F1000ResearchF1000Research2046-1402F1000 Research LimitedLondon, UK10.12688/f1000research.17744.1Research ArticleArticlesAntimicrobial resistance surveillance among gram-negative bacterial isolates from patients in hospitals in Khartoum State, Sudan
[version 1; peer review: 3 approved with reservations]
ElbadawiHana Salaheldin Data CurationFormal AnalysisMethodologyWriting – Original Draft PreparationWriting – Review & Editinghttps://orcid.org/0000-0003-2192-7932a12ElhagKamal Mustafa InvestigationMethodologyWriting – Review & Editing13MahgoubElsheikhConceptualizationMethodologyWriting – Review & Editing4AltaybHisham N.Formal AnalysisVisualizationWriting – Review & Editing5Abdel HamidMuzamil Mahdi ConceptualizationSupervisionWriting – Review & Editinghttps://orcid.org/0000-0002-6157-43882
Soba University Hospital, University of Khartoum, Khartoum, Sudan
Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan
Ahfad University for Women, Omdurman, Sudan
Department of Microbiology, Faculty of Medicine,, University of Khartoum, Khartoum, Sudan
Department of Microbiology, Faculty of Medical Laboratory Sciences,, Sudan for Sciences and Technology, Khartoum, Sudanhanasalah200@gmail.com
Background: Antimicrobial resistance (AMR) among gram-negative bacilli is a global health problem. Surveillance of AMR is required to advise on empirical antimicrobial therapy. This study aimed at evaluating the frequency and the AMR patterns of gram-negative isolates from patients treated in eight hospitals in Khartoum State, Sudan.
Methods: A cross-sectional laboratory-based study was conducted over a 6 months period at the Microbiology Department, Soba University Hospital- Khartoum State, Sudan. All gram-negative isolates from blood, urine, wound, and sputum during the period of study were included. Identification and antimicrobial susceptibility testing were carried out for all isolates.
Results: A total of 734 Gram-negative bacilli were isolated.
Klebsiella pneumoniae (249 isolates, 34%) was the most frequently encountered one, followed by
Pseudomonas aeruginosa (153 isolates, 21%),
E.coli (123 isolates, 17%),
Acinetobacter baumannii (75 isolates, 10%),
Burkholderia cepacia (42 isolates, 6%),
Proteus mirabilis and
Proteus vulgaris (28 isolates, each, (4%)
Enterobacter colecaes (28 isolates, 4%),
Stenotrophomonas maltophilia (21 isolates, 2.8%), and other gram-negative bacilli (15 isolates, 2.2%) The analysis of the antimicrobial susceptibility patterns showed that 134 (22.3%) isolates were resistant to three or more classes of antibiotics, including cephalosporins, β-lactam–β-lactamase inhibitor, quinolones, aminoglycosides and carbapenems.
Conclusion: This high level of resistance among gram-negative bacilli in Khartoum state hospitals is alarming. The local health authorities should be prompted to step up infection control programs and introduce the concept of antimicrobial stewardship in Khartoum State hospitals.
Gram-negative bacilliMultidrug resistant bacterialaboratory-based studySurveillance.Ministry of Higher Education and Scientific ResearchSUD/MOH/MMAH/08/2016This research received partial research fund from the Ministry of Higher Education and Scientific Research, Sudan (grant number SUD/MOH/MMAH/08/2016).The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Introduction
Antimicrobial resistance (AMR) constitutes a continuously growing threat to the effective treatment of microbial infections
1. However, the direct impact of AMR on the health of hospitalized patients or the people in the community, as well as the financial burden experienced by health care systems in managing the infections and complications due to AMR, are still mostly uncertain
2. Antibacterial drugs are widely used worldwide both in human health and food industry. Overuse of these medications can favor the selection and the spread of multidrug resistant (MDR) bacteria
1. Multi drug resistance is defined as resistance to at least three different antibiotic groups, as reported by Masgala and Kostaki
3. Antibiotic resistance among a variety of bacterial species is increasing in healthcare and community setting. Extended-spectrum β-lactamase and carbapenemase production are the most frequently emerging resistance mechanisms among gram-negative bacilli
4. Gram-negative bacilli including Enterobacteriaceae and non-lactose fermenting bacteria such as
Pseudomonas spp. and
Acinetobacter spp. are the main causes of hospital-acquired infection in critical care units
2,
5. The antibiotic resistance rates among these organisms have amplified uncontrollably in a matter of a few years to become worldwide
2. According to the Centre for Disease Control and Prevention, gram-negative bacilli are able to develop antibiotic resistance through multiple methods and are particularly competent at spreading the resistance among species via horizontal gene transfer
6. The enigma of AMR is particularly plaguing low- and middle-income countries, where infectious diseases are the commonest cause of hospitalization and death; and the newer antibiotics cannot be afforded
7.
AMR surveillance is key for determining the prevalence patterns of AMR, which is fundamental for the development of national and international treatment strategies. Most of the available surveillance data are derived from developed countries; the studies conducted in developing countries are unfortunately not adequate.
This surveillance study was undertaken in order to find out the different types of the AMR patterns of bacterial pathogens isolated from patients in Khartoum State, Sudan. This study may help in formulating antibiotic policies tailored to our hospitals. These data can be used as “information for action” antibiotic stewardship and interventions to optimize antibiotic prescribing practice, therefore prolongs the usefulness of existing antibiotics.
