Vaginal colonization with antimicrobial-resistant bacteria among women in labor in central Uganda: prevalence and associated factors

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Study Justification:
This study aimed to investigate the prevalence of vaginal colonization with antimicrobial-resistant (AMR) bacteria among women in labor in central Uganda. The justification for this study is based on the importance of understanding the prevalence of AMR bacteria in the female genital tract, as these bacteria can be transmitted to newborns during birth and cause difficult-to-treat neonatal infections. By obtaining updated information on the prevalence of colonization with important AMR pathogens, effective treatment strategies can be developed.
Study Highlights:
– The study found that a significant proportion of women in labor in central Uganda were colonized with potentially pathogenic and clinically important AMR bacteria.
– The prevalence of colonization with extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae was 3.9%, carbapenem-resistant Enterobacteriaceae was 1.8%, and methicillin-resistant Staphylococcus aureus (MRSA) was 5.8%.
– The prevalence of colonization with multidrug-resistant (MDR) bacteria, defined as bacteria resistant to antibiotics from ≥ 3 antibiotic classes, was high at 50.9%.
– Women who were ≥ 30 years of age had higher odds of being colonized with MDR bacteria compared to women aged 20-24 years.
Recommendations:
– The high prevalence of colonization with potentially pathogenic MDR and other clinically important AMR bacteria among women in labor highlights the need for interventions to prevent the transmission of these bacteria to newborns.
– Strengthening infection prevention and control measures in healthcare facilities, particularly during labor and delivery, is crucial to reduce the incidence of difficult-to-treat neonatal sepsis.
– Antimicrobial stewardship programs should be implemented to promote appropriate and judicious use of antibiotics, both in the community and healthcare settings.
– Further research is needed to explore the factors contributing to the high prevalence of AMR bacteria colonization and to develop targeted interventions to reduce transmission.
Key Role Players:
– Healthcare providers: Obstetricians, midwives, nurses, and other healthcare professionals involved in labor and delivery care.
– Laboratory personnel: Microbiologists, technicians, and researchers responsible for processing and analyzing bacterial isolates.
– Policy makers: Government officials, public health authorities, and policymakers responsible for developing and implementing strategies to address antimicrobial resistance.
– Community leaders and advocates: Individuals and organizations involved in raising awareness about antimicrobial resistance and promoting behavior change in the community.
Cost Items for Planning Recommendations:
– Training and capacity building: Budget for training healthcare providers on infection prevention and control measures, antimicrobial stewardship, and appropriate antibiotic use.
– Equipment and supplies: Budget for necessary equipment and supplies for implementing infection prevention and control measures, such as personal protective equipment, disinfectants, and sterilization equipment.
– Surveillance and monitoring: Budget for establishing or strengthening surveillance systems to monitor the prevalence of AMR bacteria and track resistance patterns over time.
– Public awareness campaigns: Budget for developing and implementing public awareness campaigns to educate the community about antimicrobial resistance and promote responsible antibiotic use.
– Research and development: Budget for conducting further research to explore the factors contributing to AMR bacteria colonization and to develop targeted interventions.
– Policy implementation and enforcement: Budget for supporting the implementation and enforcement of policies and guidelines related to infection prevention and control and antimicrobial stewardship.
Please note that the provided cost items are general suggestions and may vary depending on the specific context and resources available.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides detailed information about the study design, methods, and results. However, it lacks information about the statistical analysis and the limitations of the study. To improve the evidence, the abstract could include a brief description of the statistical analysis performed and any potential limitations of the study, such as sample size limitations or potential biases.

