Effects of antibiotic resistance, drug target attainment, bacterial pathogenicity and virulence, and antibiotic access and affordability on outcomes in neonatal sepsis: an international microbiology and drug evaluation prospective substudy (BARNARDS)

Abstract

Background: Sepsis is a major contributor to neonatal mortality, particularly in low-income and middle-income countries (LMICs). WHO advocates ampicillin-gentamicin as first-line therapy for the management of neonatal sepsis. In the BARNARDS observational cohort study of neonatal sepsis and antimicrobial resistance in LMICs, common sepsis pathogens were characterised via whole genome sequencing (WGS) and antimicrobial resistance profiles. In this substudy of BARNARDS, we aimed to assess the use and efficacy of empirical antibiotic therapies commonly used in LMICs for neonatal sepsis.

Methods: In BARNARDS, consenting mother-neonates aged 0-60 days dyads were enrolled on delivery or neonatal presentation with suspected sepsis at 12 BARNARDS clinical sites in Bangladesh, Ethiopia, India, Pakistan, Nigeria, Rwanda, and South Africa. Stillborn babies were excluded from the study. Blood samples were collected from neonates presenting with clinical signs of sepsis, and WGS and minimum inhibitory concentrations for antibiotic treatment were determined for bacterial isolates from culture-confirmed sepsis. Neonatal outcome data were collected following enrolment until 60 days of life. Antibiotic usage and neonatal outcome data were assessed. Survival analyses were adjusted to take into account potential clinical confounding variables related to the birth and pathogen. Additionally, resistance profiles, pharmacokinetic-pharmacodynamic probability of target attainment, and frequency of resistance (ie, resistance defined by in-vitro growth of isolates when challenged by antibiotics) were assessed. Questionnaires on health structures and antibiotic costs evaluated accessibility and affordability.

Findings: Between Nov 12, 2015, and Feb 1, 2018, 36 285 neonates were enrolled into the main BARNARDS study, of whom 9874 had clinically diagnosed sepsis and 5749 had available antibiotic data. The four most commonly prescribed antibiotic combinations given to 4451 neonates (77·42%) of 5749 were ampicillin-gentamicin, ceftazidime-amikacin, piperacillin-tazobactam-amikacin, and amoxicillin clavulanate-amikacin. This dataset assessed 476 prescriptions for 442 neonates treated with one of these antibiotic combinations with WGS data (all BARNARDS countries were represented in this subset except India). Multiple pathogens were isolated, totalling 457 isolates. Reported mortality was lower for neonates treated with ceftazidime-amikacin than for neonates treated with ampicillin-gentamicin (hazard ratio [adjusted for clinical variables considered potential confounders to outcomes] 0·32, 95% CI 0·14-0·72; p=0·0060). Of 390 Gram-negative isolates, 379 (97·2%) were resistant to ampicillin and 274 (70·3%) were resistant to gentamicin. Susceptibility of Gram-negative isolates to at least one antibiotic in a treatment combination was noted in 111 (28·5%) to ampicillin-gentamicin; 286 (73·3%) to amoxicillin clavulanate-amikacin; 301 (77·2%) to ceftazidime-amikacin; and 312 (80·0%) to piperacillin-tazobactam-amikacin. A probability of target attainment of 80% or more was noted in 26 neonates (33·7% [SD 0·59]) of 78 with ampicillin-gentamicin; 15 (68·0% [3·84]) of 27 with amoxicillin clavulanate-amikacin; 93 (92·7% [0·24]) of 109 with ceftazidime-amikacin; and 70 (85·3% [0·47]) of 76 with piperacillin-tazobactam-amikacin. However, antibiotic and country effects could not be distinguished. Frequency of resistance was recorded most frequently with fosfomycin (in 78 isolates [68·4%] of 114), followed by colistin (55 isolates [57·3%] of 96), and gentamicin (62 isolates [53·0%] of 117). Sites in six of the seven countries (excluding South Africa) stated that the cost of antibiotics would influence treatment of neonatal sepsis.