MethodsStudy design and clinical strains
This is a cross-sectional laboratory based study carried out in the department of medical microbiology Soba University Hospital (SUH) and Institute of Endemic Diseases, University of Khartoum, Sudan. A total of 734 Gram-negative bacteria were isolated from patients treated in eight hospitals in Khartoum state including: two university hospitals (Soba university hospital and Bashaier); three teaching hospitals (Ibrahim Malik, Bahri and Sadabulalla) , a specialized hospital (Elfouad), and two private hospitals (Imperial and Elswedy). This study included all clinical specimens received in Soba University hospital microbiology laboratory in a period from October 2016 to February 2017 from various wards in the aforementioned hospitals including: intensive care units (ICUs), neonatal ICUs, medicine units, surgery units, pediatric units, and renal units. The isolates were collected from different clinical specimens including: blood (243 isolates, 33.1%), urine (230 isolates, 31.3%), wounds (183 isolates, 25%), sputum (22 isolates, 3%), catheter tips (26 isolates, 3.4%) and body fluids (including cerebrospinal, peritoneal, pleural, acetic and synovial fluid; 30 isolates 4.2%). Microorganisms were grown on Blood, Chocolate and MacConkey agar. Then, they were identified according to standard microbiological procedures (based on colony morphology, microscopy, and biochemical tests)
8. Quality control strains were used in biochemical tests and antimicrobial susceptibility testing [
E.
coli (ATCC #25922) and
P. aeruginosa (ATCC #27853)].
Most gram-negative Bacilli isolates were further identified and confirmed by PCR. Guanidine chloride method, as described by Alsadig
et al.9, was used for DNA extraction followed by PCR which it was carried out using thermal cycler (analytikjena® Biometra TADVANCED, Germany), by using the following primers (Macrogen, Korea), using species-specific primers for
Klebsiella pneumoniae,
Escherichia coli,
Pseudomonas aeruginosa,
Acinetobacter baumannii and Universal 16S rRNA primers (
Table 1) the reaction was carried out in a total reaction volume of 25 μl (5μl Master mix of Maxime RT premix kit (iNtRON Biotechnology, Seongnam, Korea), 0.6 μl of forward primer, 0.6 μl of reverse primer, 2μl of DNA and 16.8 μl deionized sterile water). The cycle condition as the following: initial denaturation step at 94°C for 5-min, followed by 30 cycles of denaturation at 94°C for 45 seconds, primer annealing temperature according to the primers
Table 1 for 45 seconds, followed by step of elongation at 72°C for 60 seconds and the final elongation at 72°C for 5 min
10. The purity and integrity of each PCR product was evaluated electrophoresis in a 2% agarose gel in TBE 1X, that contain 2.5 μl of (20mg/ml) ethidium bromide at 100V for 40 min. The specific amplified product were detected by comparing with 100 base-pairs standard DNA ladder (iNtRON BIOTECHNOLOGY, Seongnam, Korea) Bands were visualized under U.V transilluminater (analytikjena® Biometra BDAcompact, Germany). The PCR product of 16SrRNA were purified and Sanger sequencing was performed by Macrogen Company (Seoul, Korea). Then nucleotides sequences of the genes 16SrRNA achieved were searched for sequence similarity using
nucleotide BLAST for species identification
11.
Bacterial gene primers used for PCR.
Species specific
primers
Primer (5' to 3')
Tm (°C)
Band
size (bp)
Ref
Universal 16S rRNA
F=AGAGTTTGATCCTGGCTCAG
58
890
10
R=CTACGGCTACCTTGTTACGA
58
K. pneumoniae
Pf = ATTTGAAGAGGTTGCAAACGAT
56
13
Pr1=TTCACTCTGAAGTTTTCTTGTGTTC
56
130
Pr2 = CCG AAG ATG TTT CAC TTC TGA TT
56
260
E.coli
ECA75F=GGAAGAAGCTTGCTTCTTTGCTGAC
52
544
14
ECR619R=AGCCCGGGGATTTCACATCTGACTTA
52
Pseudomonas spp.
F= GGGGGATCTTCGGACCTCA
58
956
15
R=TCCTTAGAGTGCCCACCCG
58
Acinetobacter
sp4F CACGCCGTAAGAGTGCATTA
58
294
16
sp4R AACGGAGCTTGTCAGGGTTA
58
A. baumannii
13TU,sp2FGTTCCTGATCCGAAATTCTCG
58
490
Antimicrobial susceptibility testing
Susceptibility testing was performed using the Kirby-Bauer disc-diffusion method; each isolate was swabbed on the Muller-Hinton agar and the antibiotic discs were placed on top and incubated at 37°C for 18–24 hours
12. all isolates were tested against the following antibiotic disc (Mast Diagnostic): amoxycillin clavulanate (AMC) (30 μg), cefuroxime (CXM) (30 μg), cephalexin (CL) (30 μg), ceftriaxone (CRO) (30 μg), ceftazidime (CAZ) (30 μg), meropenem (MEM) (10 μg), imipenem (IPM) (10 μg), amikacin (AK) (30 μg), gentamicin (Gen) (10 μg), ciprofloxacin (CIP) (5 μg), trimethoprim-sulfamethoxazole (SXT) (25 μg), temocillin (TEM) (30 μg), azteroname (AZT) (30 μg) and nitrofrantoine (NIT) (300 μg). Results were interpreted according to the Clinical Laboratory Standards Institute (CLSI) guidelines
12.
Classification of MDR gram-negative Bacilli
MDR has been considered for clinically significant gram-negative Bacilli such as
E. coli,
K. pneumoniae,
P. aeruginosa, and
A. baumannii based on the aforementioned antimicrobial resistance definition. Classes of antibiotics used for MDR-GNB analysis were aminoglycoside (AMG), cephalosporins (CEPH), carbapenems (CARB), and fluroquinolones (FQ) as follows: bacteria that were MDR for four classes of antibiotics (AMG+ CEPH+ CARB+ FQ) and bacteria that were MDR for three classes of antibiotics (either AMG+CEPH +FQ, CARB+CEPH+FQ, AMG+CEPH+CARB, or AMG+FQ+CARB)
3.
Cephalosporin resistance was defined as resistance to ceftriaxone and ceftazidime, except for
P. aeruginosa, where only ceftazidime was used. Carbapenem resistance was defined as resistance to both meropenem and imipenem. Aminoglycoside resistance was defined as resistance to both gentamicin and amikacin, Ciprofloxacin resistance was considered an indication to fluoroquinolones resistance.