Background: According to WHO (CISMAC. Centre for Intervention Science in Maternal and Child health), the antimicrobial resistant bacteria considered to be clinically most important for human health and earmarked for surveillance include extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae, carbapenem-resistant bacteria, methicillin-resistant (MRSA) and, macrolide-lincosamide-streptogramin B -resistant vancomycin-resistant (VRSA) Staphylococcus aureus and vancomycin-resistant Enterococcus (VRE). If these bacteria are carried in the female genital tract, they may be transmitted to the neonate causing local or systemic neonatal infections that can be difficult to treat with conventionally available antimicrobials. In order to develop effective treatment strategies, there is need for updated information about the prevalence of colonization with important antimicrobial-resistant pathogens. Objective: We sought to estimate the prevalence of vaginal colonization with potentially pathogenic and clinically important AMR bacteria among women in labour in Uganda and to identify factors associated with colonization. Methods: We conducted a cross-sectional study among HIV-1 and HIV-2 negative women in labour at three primary health care facilities in Uganda. Drug susceptibility testing was done using the disk diffusion method on bacterial isolates cultured from vaginal swabs. We calculated the prevalence of colonization with potentially pathogenic and clinically important AMR bacteria, in addition to multidrug-resistant (MDR) bacteria, defined as bacteria resistant to antibiotics from ≥ 3 antibiotic classes. Results: We found that 57 of the 1472 enrolled women (3.9% prevalence; 95% Confidence interval [CI] 3.0%, 5.1%) were colonized with ESBL-producing Enterobacteriaceace, 27 (1.8%; 95% CI 1.2%, 2.6%) were colonized with carbapenem-resistant Enterobacteriaceae, and 85 (5.8%; 95% CI 4.6%, 7.1%) were colonized with MRSA. The prevalence of colonization with MDR bacteria was high (750/1472; 50.9%; 95% CI 48.4%, 53.5%). Women who were ≥ 30 years of age had higher odds of being colonized with MDR bacteria compared to women aged 20–24 years (OR 1.6; 95% CI 1.1, 2.2). Conclusion: Most of the women included in our study were vaginally colonized with potentially pathogenic MDR and other clinically important AMR bacteria. The high prevalence of colonization with these bacteria is likely to further increase the incidence of difficult-to-treat neonatal sepsis.