Interpretation: Our data raise questions about the empirical use of combined ampicillin-gentamicin for neonatal sepsis in LMICs because of its high resistance and high rates of frequency of resistance and low probability of target attainment. Accessibility and affordability need to be considered when advocating antibiotic treatments with variance in economic health structures across LMICs.

Funding: The Bill & Melinda Gates Foundation.

Figure 1

Study profile The diagram shows the process of isolate selection for inclusion in this study, as a substudy from the main BARNARDS project and subsets used for analyses. BARNARDS=Burden of Antibiotic Resistance in Neonates from Developing Societies. WGS=whole genome sequencing. MIC=minimum inhibitory concentration.

Figure 2

Survival analysis for neonates treated with each antibiotic therapy Analysis was done for 476 neonates through Cox regression hazard ratios, adjusted for clinical factors. Clinical variables considered included cohort, sex, type of pathogen (ie, Gram-negative vs Gram-positive); whether the neonate was delivered via caesarean section; and whether the neonate was premature (appendix, pp 14–15) and stratified for onset of sepsis (early-onset sepsis or late-onset sepsis) to meet proportional hazard assumptions. For the purpose of this survival curve, the following clinical variables were set: male sex, inborn cohort, early-onset sepsis, Gram-negative sepsis pathogen type, no caesarean section, and no premature neonates.

Figure 3

Antibiotic resistance profiles according to EUCAST version 9.0 (2019) (A) 390 Gram-negative isolates were tested against 20 antibiotics (minocycline is not shown as there is no defined breakpoint in EUCAST for Gram-negative species). (B) 55 Gram-positive isolates (33 for azithromycin) were tested against a panel of 14 antibiotics. Resistance profiles for 13 of 14 antibiotics tested against Gram-positive bacteria are shown (ampicillin is not shown as there is no defined breakpoint in EUCAST for Staphylococcus aureus against ampicillin, because most Staphylococci are penicillinase producers making them resistant to ampicillin). Breakpoints for oxacillin and flucloxacillin are based on the assumption that isolates with MIC >2 mg/L are resistant because they carry mecA or mecC. These were also evaluated as meticillin-resistant S aureus (45·5% of isolates). MIC₅₀ and MIC₉₀ results are in the appendix, pp 7–8. EUCAST=European Committee on Antimicrobial Susceptibility Testing. MIC=minimum inhibitory concentration.

Figure 4

Probability of target attainment of commonly used antibiotic combination treatments (A–D) Relationship between simulated probability of target attainment values and MIC values for four antibiotic combination therapies for 290 neonates treated empirically with no following change in treatment. Vertical and horizontal lines represent ranges of MIC breakpoints according to EUCAST. Size of the bubbles indicates the frequency of isolates with associated MICs. (E) Comparison of simulated probability of target attainment values ≥80% (mean [1·96 SD]) and observed survival rate. (F) Simulated probability of target attainment values for the four combination therapies, compared with meropenem (10mg/kg every 8 h), fosfomycin (200 mg/kg every 12 h), and colistin (5 mg/kg per day), based on observed MIC distributions for these antibiotics. MIC=minimum inhibitory concentration. EUCAST=European Committee on Antimicrobial Susceptibility Testing.

Figure 5

Frequency of resistance for Gram-negative isolates Numbers included in the analysis and mean growth per mL were: amikacin n=117, 3·75 × 10⁻⁴; amoxicillin–clavulanate n=24, 2·50 × 10⁻³; ampicillin n=6, 6·67 × 10⁻⁷; ceftazidime n=52, 1·92 × 10⁻⁴; colistin n=96, 4·17 × 10⁻⁴; fosfomycin n=114, 3·59 × 10⁻⁴; gentamicin n=117, 4·45 × 10⁻³; meropenem n=117, 0·00; and piperacillin–tazobactam n=102, 1·97 × 10⁻⁴. The numbers of isolates differed across antibiotics because of susceptibility patterns, with only sensitive bacteria suitable for frequency of resistance determination. Data are presented per mL and the frequency of resistance calculated from growth at a lower dilution on control plates free from antibiotics. Results have been log-transformed with a standard of 1 × 10⁻¹⁰ added to enable incorporation of zero values. This standard was chosen as the lowest rate of frequency of resistance found was 1 × 10⁻⁹.