Ethical consideration
Formal permission was obtained from the managers of Soba University Hospital and the Institutional Research Ethics Committee of the Institute of Endemic Diseases, University of Khartoum, approved this study under reference number IEND_REC 12/2017. Patient consent was waived by the Research Ethics Committee.
Statistical analysis
Data were analysed using Microsoft Excel and SPSS version 20.0. Cross-tabulation was used to present the different relations between data, qualitative data were performed using a χ
2 test (significance was set at
p≤0.05), which was performed to find the differences between bacterial isolates with resistance to at least one class of antibiotics by specimens (blood, urine, wound and other samples)
p-values were determined for primary and secondary outcomes.
ResultsBacterial identification
Isolated Gram-negative bacilli showed different strains, including
E. coli (123 isolates, 17%),
K. pneumoniae (249 isolates,34%),
P. aeruginosa (153 isolates, 21%
),
A. baumannii (75 isolates, 10%),
Burkholderia cepacia (42 isolates, 6%),
Proteus mirabilis and
Proteus vulgaris (28 isolates, 4%),
Enterobacter colecaes (28 isolates, 4%),
Stenotrophomonas maltophilia (21 isolates, 2.8%) and other gram-negative bacilli (15 isolates, 2.2%).
While isolates were distributed among the different hospital units, most of the pathogenic strains were isolated from neonatal intensive care unit (ICU) (182 isolates, 24.8%) mainly
K. pneumoniae (77 isolate, 42.3%) and pediatric units (175 isolates 23.8%) the most prevalent strains were
K. pneumoniae (50 isolate, 29%) and
P. aeruginosa (44 isolates, 25.1), while medicine (147 isolates, 20%),
K. pneumoniae and
E.coli (45 isolates 30.6%) for both. For the surgery unit (103 isolates, 14%) renal unit (78 isolates, 10.7%) and ICU (49 isolates, 6.7%) mainly
K. pneumoniae (19 isolates, 39%),
P. aeruginosa and
A. baumannii were (9 isolates, 20.4) for both.
Klebsiella pneumoniae was the most isolated organism from all hospital units. The distribution of different gram-negative isolates is shown in
Table 2.
The incidence of gram-negative Bacilli isolated from patients admitted to different hospital wards in Khartoum State between October 2016 and February 2017.
Bacteria
Hospital ward
P-value
ICU,
n (%)
NICU,
n (%)
Medicine,
n (%)
Surgery,
n (%)
Renal
unit, n (%)
Paediatric,
n (%)
Klebsiella pneumoniae (249)
19 (39)
77 (42.3)
45 (30.6)
34 (33)
24 (31)
50 (29)
<0.001
Escherichia coli (123)
4(8.1)
9 (5)
45 (30.6)
22 (21.3)
16 (21)
25 (14.2)
<0.001
Pseudomonas
aeruginosa (153)
10 (20.4)
40 (21.9)
24 (16.3)
17 (16.5)
19 (24.3)
44 (25.1)
<0.001
Acinetobacter baumannii (75)
10 (20.4)
18 (9.9)
9 (6.1)
8 (8)
7 (9)
24 (14)
<0.001
Burkholderia cepacia (42)
3 (6.1)
11 (6)
7 (4.7)
6 (6)
4 (5.1)
11 (6.3)
<0.001
Proteus spp
. (28)
1 (2)
3 (2)
4 (2.7)
9 (9)
3 (4)
8 (5)
<0.001
Enterobacer spp
. (28)
1 (2)
10 (5.5)
4 (3)
3 (3)
4 (5.1)
6 (3.4)
<0.001
Stenotrophomonas spp
. (21)
1 (2)
10 (5.5)
3 (2)
2 (2)
1 (1)
4 (2)
<0.001
Other gram-negative Bacilli (15)
0 (0)
4 (2.2)
6 (4)
2 (2)
0 (0)
3 (2)
<0.001
Total (734)
49 (6.7)
182 (24.8)
147 (20)
103 (14)
78 (10.7)
175 (23.8)
<0.001
*Other Gram-negative bacilli include
Citrobacter species,
Serratia species,
Vebrio vurneficus and
Morganella morganii. †Body fluids include cerebrospinal fluid, peritoneal fluid, pleural fluid, acetic fluid and synovial fluid.
With regard to the distribution of the isolates among different clinical specimens,
Klebsiella pneumoniae and
Pseudomonas aeruginosa were isolated mainly in blood specimens 39% and 25% respectively, while
K. pneumoniae and
E.coli were 36% and 30% of urine samples.
A. baumannii was isolated from 14% of wound specimens and
P. aeruginosa was isolated from 23% of wound specimens. For more details about gram-negative bacilli among different specimen see
Table 3.
The frequency of gram-negative bacilli isolated from different clinical samples obtained from patients treated at Khartoum State hospitals between October 2016 and February 2017.
Bacteria
Specimen
P-value
Blood,
n (%)
Urine,
n (%)
Wounds,
n (%)
Sputum,
n (%)
Catheter
tips, n (%)
Bodily
fluids†, n (%)
Klebsiella pneumoniae (249)
94 (39)
82 (36)
50 (27)
7 (32)
7 (28)
9 (29)
<0.001
Escherichia coli (123)
15 (6.1)
70 (30)
31 (17)
2 (9)
1 (4)
4 (12.9)
<0.001
Pseudomonas aeruginosa (153)
60 (25)
32 (14)
42 (23)
6 (27.2)
7 (28)
6 (25)
<0.001
Acinetobacter baumannii (75)
18 (7.4)
13 (5.6)
25 (14)
6 (27.2)
7 (28)
6 (25)
<0.001
Burkholderia cepacia (42)
20 (8)
9 (4)
9 (5)
1 (5)
1 (4)
2 (6.4)
<0.001
Proteus spp
. (28)
6 (2.5)
7 (3)
12 (6.5)
0 (0)
2 (8)
1 (3.2)
<0.001
Enterobacer spp
. (28)
13 (5)
8 (3.5)
7 (4)
0 (0)
0 (0)
0 (0)
<0.001
Stenotrophomonas spp
. (21)
12 (5)
2 (0.9)
5 (3)
0 (0)
0 (0)
2 (6.4)
<0.001
Other gram-negative Bacilli
* (15)
5 (2)
7 (3)
2 (1)
0 (0)
1 (0)
0 (0)
<0.001
Total (734)
243 (33.1)
230 (31.3)
183 (25)
22 (3)
26 (3.4)
30 (4.2)
<0.001
*Other Gram-negative bacilli include
Citrobacter species,
Serratia species,
Vebrio vurneficus and
Morganella morganii.