We conducted a cross-sectional study between July 2016 and July 2018 at three primary health care facilities in and close to Kampala in central Uganda: Mukono General Hospital (formerly Mukono Health Centre IV), Kawaala Health Centre III, and Kitebi Health Centre III [15]. This study was nested within the Chlorhexidine Trial, which is a randomized controlled assessing whether a single application of 4% chlorhexidine solution on the umbilical cord stump immediately after birth reduces the risk of omphalitis and severe illness [16]. Of the 1658 women in labour who were screened for this study, we recruited 1472 who had already agreed to being enrolled in the above-mentioned Chlorhexidine Trial. The inclusion criteria for the trial were: mother was negative for HIV-1 and HIV-2 and gave birth on a weekday, the newborn weighed > 1.5 kgs, had no severe congenital anomalies, had no obvious signs of umbilical cord stump infection and had no severe illness on the day it was born. We enThe sample size was calculated for the trial but not for the present study. With this sample size we would obtain a very high (0.7% to 2.6%) absolute precision, i.e. the difference between the upper limit and the lower limit of the 95% confidence interval (CI) for prevalence estimates ranging from 2 to 50%. Midwives obtained oral consent to collect a specimen from women in labour. After birth, a study nurse confirmed the verbal consent by obtaining written consent. In the subsequent interview, study nurses collected socio-demographic and clinical information from study participants using Open Data Kit-based standardized questionnaires [17]. Trained midwives collected the vaginal swabs during labour. A Regular Rayon sterile swab (Copan Diagnostics Inc., Murrieta, CA) was carefully inserted halfway between the introitus and cervix, avoiding contamination from the cervical mucus. The swab was then gently pressed against the vaginal wall, rotated to collect the specimen, and then removed, carefully avoiding contact with other parts of the body. The swabs were immediately stored in Amies Agar Gel without Charcoal transport medium (Copan Diagnostics Inc.) and transported daily in a cold box holding a temperature of 10–25 °C to MBN Clinical Laboratories Ltd in Kampala, which is a private research and diagnostic laboratory currently undergoing accreditation, where the swabs were immediately processed. We did not culture the specimens anaerobically because of the added cost and effort and because anaerobic bacteremia is uncommon in neonates [2]. The specimens were streaked onto blood agar containing 5% in-house produced sheep blood and onto MacConkey agar (both Biolab Inc., Budapest, Hungary) and incubated aerobically at 35–37 °C for 18–24 h for isolation of single colonies. The blood agar plates were further incubated for a total of 72 h to enable isolation of slow-growing colonies. From each of the two plates, one representative of each morphologically distinct colony was picked and streaked onto new plates and 1–5 resulting colonies from each of them were pooled in saline solution and subjected to further species determination and classification as described below, before being stored at −80 °C in Brain Heart Infusion broth with 20% glycerol. Identification of bacterial species was mainly done based on colony morphology, Gram staining and on standard biochemical tests. S. aureus was identified with the catalase, slide coagulase, mannitol fermentation, and DNase tests. The bile esculin test was performed to identify Enterococcus spp. Putative streptococcal isolates were grouped into different Lancefield groups with the Streptococcal Grouping Kit (Oxoid Ltd., Basingstoke, Hants, UK). Lactose and non-lactose fermenting colonies of gram-negative bacilli were identified based on morphology on MacConkey agar, and the isolates were characterized on the species level by performing standard biochemical tests such as Sulphide Indole Motility (SIM test), gas production, citrate test, urease test and oxidase test [18]. If two isolates from the same specimen were of the same species but had different biochemical characteristics, we included both isolates in the analyses. We considered gram-negative isolates representing E. coli, K. pneumoniae, Citrobacter spp., Enterobacter spp., Acinetobacter spp., K. oxytoca, Pseudomonas spp., and Proteus spp. and gram-positive isolates representing S. aureus, Enterococcus spp., Group A Streptococcus, and Group B Streptococcus to be potentially pathogenic bacteria and they were thereby included in the present study. Antimicrobial drug susceptibility testing of the bacterial isolates was performed using the disk diffusion method as described in the 2017 Performance Standards published by the Clinical Laboratory Standard Institute (CLSI) [19]. We also tested for the antibiotics recommended by the same standard. For gram-positive isolates, we tested against the following antibiotic resistance discs purchased from Biolab Inc.: penicillin (10 µg), trimethoprim-sulfamethoxazole (1.25/23.75 µg), chloramphenicol (30 µg), tetracycline (30 µg), ciprofloxacin (5 µg), gentamicin (10 µg), erythromycin (15 µg), oxacillin (1 µg), vancomycin (30 µg), ceftriaxone (30 µg), and linezolid (30 µg). For Gram-negative isolates, we tested against the following discs: trimethoprim-sulfamethoxazole (1.25/23.75 µg), ciprofloxacin (5 µg), chloramphenicol (30 µg), gentamicin (10 µg), amikacin (10 µg), ampicillin (10 µg), amoxicillin-clavulanic acid (20/10 µg), ceftriaxone (30 µg), cefuroxime (30 µg), ceftazidime (30 µg), tetracycline (30 µg), piperacillin (100 µg), piperacillin-tazobactam (100/10 µg), colistin (10 µg), and imipenem (10 µg). The inhibition zone diameters were measured after incubation at 35–37 °C for 24 h, and we considered an isolate to be resistant (i.e. non-susceptible) if the measurements indicated resistance or intermediate resistance to the given drug. To identify ESBL-producing Enterobacteriaceae, we used the combination disk method [20] where a combination disk containing 30 µg ceftazidime and 10 µg clavulanic acid was placed 15 mm from a 30 µg ceftazidime disk on a Mueller–Hinton agar plate. Isolates that had clear zones that were ≥ 5.0 mm larger