Phenotypic Bacterial Isolates, Antimicrobial Susceptibility Pattern and Associated Factors among Septicemia Suspected Patients at a hospital, in Northwest Ethiopia. Prospective cross- sectional study

doi:10.21203/rs.3.rs-1532625/v1

Background

Septicemia is a life-threatening infection when pathogenic bacteria infiltrate the bloodstream, leading morbidity and mortality in Ethiopian hospital patients. Multidrug resistance is a therapeutic challenge among this patient and has a paucity of data in the hospitals. Therefore, this study aimed to assess the bacterial isolates, antimicrobial susceptibility pattern, and associated factors among septicemia suspected patients.

Methods

Prospective cross-sectional study was conducted among 214 septicemia suspected patients from February to June 2021 a hospital in northwest, Ethiopia. Blood samples were collected aseptically and processed to identify bacterial isolates by using different standard microbiological procedures. Antimicrobial susceptibility pattern was performed using the modified Kirby Bauer disc diffusion on Mueller Hinton agar. Epi-data V4.2 was used to enter data and SPSS V25 for analysis. The variables were assessed using a bivariate logistic regression model with a 95% confidence interval, and declared statistically significant; P-value was < 0.05.

Results

The overall bacterial isolates was found 45/214 (21%) in this study. Gram-negative and positive bacteria were 25/45(55.6%), 20/45(44.4%) respectively. The most common bacterial isolates were Staphylococcus aureus12/45 (26.7%), Klebsiella pneumonia8/45(17.8%), Escherichia coli 6/45 (13.3%). Gram-negative bacteria showed susceptible to amikacin (88%), meropenem, imipenem (76%), but resistance to (92%) ampicillin, (85.7%) amoxicillin-clavulanic acid. S.aureus (91.7%) resistance to Penicillin, (58.3%) cefoxitin and (75%) susceptible to ciprofloxacillin. S.pyogenes and S.agalactia were (100%) susceptible to Vancomacin. Multidrug resistance was found in 27/45(60%) of the bacterial isolates. The main predictors related to patients suspected of septicemia were prolonged hospitalization (AOR = 2.29, 95% CI: 1.18, 7.22), fever (AOR = 0.39, 95%CI: 0.18, 0.85) and length of hospital stay (AOR = 0.13, 95%CI: 0.02, 0.82).

Conclusions

Bacterial isolates among septicemia suspected patients were high. The majority of the bacterial isolates were multidrug-resistant. To prevent antimicrobial resistance, specific antibiotic utilization strategy should be applied.

Bacterial Isolates

Septicemia

Antimicrobials Susceptibility

Ethiopia

Septicemia is a life-threatening infection in the bloodstream that is a major public health concern around the world and fatal if not treated with appropriate antimicrobials[1]. The production or release of toxin of bacteria in the bloodstream is known as septicemia [2, 3].It is similar to terms like Blood poisoning, Bacteremia with sepsis and systemic inflammatory response syndrome(SIRS) are all phrases that are comparable to it[4]. It causes illness and deaths in all groups of the population[5], especially in immunocom-promised patients in an intensive care unit (ICU), elders, and children [6], cancer patient [7, 8], and patients living with human immunodeficiency virus (HIV)[9]. The incidence rate of septicemia is increased due to previous hospitalization, length of hospital stay, unexplained fever, age groups, gestational age of the mother, serious injury, chronic antibacterial therapy, comorbidities, invasive medical procedures, respiratory disease, urinary tract disease, gastrointestinal disease, HIV/AIDS, hematological disorders are the factors that increase the severity of septicemia[5, 7, 10, 11]. Different Gram-negative and positive bacteria are common and the bacterial spectrums are vary to place to place, and time [12–15].

The global burden of bacterial infection of the blood in recent scientific publications estimate that 48.9 million new cases of septicemia were registered globally in 2017, with 11.0 million septicemia-related deaths ,accounting 20% of all deaths worldwide[16]. Forty-one percent of all global sepsis cases in 2020 by the World Health Organization (WHO) estimates all worldwide and in sub-Saharan African and Asia countries were 30–70% were children under the age of five, with a death rate of 42% among intensive care patients with septicemia [17, 18]. One in two cases of sepsis in intensive care units (ICUs) result from healthcare-associated infections. Mortality in healthcare-associated septicemia from hospitalized adult patients range from 20–30%, pediatric ICUs 20%-50% deaths worldwide among 200,000 cases reported [17, 19–21]. On the other hand, among infants identified with septicemia, 40% have died, the major toll being in developing countries makes difficult to control worldwide and a major public health concern[22, 23]. In low and middle-income countries (LMICs)including Ethiopia more than 19 million septicemia cases and 5 million septicemia-related deaths are estimated to occur annually [16, 19].