Antimicrobial resistance pattern of clinical isolates
Antibiotic resistance pattern are shown in
Figure 1. Out of 734 isolates tested using the disk diffusion method, the highest percentage of resistance, in 97% and 93.5% of isolates, were found against ampicillin and cephalexin, respectively, followed by amoxicillin/clavulanic acid(90%), cefotaxime (89.7%), ceftriaxone (88.4%) and ceftazidime (79.2%). In addition, co-trimoxazole and nitrofurantoin resistance were detected in 74.4% and 75.2% of isolates, respectively. Resistance rates also were high in ciprofloxacin (45.2%), gentamicin (52.5%) and amikacin (18.3%). Meropenem and imipenem were the most effective antibiotic tested, with resistance observed in 21.6% and 16.2% of isolates, respectively.
Antimicrobial resistance pattern among different gram-negative Bacilli isolated from patients treated at Khartoum State hospitals between October 2016 and February 2017.
The antimicrobial resistance patterns of most commonly isolated organisms are shown in
Figure 2.
K. pneumoniae resistant pattern as the following (22%) of them were resistant to meropenem while (11%) were resistant to imipenem, ceftazidime (80.6%), Gentamicin (52%), ciprofloxacin (42%) and amikacin (16.7%). With regard to the
E. coli antimicrobial resistant pattern, meropenem (9%), imipenem (8%), ceftazidime (84.2%), ciprofloxacin (66.4%), Gentamicin (53.1%) and amikacin (12.0%). In
Pseudomonas aeruginosa the resistance rate was meropenem (20%), imipenem (22%) ceftazidime (81%) followed by gentamicin (57.5%), ciprofloxacin (22.5%) and amikacin (9.5%). The rate of antimicrobial resistant among
A. baumannii was as the following; meropenem (73.7%), imipenem (66.7%), amikacin (63.2%), gentamicin (79%) and ciprofloxacin (79%).
Antimicrobial resistance pattern of commonly isolated organisms’ different antibiotics between October 2016 and February 2017.
Multidrug resistance patterns among gram negative Bacilli
The gram-negative bacilli that were resistant to several antibiotic groups are shown in
Table 4. Of 600 GNB isolates, 134 (22.3%) isolates were MDR. Of those MDR organisms, 48 isolates (8%) were resistant to four classes of antimicrobial drugs:
A. baumannii (38 isolates, 50.6%),
K. pneumoniae (9 isolates, 3.6%), and
E. coli (1 isolate, 0.8%). A further 86 isolates (14.2%) were resistant to three classes of antimicrobial drugs:
A. baumannii (38 isolates, 50.6%),
K. pneumoniae (47 isolates, 18.8%),
P. aeruginosa (21 isolates, 13.7%) and
E. coli (6 isolate, 4.8%).
Multidrug resistance among gram-negative isolates.
Infection with MDR gram-negative Bacilli is a major problem worldwide, associated with increased patients morbidity and mortality
17. In Sudan, the increasing number of MDR bacteria is a real clinical challenge
18,
19. This study was undertaken; to identify the different patterns of AMR in bacterial pathogens isolated from patients treated in various wards of hospitals.
In this study,
K. pneumoniae and
P. aeruginosa strains were more prevalent in blood specimens while
K. pneumoniae and
E.coli strains were more frequently isolated in urine specimens.
K. pneumoniae is a prominent pathogen causing both hospital-acquired and community-associated infections, including bacteremia, wound infection, pneumonia, urinary tract infections and other infections
20,
21. In this study,
K. pneumoniae was the most commonly isolated organism from the blood specimens mainly in neonatal sepsis in a high rate (39.8%). Most of these strains resistant to cephalosporins and other class of antibiotics including carbapenem as reported worldwide
7,
21,
22.
E. coli is regarded as the commonest pathogen of the urinary tract, causing complicated and uncomplicated urinary tract infections
23. In this study, the most frequently observed pathogens in urine specimens were
E. coli (30%) and
K. pneumoniae (36%). This finding is in harmony with the results of several other studies, including: de Francesco
et al., who found that
E.coli was the commonest GNB (42.4%) isolate from urine specimens of patients with urinary tract infection
24; a study in Tanzania reported 38% of
E.coli isolated from urinary specimens
25 and other studies from Pakistan and India
25,
26.
In this study, non-lactose-fermenting gram-negative bacilli such as
P. aeruginosa and
A. baumannii were mostly encountered in ICU patients, these organisms were isolated in 20.4% of samples, and were found in different clinical samples such as: blood, wound and sputum. This finding agrees with a study by Vincent
et al. that reported
P. aeruginosa and
A. baumannii were frequently isolated from ICU patients by Vincent
et al.
27; Jitendra
et al., reported that
A. baumannii was the second most common pathogen in an ICU of a tertiary care center
28.
Concerning the infection type, we found that
P. aeruginosa were associated with 25% of blood stream infections and 23% of wound infection, while
A. baumannii mainly associated with wound infection in 14% in agree with Gales
et al. 2010
29.
