Implementing clinical bacteriology in low-resource settings: a new perspective on old methods

Antimicrobial resistance is a global public health threat. Low-resource settings are disproportionally burdened due to high incidence of infectious diseases and high rates of resistance, although representative data on antimicrobial resistance rates in low-resource settings are scarce. Moreover, antimicrobial resistance is aggravated in these settings by a lack of diagnostic tools to correctly diagnose bacterial infections, leading to suboptimal use of antibiotics. Diagnosis of bacterial infections and surveillance of antimicrobial resistance both rely on clinical bacteriology laboratories, which are underequipped, understaffed and underfunded in most low-resource settings. The gap between high-resource and low-resource settings is widening, with high-resource settings having access to new technology allowing optimal workflow, automation and fast results, whereas low-resource settings are often still using traditional techniques developed more than 50 years ago. Most of these newer technologies are out of reach for low-resource settings due to high cost, high maintenance requirements and insufficient adaptation to the harsh environmental conditions. Traditional bacteriology techniques have the advantage of being more robust to these conditions and more affordable, but there are few studies evaluating their optimal use for low-resource settings. The aim of this research was to identify and optimize methods for clinical bacteriology adapted to constraints in low-resource settings. We focused on blood cultures, because of their high value for clinical management and surveillance purposes and relative simplicity of processing. For this research, we collaborated with Médecins Sans Frontières' Mini-Lab project, which aims to develop an all-in-one, transportable clinical bacteriology laboratory for use in remote settings. Blood cultures are important in the diagnosis of bloodstream infections, which cause high morbidity and mortality, especially in low-resource settings. In high-resource settings, automated blood culture incubators are used. This technique has improved time to detection and yield of blood cultures in comparison to the traditional, so-called "manual" blood culture method, which relies on visual detection of growth. In Chapter 1, an evaluation of biphasic manual blood culture bottles, consisting of a broth (liquid phase) and agar slant (solid phase), was performed in parallel with an automated blood culture system, using simulated blood cultures. A total of 177 clinical isolates representing pathogens from low-resource settings were inoculated in three blood culture bottle types: the BacT/ALERT automated blood culture system (bioMérieux), a biphasic manual blood culture bottle (Bi-State, Autobio Diagnostics) and bottles designed for automated detection but evaluated visually (BacT/ALERT FA Plus and PF Plus, bioMérieux). Both adult and pediatric formulations of these bottle types were evaluated. Yield of manual blood culture bottles was comparable to that of the automated system (95.9% and 95.5% for manual blood culture bottles, versus 96.1% for the automated system). Growth detected by Day 1 was present in 90.7% of positive Bi-State bottles and 75.0% of manual BacT/ALERT bottles; for the automated system, 99.2% of positive bottles were detected by that time. For Bi-State bottles, growth mostly occurred simultaneously in broth and slant (81·7%). Sufficient colony growth on the slant to perform further tests was present in only 44·1% and 59·0% of biphasic bottles on Day 2 and Day 3 respectively. Blind subculture generated colonies on Day 2 for 99·7% of positive Bi-State and 99·2% of positive manual BacT/ALERT bottles respectively. In conclusion, Bi-State blood culture bottles outperformed manual BacT/ALERT bottles, but the agar slant did not allow earlier detection nor earlier colony growth. Time to detection for manual blood culture systems still lags that of automated systems In Chapter 2, we evaluated the MicroScan bacterial identification system (Beckman Coulter) for the Mini-Lab project. This identification system consists of a Gram-positive (PID3) and Gram-negative (NID2) panel. For the Mini-Lab project, the manufacturer combined both panels on one inoculation plate. These panels were evaluated with 367 clinical isolates. Robustness was studied by inoculating Gram-negative species on the Gram-positive panel and vice versa and inoculating species not represented in the MicroScan database. Usability of the panels and readability of the instructions for use (IFU) were evaluated. Of species represented in the MicroScan database, 94.6% (185/195) of Gram-negative and 85.9% (110/128) of Gram-positive isolates were correctly identified up to species level. Of species not represented in the database (e.g. Streptococcus suis and Bacillus spp.)), 53.1% out of 49 isolates were incorrectly identified as non-related bacterial species. Testing of Gram-positive isolates on Gram-negative panels and vice versa (n = 144) resulted in incorrect identifications for 38.2% of tested isolates. Readability level of the IFU was considered too high for LRS. Inoculation of the panels was favourably evaluated, whereas visual reading of the panels was considered error-prone. In conclusion, accuracy of the MicroScan identification panels was excellent for Gram-negative species and good for Gram-positive species. Improvements in stability, robustness and ease-of-use have been identified