Almost in all septicemia-related cases; antimicrobial management is started empirically earlier than the results of blood culture [24]. As a result, patients who are improperly treated may have a mortality rate of 100% [25] and the emergence of antimicrobial resistance in all kinds of pathogenic bacteria has been worsen in resource limiting countries [25–28]. In addition to that, self-prescription, misuse and over-prescriptions of antimicrobials without real etiological agent identification cause a huge challenge for controlling of antimicrobial resistance in Ethiopia. Consequently, there is limited information about commonly prescribed antibiotics for their susceptibility profile, and the epidemiology of bacterial isolates septicemia suspected patients in Northwest Ethiopia. Thus, this study aimed to assess the phenotypic bacterial isolates, antimicrobial susceptibility pattern, and associated factors among septicemia suspected patients at a hospital, in Northwest Ethiopia.

Study design, Period and Settings

A hospital-based prospective cross-sectional study was conducted from February to June 2021 among septicemia suspected patients in East and west Gojjam Zone referred and admitted patients at Debre Markos comprehensive Specialized Hospital (DMCSH). The hospital is located in Amhara National Regional state in East Gojjam zone, Debre Markos town. DMCSH is a 218-bedded hospital and is the largest public comprehensive hospital in East Gojjam zone-receiving patients directly from the community, referrals from other district primary hospitals and health centers. In its catchment area, DMCSH gives health services for more than 5 million people found in the zone and nearby border neighborhoods. It has different wards with ICU, Medical, Pediatric, Surgery, Emergency, Gynecology departments and medical laboratory services. All patients greater than /equal to one month old suspected of septicemia were the study population during the study period. All patients ≥ one-month-old and suspected of septicemia at DMCSH who were given consent, and assent was included. Seriously, ill patients and that did not give the blood sample during the data collection period, contaminated blood samples were excluded from the study.

Sample size determination and Sampling

The sample size was determined by using the formula (n= (Z_α⁄2)² P (1- P) /d²). By reviewing similar different studies done before and to this extent, the maximum sample size was obtained from a study conducted in southern, Ethiopia, which was a P-value of 15.8% (0.158)[1]. So, n= (Z_α⁄2)² P (1- P) /d² and a margin of error (d = 0.05) and 95% confidence interval. That is p = 0.158, d = 0.05, Z = 0.05 = Zα/2 = 0.025 = 1.96. Therefore, n= (1.96)2* 0.158(1-0.158)/ (0.05)2 = 204. Then 5% non-respondent rates were added and the final sample size would be 214. A convenience sampling technique was used when the attending physicians suspect septicemia at each ward.

Operational Definition

Multidrug resistance: Multidrug resistance: In this study, multidrug resistance is defined as simultaneous resistance to three or more antimicrobial agents with different groups of antimicrobials [29].

Data collection, Specimen processing and culturing for Identification of Bacterial isolates

Semi-structured questionnaires were used to obtain socio-demographic, laboratory, and clinical data. The data were collected by face-to-face interviews with trained nurses, and laboratory personnel. Laboratory technicians and experienced nurses who take training were collected the blood sample. The vein puncture site was properly disinfected with 70% alcohol and 2% tincture of iodine. Two bottles of blood for each patient were collected (5ml blood for patients older than five years and 1-3ml for under five patients) aseptically from both hands within 30-minute difference [30]. After obtaining the blood, it was inoculated at bedside into Tryptone Soy Broth (TSB) (Oxoid, Hampshire, UK) maintaining a minimum of blood to broth ratio 1:10. The TSBs were prepared according to the blood specimen collected; 10ml, 20ml, 30ml, and 45ml. Medical microbiology specialists were performed blood culture processing, biochemical testing, and antimicrobial susceptibility pattern of the isolate. The blood bottles were incubated at 37⁰c and inspected daily for the presence of visible microbial growth until 7 days. Irrespective of the state of bacterial growth sub-cultures were made after 24 hr, 48 hr, 72 hr on blood agar plate (BAP) (Oxoid, Hampshire, UK), chocolate agar plate (CAP) (Oxoid, Hampshire, UK), MacConkey agar plate (MACA) (Oxoid, Hampshire, UK), and Mannitol salt agar (MSA) (Oxoid, Hampshire, UK). The BAP, MACA, and MSA plates were incubated in an aerobic atmosphere 37^0Cand examined after24–48 hr whereas CAP plates incubated in a candle jar at 5–10% CO2 at the same temperature. Finally, at the 7th day blood bottles that did not showing bacterial growth were reported as no bacterial growth observed. Bacterial growths on the sub-cultured plates were identified by their characteristic appearances. Gram stain and specific biochemical reaction panels were used for bacterial isolates. Gram-negative bacteria were identified using biochemical tests such as indole test (Oxoid, Hampshire, UK), carbohydrate fermentation reaction in triple sugar iron (TSI) (Oxoid, Hampshire, UK), citrate utilization (Oxoid, Hampshire, UK), motility test (Oxoid, Hampshire, UK), lysine decarboxylase (Oxoid, Hampshire, UK), and oxidase test. Catalase, coagulase, CAMP test, Bacitracin test were used Gram-positive bacteria according to methods described in clinical laboratory standards institute (CLSI) [31–33].