Resistance of gram-negative bacilli is widespread and multidrug resistance has been reported in many studies
2,
4,
5, causing challenges in the treatment of nosocomial infections. The resistance pattern was commonly reported in classes such as cephalosporins, carbapenem, aminoglycosides and quinolones
30–
32. In this study, we observed high rates of resistance to extended-spectrum β-lactamases (ESBL), resistance to cephalexin, cefuroxime, ceftazidime and ceftriaxone, in addition to resistance to ampicillin and amoxicillin/clavulanic acid.
The analysis of the antimicrobial susceptibility patterns of the study isolates showed high rate of MDR organisms that were resistant to three or more classes of antibiotics, including carbapenem and aminoglycosides. This pattern was observed mainly among
Acinetobacter baumannii,
Pseudomonas aeruginosa and
Klebsiella pneumoniae.
The most resistant strain was
Acinetobacter baumannii, being resistant to all four classes of antibiotics used in 50.6% of isolates. A total of 73.7% of
A. baumannii were found to be resistant to meropenem, and 66.7% to imipenem, while in the cephalosporin class, more than 91% of the isolates were resistant.
A. baumannii also have high resistance rate to aminoglycosides and quinolones (63.2% for amikacin and 79% for both gentamicin and ciprofloxacin). This increasing resistance among
A. baumannii has become a public-health issue, because this bacterium frequently causes nosocomial infections
31.
In this study the most common clinical isolates of the Enterobacteriaceae family were
K. pneumonia and
E. coli. In both species, there was a high prevalence of resistance against quinolones, aminoglycosides and beta-lactams. Rates of resistance to carbapenems were alarmingly high: 22% in
K. pneumoniae and 9% in
E. coli. These bacteria have high resistance rate to ceftazidime and cephalexin, (80.6% and 92%, respectively). These rates are much higher than those observed in 2013 by Ali in Soba University hospital, who found that ceftriaxone and ceftazidime resistance rates ranged from 56% to 79%
21,
33. Aminoglycoside (specifically amikacin) resistance rates among
K. pneumoniae and
E. coli were 16.7% and 12.1%, respectively, which is higher than those observed by Lee in 2013, who found the resistance rate to amikacin was 6.2% in
K. pneumoniae and 1.3% in
E. coli30. In this study Gentamicin resistance among both
K. pneumoniae and
E. coli was 53%, which is a high resistance rate.
E. coli was highly resistant to quinolones like ciprofloxacin (in 66.4%), whereas
K. pneumoniae was resistant in 42% of isolates. This finding is much lower than that observed by Moolchandani
et al. in 2017
32.
Pseudomonas aeruginosa was resistant to carbapenem in 22% of isolates and was highly resistant to ceftazidime (in 81% of isolates) followed by gentamicin (57.5%), ciprofloxacin (22.5%) and amikacin (9.5%). resistance to many antibiotic among
P. aeruginosa was reported in many studies
4,
34.
The high level of resistance in the current study can be attributed to the unrestricted use of antibiotics in Sudanese hospitals; this injudicious use has been shown to have, an important role in increasing carbapenem resistance
32. During this study, 134 gram negative bacilli resistant to three or four classes of antibiotics were isolated over a period of six months, which is relatively higher rate than the rate reported in a previous study also conducted in SUH over 30 months, from January 2011 to June 2013
33. This concerning finding indicates the rapid acceleration in the rate of emergence of MDR organisms in our local sittings. Moreover, 80 bacterial strains were resistant to all available antibiotics, including meropenem.
In addition, microbiology laboratories play a crucial role against the spread of antimicrobial resistance by accurately identifying causative pathogens and detecting their antimicrobial susceptibility profile, so as to guide the proper use of antibiotics by the care providers. Unfortunately, in Sudan the lack of reliable microbiology laboratory services adds yet another layer to the multifactorial problem of MDR organisms’ epidemic in our country. Most of the laboratories in our country use the disk diffusion method for antimicrobial susceptibility testing; however, there are no policies regarding phenotypic screening for antibiotic resistance among certain organisms; resulting in that the laboratory report may not be accurate and misguide the doctors. For instance, in the disk diffusion method, if the inhibitory zone around ceftazidime was ≤22 mm, ideally this should trigger testing for the presence of ESBLs in the isolated pathogen, because the presence of these enzymes renders all penicillins, cephalosporins and monobactams
12 useless against that certain isolate, even if they shows susceptible results in the routine test. Yet, this extra step is not taken and only the routine susceptibility results will be reported, which may inaccurately show some antibiotics as susceptible while in reality the organism is resistant to them. Lastly, there is a limited choice of available antibiotics in Sudan; the most widely available are cephalosporins, which makes them the backbone of treating infectious diseases regardless of the isolate or its susceptibility profile. Carbapenems are believed to treat all evils, once they were reserved for the treatment of MDR organisms causing systemic infections
4, but the recent trend led to over use them for treating infections that can be managed by less potent antibiotics, contributing to this vicious cycle that aggravate the AMR issue even more.
Conclusion
In conclusion, there was a high prevalence of gram negative bacterial pathogen associated hospital and community acquired infections, with increasing rates of resistance to available antibiotics. Strict infection control measures should be implemented, and antimicrobial stewardship should be initiated and policed to decrease the spread of MDR pathogens in Sudanese hospitals.
Data availability
Raw data for the present study, including the genotypes, isolation location and resistance status of each bacterial isolate, is available of figshare. DOI:
https://doi.org/10.6084/m9.figshare.758444935.
Data are available under the terms of the
Creative Commons Attribution 4.0 International license (CC-BY 4.0).
Acknowledgments
We would like to thank the technical staff of Medical Microbiology Department in Soba University Hospital, University of Khartoum for their help in strain and data collection.
An earlier version of this article can be found on bioRxiv (DOI:
https://doi.org/10.1101/486274).