around the combination disk than around the ceftazidime disk were considered to represent ESBL-producing bacteria. We considered isolates that were resistant to imipenem to be carbapenem-resistant based on CLSI guidelines. To identify methicillin-resistant S. aureus (MRSA) genotypically, we performed multiplex PCR-based identification of MRSA of most S. aureus isolates, as described by McClure et al. [21]. In this assay, the presence of the mecA methicillin resistance gene was used to identify MRSA, while the presence of the gene for the Panton-Valentine Leukocidin (PVL) virulence factor was a marker for community-acquired MRSA [22]. The completed reaction was separated on a 2% agarose gel stained with ethidium bromide, and the amplicons were visualized by using a UV trans-illuminator. To identify S. aureus isolates that had the macrolide-lincosamide-streptogramin B (MLSB) resistance phenotype, we performed the D-test [23]. In this test, disks with 15 µg erythromycin and with 2 µg clindamycin were placed 15 mm apart. If the isolate was resistant to both erythromycin and clindamycin, the isolate was considered to have a constitutive MLSB resistance phenotype (cMLSB), while if it was resistant to erythromycin and susceptible to clindamycin, but there was a D-shaped inhibition zone around the clindamycin disk, we considered the isolate to have an inducible MLSB resistance phenotype (iMLSB). We considered Enterococcus spp. and S. aureus isolates that are resistant to vancomycin to represent VRE and VRSA, respectively. We used the definition proposed by Magiorakos et al. [9], i.e. that isolates non-susceptible to ≥ 1 antibiotic in ≥ 3 of the antibiotic classes were considered MDR. The antibiotic selection was based on the 2017 Performance Standards from CLSI [19], which differs slightly from other commonly used standards, such as those published by EUCAST [24]. The antibiotic classes and antibiotics (given in parentheses) used for the MDR definition included penicillins (ampicillin, piperacillin, penicillin), penicillins and beta-lactamase inhibitors (amoxicillin-clavulanic acid), antipseudomonal penicillins and beta-lactamase inhibitors (piperacillin-tazobactam), non-extended-spectrum beta-lactams such as second generation cephalosporins (cefuroxime), extended spectrum beta lactams such as third generation cephalosporins (ceftriaxone, ceftazidime), carbapenems (imipenem), fluoroquinolones (ciprofloxacin), phenicols (chloramphenicol), folate pathway inhibitors (Trimethoprim-sulfamethoxazole), aminoglycoside (gentamicin, amikacin), anti-staphylococcal beta lactams (oxacillin), glycopeptides (vancomycin), macrolides (erythromycin), tetracyclines (tetracycline), and oxazolidinones (linezolid). As seen in Tables ​Tables11 and ​and2,2, we did not test for resistance for a given antibiotic if the species is known to be naturally resistant to the antibiotic. Vaginal colonization with antimicrobial drug-resistant potentially pathogenic gram-negative bacteria among study women in labor aNA indicates that the antibiotic was not tested or was not relevant for the given organism bMDR excluding ESBL-producing and carbapenem-resistant bacteria cThe two numbers in parentheses indicate number of colonized women and the number of isolates of each given species, respectively Vaginal colonization with antimicrobial drug-resistant potentially pathogenic gram-positive bacteria among study women in labor aNA indicates that the information is not relevant for the given resistance pattern bMDR excluding MRSA, VRSA, VRE, iMLSB- and cMLSB-resistant S. aureus cThe two numbers in parentheses indicate number of colonized women and the number of isolates of each given species, respectively To identify potential risk factors for colonization with different AMR bacteria in the logistic regression models described below, we included the following exposure information, which were acquired during interviews with the mothers after they had given birth. PROM defined as rupture of membranes before the start of labour [25], parity, maternal level of education, maternal age, hospitalization during pregnancy, antenatal care attendance, ownership of domestic animals at home and socioeconomic status. As a measure of socioeconomic status, we used principal component analysis on an asset index that we generated by evaluating the woman’s access to or ownership of cupboards, radios, televisions, a mobile phone, refrigerator, motorcycle, car, ownership of a house, and presence of cemented walls, flushing toilet, and having three or more rooms in the house. Socioeconomic status was divided into 5 levels, where the poorest women were categorized as belonging to the 1st quintile while the richest were categorized as belonging in the 5th quintile. The statistical analyses were done using Stata version 15.0 (StataCorp, College Station, Texas, USA). We obtained the overall prevalence of MDR colonization by dividing the number of women colonized with MDR bacteria by the total number of women enrolled into the study. To obtain the overall prevalence of resistance with clinically important bacteria such as MRSA, MLSB-resistant S. aureus, VRSA, VRE, ESBL and carbapenem-resistant bacteria, we divided the number of women colonized with such bacteria by the total number of enrolled women in the study. All proportions were reported with their respective 95% confidence intervals, which were calculated using the exact method. We performed multivariable logistic regression analyses to explore the association between selected exposures (maternal age, maternal education, socioeconomic status, gravidity, number of antenatal visits, hospitalization during pregnancy, ownership of domestic animals) and our primary outcome of vaginal colonization with MDR bacteria and secondary outcomes including ESBL and MRSA bacteria. We chose to conduct exploratory multivariable analyses because the exposures selected potentially confounded one another. We used the estat vif command in STATA to test the models for potential multicollinearity between the independent variables, as indicated by one or more variance inflation factor estimates being > 10. None of our models appeared to have potential multicollinearity issues.

