteremia. Ceftazidime and meropenem, two important beta-lactam antibiotics for treatment of K. pneumoniae infections, induce morphological changes in bacteria when examined in vitro. Thirty clinical Klebsiella spp. Bacteremia isolates were analyzed for antimicrobial resistance and serum resistance. To determine whether complement influenced the resistance to ceftazidime of extended-spectrum beta-lactamase producing-isolates and sensitivity to meropenem, one serum resistant and one partly serum sensitive isolate were analyzed in normal human serum, heat-inactivated human serum, and growth medium with addition of beta-lactam antibiotics. HA391 was resistant to ceftazidime and had identical minimum inhibitory concentrations for meropenem in normal human serum, heat-inactivated serum and RPMI. In normal human serum, HA233 was inhibited by ceftazidime and had lower inhibitory concentrations of meropenem. Morphological changes induced by serum and beta-lactam antibiotics were analyzed by light- and electron microscopy. Light microscopy showed elongation of bacteria treated with ceftazidime. By electron microscopy membrane attack complexes were observed for HA233 in normal human serum, thereby facilitating beta-lactam antibiotics access to the periplasmic space and the peptidoglycan layer, explaining the increased killing of HA233 by beta-lactam antibiotics. Complement did not enhance beta-lactam killing of HA391, underlining the importance of serum susceptibility.