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Antimicrobial resistance surveillance among gram negative bacterial isolates from patients in hospitals in Khartoum State, Sudan .xlsx.figshare.Dataset.2019.
http://www.doi.org/10.6084/m9.figshare.7584449.v110.5256/f1000research.19402.r86820Reviewer response for version 1MelanoRoberto G1Referee
Public Health Ontario Laboratory, University of Toronto, Toronto, Ontario, Canada
Competing interests: No competing interests were disclosed.
In
Methods, I suggest this modification for the very long (and unclear) sentence:
"Guanidine chloride method, as described by Alsadig et al.
9, was used for DNA extraction followed by PCR. Species-specific primers (Macrogen, Korea) were used for identification of Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, Acinetobacter baumannii; universal 16S rRNA primers were also used for identification of other species (Table 1). Each amplification was carried out in a total reaction volume of 25 μl: 5μl Master mix of Maxime RT premix kit (iNtRON Biotechnology, Seongnam, Korea), 0.6 μl of forward primer, 0.6 μl of reverse primer, 2μl of DNA and 16.8 μl deionized sterile water). The cycle condition were the following…”.
In “Antimicrobial susceptibility testing” and Fig. 1, please check the spelling of some antibiotics (e.g. amoxicillin instead of amoxicillin, etc). In Fig. 1, ‘augmentin’ is a brand name. Please, use the generic name of the drug (amoxicillin clavulanate).
In “Classification of MDR gram-negative Bacilli”, the definitions of MDR are not in reference 3, as mentioned by the authors. Please, add the correct reference, Magiorakos
et al., (2012)
1.
In the sentence ‘Cephalosporin resistance was defined as resistance to ceftriaxone
and ceftazidime, …’, it is interesting to see that the authors did not use the optional "or" instead of "and", since resistance to these antibiotics (cephalosporins and carbapenems) can be consequence of the presence of different mechanisms. For example, Enterobacteriaceae can be resistant to ceftazidime due to the presence of ESBLs such as PER-2 or from the SHV-family, but susceptible to ceftriaxone. Same for carbapenems (e.g. deficiency of the outer membrane protein OprD confers
P. aeruginosa resistance to imipenem) and aminoglycosides (different aminoglycoside modifying enzymes can confer resistance to only gentamicin or amikacin). I suggest changing these criteria, and as consequence revise the number of isolates included in this study.
In
Results, “Bacterial identification”, I suggest changing ‘strain’ by ‘species’ in the sentence, “Isolated Gram-negative bacilli showed different strains, including…”.
The description in the second paragraph (‘While isolates were distributed…’) is not clear. I suggest deleting all this paragraph since Table 2 describes the same and in a very clear way. I just would keep the last 2 sentences ("
K. pneumoniae was the most isolated organism from all hospital units. The distribution of different gram-negative isolates is shown in Table 2"). Please, use the abbreviated form of the bacterial names after these were mentioned (i.e. first mention:
Klebsiella pneumoniae, after that,
K. pneumoniae; same for all the species included in this manuscript).
It is not clear the meaning of the p-values in the Tables 2 and 3. Please, clarify.
In “Antimicrobial resistance pattern of clinical isolates”, Fig. 1, I don’t think the authors can present accumulative results for bacterial groups that were not tested by the same antibiotics (as showed in Figure 2). I'd delete Figure 1 and the first paragraph of this section.
In “Multidrug resistance patterns among gram negative Bacilli”, why were only 600 isolates were analyzed? Why were the other 134 isolates not included in this analysis? I suggest adding a sentence explaining this issue. The % of MDR (22.3%) would be an underestimation considering my comment #4 about the criteria for defining MDR.
In
Discussion, in the paragraph starting in “Resistance of gram-negative bacilli is widespread and…”, the authors didn't study the mechanisms of resistance but the susceptibility of the isolates. Then they can't talk about high rates of ESBLs. Maybe they wanted to say "resistance to extended-spectrum cephalosporins" ("resistance to ESBLs” is wrong). If that is the case, the authors have to change the sentence. I suggest:
"In this study, we observed high rates of resistance to extended-spectrum cephalosporins (ceftazidime and ceftriaxone), in addition to resistance to cephalexin, cefuroxime, ampicillin and amoxicillin/clavulanic acid." If there are previous studies from Sudan, and/or close countries, about AMR, it would be interesting a paragraph comparing those results with the ones obtained in this manuscript. That would show the evolution of resistance in the country/region. Please, discuss some of these data in the manuscript.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
No source data required
Is the study design appropriate and is the work technically sound?
Yes
Are the conclusions drawn adequately supported by the results?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
Reviewer Expertise:
Antimicrobial resistance
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
References:
Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.Clin Microbiol Infect.2012;18(3) :
10.1111/j.1469-0691.2011.03570.x268-812179398810.1111/j.1469-0691.2011.03570.x10.5256/f1000research.19402.r86818Reviewer response for version 1RafeiRayane1Refereehttps://orcid.org/0000-0001-9633-1290
Laboratoire Microbiologie Santé et Environnement (LMSE), Doctoral School of Science & Technology, Faculty of Public Health, Lebanese University, Tripoli, Lebanon
Competing interests: No competing interests were disclosed.
This manuscript presents the surveillance data of antimicrobial resistance patterns of Gram-negative bacteria from patients in Khartoum State, Sudan. Such data are highly valuable from underrepresented regions. Nevertheless, this manuscript contains several flaws that must be addressed before acceptance.
Comments:
1. Is there a systematic collection of all Gram-negative bacteria isolated in the 8 hospitals mentioned in the materials and methods section? The authors should describe and clarify more their study design. The patients from whom bacteria were isolated are only inpatients admitted to hospitals or also including outpatients? These 8 hospitals are sole hospitals in the Khartoum state, are they representative of such state? It would be interesting to include more data on these hospitals.
2. The MDR definition adopted in the manuscript to categorize the strains as MDR is not well-referenced. Usually, an isolate could be considered resistant to a group of antibiotics if it is resistant to at least one (
≥1) antibiotic agent in the group, not necessarily to all agents in the group (as mentioned in the second paragraph of the Classification of MDR Gram negative Bacilli). I recommend the authors to revaluate their data based on a good definition as that described in the reference Magiorakos
et al. (2012)
1.