Based on the provided information, here are some potential innovations that could improve access to maternal health:

1. Development of rapid diagnostic tests: Creating rapid diagnostic tests that can quickly identify antimicrobial-resistant bacteria in the female genital tract would enable healthcare providers to promptly initiate appropriate treatment and prevent the transmission of these bacteria to neonates.

2. Implementation of antimicrobial stewardship programs: Antimicrobial stewardship programs can help optimize the use of antibiotics in maternal health settings. These programs involve monitoring antibiotic prescribing practices, providing education to healthcare providers, and implementing guidelines to ensure appropriate antibiotic use, which can help reduce the prevalence of antimicrobial-resistant bacteria.

3. Strengthening infection prevention and control measures: Enhancing infection prevention and control measures in healthcare facilities, such as proper hand hygiene, sterilization of equipment, and adherence to standard precautions, can help prevent the spread of antimicrobial-resistant bacteria among women in labor.

4. Promoting maternal education and awareness: Educating pregnant women about the risks of antimicrobial-resistant bacteria and the importance of seeking timely prenatal care can help improve access to maternal health services and reduce the transmission of these bacteria.

5. Collaboration and surveillance: Establishing collaborations between healthcare facilities, researchers, and public health agencies to share data and conduct surveillance on the prevalence and trends of antimicrobial-resistant bacteria in maternal health settings can help inform targeted interventions and improve overall maternal health outcomes.

It is important to note that these recommendations are based on the information provided and may need to be further evaluated and tailored to the specific context and resources available in Uganda.
AI Innovations Description
Based on the provided description, the recommendation to improve access to maternal health and address the issue of vaginal colonization with antimicrobial-resistant bacteria among women in labor in central Uganda is as follows:

1. Strengthen Antimicrobial Stewardship Programs: Implement comprehensive antimicrobial stewardship programs in healthcare facilities to promote appropriate and judicious use of antibiotics. This includes educating healthcare providers on proper prescribing practices, promoting adherence to treatment guidelines, and monitoring antibiotic use and resistance patterns.

2. Enhance Infection Prevention and Control Measures: Improve infection prevention and control practices in healthcare facilities, particularly during labor and delivery. This includes ensuring proper hand hygiene, sterilization of equipment, and adherence to standard precautions. Implementing protocols for screening and isolating women colonized with antimicrobial-resistant bacteria can help prevent transmission to neonates.

3. Increase Surveillance and Monitoring: Establish a robust surveillance system to monitor the prevalence and trends of antimicrobial-resistant bacteria among women in labor. This can help identify emerging resistance patterns, guide treatment strategies, and evaluate the effectiveness of interventions.