to assure adaptation to LRS constraints. The concepts of traditional techniques for low-resource settings were put in practice in Chapter 3. In Cambodia, we evaluated the optimal timing for blind subculture in a manual blood culture system (BacT/ALERT bottles evaluated visually). An aerobic/anaerobic blood culture pair was substituted by two aerobic bottles and blind subculture was advanced from day 3 to day 2 of incubation. Two years later, it was further advanced to day 1 of incubation. During the study period, 9760 blood cultures were sampled. The proportion of cultures showing pathogen growth decreased from 9.6% to 6.8% after the implementation of the laboratory changes (p<0.001). Advancing the blind subculture from day 3 to day 2 led to an increased proportion of pathogens detected by day 3 (92.8% versus 82.3%; p<0.001); for Burkholderia pseudomallei, a key pathogen in this setting, this increase was even more remarkable (92.0% versus 18.2%). Blind subculture on day 1 similarly increased the proportion of pathogens detected by day 2 (82.9% versus 69.0% overall, 66.7% versus 10.0% for Burkholderia pseudomallei; both p<0.001). However, after implementation of day 1 subculture, a decrease in recovery of Burkholderia pseudomallei was observed (12.4% of all pathogens versus 4.3%; p<0.001). In conclusion, earlier subculture significantly shortened time to detection and time to actionable results. However, some organisms may be missed by performing an early subculture, especially those that grow more slowly. Finally, blood culture surveillance was implemented in a semi-rural, secondary care hospital in Benin (Hôpital Saint Jean de Dieu de Boko). Blood cultures were sampled in BacT/ALERT FA Plus and PF Plus blood culture bottles in Boko hospital and to a lesser extent in the University hospital of Parakou. These bottles were daily inspected for visual signs of growth and incubated for 7 days in a standard incubator. During the study period of 2.5 years, 3353 blood culture bottles were sampled, corresponding to 3140 blood cultures and 3082 suspected bloodstream infection episodes. Most of these cultures (n = 2471; 78.7%) were sampled in children < 15 years of age. Pathogens were recovered from 383 (12.4%) cultures, corresponding to 381 confirmed BSI. 340 of these pathogens were available and confirmed by reference identification. The most common pathogens were Klebsiella pneumoniae (n = 53; 15.6%), Salmonella Typhi (n = 52; 15.3%) and Staphylococcus aureus (n = 46; 13.5%). AMR rates were high among Enterobacterales, with resistance to third-generation cephalosporins in 77.6% of Klebsiella pneumoniae isolates (n = 58), 12.8% of Escherichia coli isolates (n = 49) and 70.5% of Enterobacter cloacae isolates (n = 44). Carbapenemase production was detected in 2 Escherichia coli and 2 Enterobacter cloacae isolates, all of which were of the New Delhi metallo-beta lactamase type. Methicillin resistance was present in 22.4% of Staphylococcus aureus isolates (n = 49). In the Discussion of this PhD, we outlined the relevance of the findings of these studies and proposed further research directions. Methods to improve time to detection for manual blood culture bottles are needed. Early blind subculture can shorten time to detection, but its value is context-dependent and cannot be generalized over different settings. Optimization of blood culture bottle content and physical design, as well as exploring the role improved growth detection by using simple and affordable tools should be prioritized. Identification of pathogens remains challenging in low-resource settings, as exemplified both by the evaluation of the MicroScan panels and the experience using traditional identification techniques in Benin, which resulted in 55.9% of isolates being correctly identified up to species level. We proposed use of lateral-flow assays as a possible way of simplifying pathogen identification in blood cultures in low-resource settings, but culture-based methods remain necessary to perform antibiotic susceptibility testing. Contamination of blood cultures was very high in Benin and many other similar settings; innovative solutions for this problem should be encouraged as contamination leads to high costs, both financially and in terms of morbidity. Identification systems developed for low-resource settings should also be able to identify common contaminants, to facilitate the distinction with pathogens and reduce further costs and unnecessary antibiotic use. Antimicrobial resistance rates found in Benin were worrying and prompted questions about adequacy of empiric treatments. More quality-assured studies are needed to further map out antimicrobial resistance in low-resource settings; empiric antibiotic guidelines should be guided by this information. To ensure successful antibiotic stewardship in low-resource settings, further efforts to strengthen clinical bacteriology laboratories at the secondary care level are required. Blood culture implementation in low-resource settings is a feasible way of ensuring antimicrobial resistance surveillance and appropriate diagnosis of bacterial infections, but requires sustained financial and logistic support from high-income countries for the foreseeable future. Quality of laboratory staff has been shown to be key to good performance of such laboratories and this is a resource worth investing in. Re-appraisal of educational standards for laboratory staff may be instrumental in achieving this goal.

Publication year:2022

Accessibility:Embargoed