3. Reference 3 used for the definition of MDR in the introduction (and perhaps in the materials and methods) does not define such terms. Please verify that cited references matched well the text throughout the manuscript (as for reference 29 wherein the reference did not match the text).
4. Table 1, describing the bacterial gene primers used for PCR, must include a column for gene targets. In addition, it also contains many ambiguities to clarify:
The primers used for
Acinetobacter identification are wrongly mentioned. Indeed, the sp4F and sp4R can identify both
Acinetobacter genomic species 13TU (which is recently known as
Acinetobacter nosocomialis) and
A. baumannii. The primers sp2F and sp4R can identify
A. baumannii. A PCR with the 3 primers (sp2F, 4F, 4R) yields 2 bands when the isolate is
A.baumannii (one 294 bp with primer sp4F and sp4R and one 490 bp with sp2F and sp4R), and only one band (294 bp with sp4F and sp4R) when the isolate is
A. nosocomialis.
For the universal 16S rRNA, the reverse primer is not present in the mentioned reference (table 1).
Please, also use the bona fide name for primers as they are named in their original article (for example instead of F use the 27F (5’-AGAGTTTGATCCTGGCTCAG-3’)).
5. The statistical analysis paragraph should be reformulated. Moreover, what statistical relationships do the authors use to reveal by the mentioned P-values in tables 2 and 3?
6. Was the 16S rRNA gene sequencing carried out to all Gram-negative bacteria isolates, even those identified using PCR with species-specific primers?
7. Which cut-off has been used for the identification of species when blasting the 16S rDNA sequence, what is the NCBI database that has been used (nucleotide collection nr/nt or rRNA/ITS database)?
8. Please verify the charge of antibiotic disks as the charge of trimethoprim-sulfamethoxazole (SXT) should be 1.25/23.75 μg.
9. Why are the antibiotics ticarcillin, ticarcillin-clavulanate, piperacillin, piperacillin-tazobactam and cefepime not tested?
10. Why include only 600 GNB for studying the MDR, however, the authors start with 743 isolates. The reasons should be clearly stated in the text.
11. Why are the data on drug susceptibility about
Stenotrophomonas maltophilia and
Burkholderia cepacia and other bacteria (as
Enterobacter) not mentioned in the results section and analyzed in the discussion. What are the definitions used to define MDR in these bacterial isolates?
12. The authors define the distribution of species according to the hospital wards and specimens. However, data concerning the distribution of species according to studied hospitals is also interesting.
13. Amikacin and imipenem have a low percentage of resistance, why was amikacin not listed as the most effective antibiotic along with imipenem (paragraph one – antimicrobial resistance pattern of clinical isolates).
14. In the discussion, the authors refer the increase of resistance in their hospitals to the unrestricted use of antibiotics in Sudanese hospitals. However, the misuse of antibiotics in the community and extra-hospital settings can also affect this upward trend. Addressing the one health concept is a way to cope with the rising threat of antimicrobial resistance. In addition, this increase in antimicrobial resistance in Sudanese hospitals may due to the occurrence of (silent) outbreaks that need investigation and control.
15. Could the author explain what did they mean in the discussion by: “In this study, we observed high rates of resistance to extended-spectrum B-lactamases (ESBL)”.
16. In the discussion, the authors concluded that the resistance rate (134 gram-negative bacilli resistant to three or four classes of antibiotics isolated over a period of 6 months) is relatively higher than the rate reported in a previous study also conducted in SUH over 30 months from January 2011 to June 2013 (reference 33). The authors of reference 33 isolated 80 bacterial strains resistant to all available antibiotics including meropenem (Microbiology records SUH). Did the authors of the manuscript isolate the same number of isolates that are resistant to all available antibiotics including meropenem as stated in the last sentence, “This concerning finding...Including meropenem")?
17. The authors must compare their findings in the discussion to those obtained in the MENA and the surrounding region. Following are some reviews addressing resistance in such regions: Al-Orphaly
et al. (2021)
2, Moghnieh
et al. (2018)
3, and Dandachi
et al. 2019
4.
18. The authors should be aware when formulating their findings: is actually
K. pneumoniae the most commonly isolated organism from the blood specimens among all organisms? Or within Gram-negative bacteria? The same applies to other findings? And if among all organisms, these data are not represented in the text. Please revise the text accordingly.
19. The language is generally good in the text, however, many paragraphs and sentences are written poorly. For example:
"by using the following primers (Macrogen, Korea), using species-specific primers";
"The purity and integrity of each PCR product was evaluated electrophoresis in a 2% agarose gel";
There are also many typos in the text as (use Aztreonam instead of aztreoname, settings instead of sittings,
Enterobacter cloacae instead of
Enterobacter colecaes) and in Figure 1 (cotrimoxazole instead of cotramoxazole, even I prefer using the same nomenclature for antibiotics in the text as well as in the figure).
These aforementioned examples are not exhaustive; therefore, the text should be revised accordingly, and I suggest a language edit.
20. Verify numbers in the text, table, and figure throughout the text. For instance, how did the authors get the number 86 isolates that are resistant to three classes of antimicrobial drugs, as well as for the 38
A. baumannii isolates that are also resistant to three classes of antimicrobial drugs? These numbers did not match table 4. Another example is the percentage of ceftazidime-resistant
E.coli: in the text 84.2% vs in the figure 2 80.60%.
21. Table 4 should be reorganized to become more visible and clearer. Simply, the authors can drop the last row (total row) because it confuses the readers about what the total row is standing for.
22. In the text, when mentioning authors of a reference in the discussion, please write the last name of the first author (not the first name) of the citation as mentioned in the reference list. Instead of Jitendra
et al., (discussion) please mention Javeri
et al., as reference 28 in the reference list. Gales
et al., 2010 is used to refer to reference 29, while it should be mentioned as Zavascki
et al., 2010.