4. Promote Antenatal Care and Education: Strengthen antenatal care services to provide education and counseling on maternal health, including the risks of antimicrobial resistance. Encourage pregnant women to attend regular antenatal visits, promote healthy behaviors, and provide information on the importance of completing prescribed antibiotic courses.

5. Improve Socioeconomic Conditions: Address socioeconomic factors that contribute to the spread of antimicrobial-resistant bacteria, such as poverty and lack of access to clean water and sanitation. Implement interventions to improve living conditions, access to healthcare, and socioeconomic status, which can indirectly impact maternal health outcomes.

6. Foster Collaboration and Partnerships: Encourage collaboration between healthcare providers, researchers, policymakers, and community stakeholders to develop and implement innovative strategies to address antimicrobial resistance in maternal health. This includes sharing best practices, conducting research, and advocating for policy changes to support effective interventions.

By implementing these recommendations, it is possible to improve access to maternal health and reduce the prevalence of antimicrobial-resistant bacteria among women in labor in central Uganda, ultimately leading to better maternal and neonatal outcomes.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Strengthening Antimicrobial Stewardship Programs: Implementing comprehensive antimicrobial stewardship programs in healthcare facilities can help optimize the use of antibiotics, reduce the emergence of antimicrobial resistance, and improve patient outcomes. These programs should include guidelines for appropriate antibiotic use in maternal health, regular monitoring of antibiotic prescribing practices, and education for healthcare providers on the importance of responsible antibiotic use.

2. Enhancing Infection Prevention and Control Measures: Improving infection prevention and control practices in healthcare facilities can help reduce the transmission of antimicrobial-resistant bacteria. This can include measures such as proper hand hygiene, appropriate use of personal protective equipment, proper cleaning and disinfection of equipment and surfaces, and adherence to standard precautions during labor and delivery.

3. Increasing Access to Antenatal Care: Ensuring that pregnant women have access to regular antenatal care can help identify and manage potential risk factors for maternal infections. Antenatal care visits provide an opportunity for healthcare providers to screen for infections, provide appropriate treatment, and educate women on preventive measures.

4. Strengthening Laboratory Capacity: Investing in laboratory infrastructure and capacity can improve the timely and accurate diagnosis of antimicrobial-resistant infections. This can help guide appropriate treatment decisions and facilitate surveillance efforts to monitor the prevalence and trends of antimicrobial resistance in maternal health.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the study population: Identify the target population for the simulation, such as pregnant women in a specific geographic area or healthcare facility.

2. Collect baseline data: Gather data on the current access to maternal health services, prevalence of antimicrobial-resistant infections, and existing practices related to antimicrobial use and infection prevention and control.

3. Develop a simulation model: Create a mathematical or computational model that represents the dynamics of maternal health access, antimicrobial resistance, and the impact of the recommended interventions. The model should incorporate relevant variables, such as population size, healthcare facility capacity, antibiotic prescribing patterns, and infection transmission dynamics.

4. Parameterize the model: Assign values to the parameters in the simulation model based on available data and expert knowledge. This may involve estimating the effectiveness of the recommended interventions, such as the reduction in antimicrobial-resistant infections achieved through improved antimicrobial stewardship or infection prevention and control measures.

5. Run the simulation: Use the parameterized model to simulate the impact of the recommended interventions over a specified time period. This can involve running multiple iterations of the simulation to account for uncertainty and variability in the input parameters.

6. Analyze the results: Evaluate the outcomes of the simulation, such as changes in the prevalence of antimicrobial-resistant infections, improvements in access to maternal health services, and potential cost-effectiveness of the interventions. Compare the results to the baseline data to assess the potential impact of the recommendations.

7. Interpret and communicate the findings: Interpret the simulation results and communicate the potential benefits and limitations of the recommended interventions to relevant stakeholders, such as policymakers, healthcare providers, and community members. This can help inform decision-making and guide the implementation of strategies to improve access to maternal health.

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