23. Please capitalize the first letter in the word (gram) throughout the text.
24. Once the full name of bacteria species is defined for the first time (ex:
Klebsiella pneumoniae), use the abbreviated form (
K. pneumoniae) throughout the text. The same applies to other abbreviated forms as Intensive care units, one ICU is spelled out for the first time mentioning intensive care units in the text, use the abbreviated form throughout the text.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
No source data required
Is the study design appropriate and is the work technically sound?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
Reviewer Expertise:
Molecular epidemiology of infectious diseases
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
References:
Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.Clin Microbiol Infect.2012;18(3) :
10.1111/j.1469-0691.2011.03570.x268-812179398810.1111/j.1469-0691.2011.03570.x:
Epidemiology of Multidrug-Resistant Pseudomonas aeruginosa in the Middle East and North Africa Region.mSphere.2021;6(3) :
10.1128/mSphere.00202-213401168610.1128/mSphere.00202-21:
Epidemiology of common resistant bacterial pathogens in the countries of the Arab League.
The Lancet Infectious Diseases.2018;18(12) :
10.1016/S1473-3099(18)30414-6e379-e39410.1016/S1473-3099(18)30414-6:
Understanding the Epidemiology of Multi-Drug Resistant Gram-Negative Bacilli in the Middle East Using a One Health Approach.Front Microbiol.2019;10:
10.3389/fmicb.2019.0194119413150755810.3389/fmicb.2019.0194110.5256/f1000research.19402.r84294Reviewer response for version 1MarkwartRobby12Referee
Infectious Disease Epidemiology, Robert Koch Institute, Jena University Hospital, Nordufer, Berlin, 13353, Germany
Jena University Hospital, Institute of General Practice and Family Medicine, Jena, Germany
Competing interests: No competing interests were disclosed.
The study
Antimicrobial resistance surveillance among gram-negative bacterial isolates from patients in hospitals in Khartoum State, Sudan by Hana Salaheldin Elbadawi
et al. investigates the spectrum of gram-negative bacterial pathogens and antimicrobial resistance patterns in Khartoum State, Sudan.
The manuscript is generally well written and the data are presented in a clear way. However, I have some suggestions, which may help to improve the manuscript.
Specific comments:
The authors state that isolates from eight hospitals in Khartoum state were included in the study. Include these eight hospitals all hospitals in Khartoum State or are they are a sample of more hospitals?
The study was carried out between October 2016 and February 2017, i.e. encompassing the winter season. Is it possible that the spectrum of gram-negative pathogens could be different in the summer season?
In table 2 and 3, what exactly do the p-values indicate? What is the purpose of the p values? If the authors want analyze whether there are statistical differences in the proportion of isolates between in hospital wards (Table 2) or clinical sample materials (Table 3), I also suggest adding 95% confidence intervals of the proportions.
I personally do not like the visual style of the Figures (Figures 1 and 2). From my knowledge, 3-dimensional bar charts are unusual in scientific publications. I suggest designing the figures in a more scientific format. Moreover, I suggest adding figure legends that include the total number of isolates tested per antibiotic. Furthermore, the authors could consider adding 95% confidence intervals to the bar charts since the study represents a more or less random sample of isolates in Sudan. The authors should discuss the representativeness of their study for Sudan or even North-East Africa.
In the discussion, the authors conclude that “
K. pneumonia was the most commonly isolated organism from the blood specimens mainly in neonatal sepsis in a high rate (39.8%).” This might be correct, but the study only analyzes the distribution of gram-negative pathogens. That means from the data presented in the manuscript, the authors only can conclude that K. pneumonia is the most frequent pathogen among gram-negative pathogens. Similarly, the authors state that the most frequently observed pathogens in urine specimens were E. coli and K. pneumonia. Again, this only true among gram-negative pathogens. At least in Germany, gram-positive
Enterococcus spp. are the second most frequent found pathogens in urine samples (Klingeberg 2018).
In the discussion, it would be helpful to compare the resistance patterns with studies from the same region in Sudan or surrounding regions / countries. Are the resistance proportions higher or lower in Khartoum State compared to surrounding regions / countries? Similarly, the authors could compare their resistance patterns with other regions of the world. For Europe, I suggest data from EARS-Net (European Antimicrobial Resistance Surveillance Network), for the United States CDC data are available. For example, in Germany, a nationwide study showed that only 3.5% of all
A. baumannii (complex) isolates were carbapenem resistant (Said
et al. Antimicrob Resist Infect Control 2021 Mar 1;10(1):45
1). For China, there are multiple systematic reviews and meta-analyses for antimicrobial resistance proportions for different pathogens available. A systematic comparison of the resistance rates described in this study with resistance patterns in other regions would help to put the data in perspective.
In the introduction, the authors state
“This study may help in formulating antibiotic policies tailored to our hospitals. These data can be used as information for action” antibiotic stewardship and interventions to optimize antibiotic prescribing practice, therefore prolongs the usefulness of existing antibiotics.”. However, in the discussion these aspects are not addressed properly. What clinical conclusions do the authors draw from their data? How do these data help to taylor ABS interventions? Etc.
Minor comments:
I suggest a profound proof reading in order to correct spelling mistakes and typos in the manuscript.
I suggest adding a column “Total” in Tables 2 and 3 to indicate the total numbers of the isolated pathogens (e.g. Table 2: 249 for
K. pneumonia)
Is the work clearly and accurately presented and does it cite the current literature?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
No source data required
Is the study design appropriate and is the work technically sound?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
Reviewer Expertise:
infectious disease epidemiology
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
References:
The epidemiology of carbapenem resistance in Acinetobacter baumannii complex in Germany (2014–2018): an analysis of data from the national Antimicrobial Resistance Surveillance system.
Antimicrobial Resistance & Infection Control.2021;10(1) :
10.1186/s13756-021-00909-810.1186/s13756-021-00909-8