Antimicrobial susceptibility pattern

Antimicrobial susceptibility testing for all blood culture isolates were done on modified Kirby Bauer disc diffusion methods of Mueller-Hinton agar(MHA) plates (Oxoid, Hampshire, UK) according to the criteria of CLSI of 2020[31]. A fresh 2 to 5 pure colonies from BAP or CAP were selected and transferred to 5 ml sterile nutrient broth (Oxoid, Hampshire, UK.),and mixed to make the suspension homogenous and transferred into sterile normal saline by sterile pipette. At the end, turbidity was adjusted visually with sterile normal saline to match with a 0.5 McFarland standard. The suspension was then inoculated uniformly over the entire surface of a MHA plate using a sterile swab. The inoculated plates were left at room temperature to dry for 3–15 minutes. Using sterile forceps, the antibiotic discs were placed on MHA by considering 24 mm distance between each disk and15 mm from the border. The antimicrobial discs were used in the given concentrations in the brackets, selected with availability, and frequently prescribed for the management of bacterial infections in the hospital and as entire in Ethiopia. Antimicrobials used for this study were: Ampicillin (AMP)(10µg), ceftazidime(CAZ)(30µg), ceftriaxone (CTR) (30µg), cefepime (CFP) (30µg) chloramphenicol (CHL) (30 µg), ciprofloxacin (CPR) (5µg), gentamicin(GEN) (10µg), amikacin (AMK) (30 µg), piperacillin(PIP) (30µg), meropenem(MER)(10µg),imipenem (IMP)(10µg) and trimethoprin-sulfamethoxazole(TS)(1.25/23.75µg) ,amoxicillin- clavulanic acid(AMC) (20 µg),cefoxitin (CXT) (30 µg),penicillin (P) (10 IU), and vancomacin (VAN) (30 µg). Cefoxitin disk diffusion tests were used to identify methicillin resistance Staphylococci. The results were interpreted by measuring the zone of inhibition as sensitive, intermediate, and resistant according to the standardized CLSI guidelines[31, 32].

Quality control

Pre-tested questionnaires were used. The questionnaires were prepared in English, translated into Amharic, and back translated to English to check consistency. Half-day training was given for those laboratory personnel, and nurses. Standard operating procedures (SOPs) were firmly followed throughout the laboratory analysis to assure the quality of the process in this research starting from pre-analytical to post-analytical. Five percent of all the prepared culture media were incubated over night at 37⁰c without inoculation to ensure the sterility of the media. Performance check was made on a standard reference strains to the culture media of BAP, CAP, MACA and MSA whenever a new batch of media was prepared. American Type Culture Collection (ATCC) standard reference strains (E. coli ATCC 25922, S. aureus (ATCC 25923, and P.aeruginosa ATCC27853) were used. The principal investigator daily checked the completeness of data and the laboratory work procedures as a whole.

Data analysis and Interpretation

Data were entered and cleaned by using Epi-Data V.4.2 computer program and exported to SPSS V 25-software package for the analysis. The completeness and consistency of the data were checked by running cross-tabulation of each variable. A binary logistic regression model was used to show any association between independent and outcome variables. A variable with a p-value ≤ 0.25 in the bivariate analysis was entered into multivariate analysis to identify variables that were independently associated with the outcome variable. The presence and strength of association between independent and outcome variables were computed by an adjusted odds ratio with a 95% confidence interval (CI). Hosmer–Lemeshow test was used to test the fitness of the model. A p-value of < 0.05 was considered as an indicator of a statistically significant association between the predictors and the dependent variable.

Socio-demographic and Clinical characteristics

Of 214 septicemia, suspected patients were included in this study. Out of these, 109(50.9%) were males. The median age of the participants with their interquartile range was 14 ± 9.3years, (64%) had a fever, 43 (20.1%) had previous medical procedures (Table 1).

Table 1

Socio-demographic characteristics of septicemia suspected patients at a hospital, in Northwest Ethiopia, 2021
Characteristics(n = 214)	Frequency	Percentage
Age 1month-11month 1–5 years 6–10 years 11–15 years > 15 years	48 51 41 16 58	22.4 23.8 19.2 7.5 27.1
Sex Male Female	109 105	50.9 49.1
Residence Rural Urban	130 84	60.7 39.3
Patient ward Surgery Emergency Pediatric Medical ICU	13 12 154 21 14	6.1 5.6 72 9.8 6.5
Fever Yes No	137 77	64 36
Temperature _<37^0C _>37^0C	74 140	34.6 65.4
Previous medical procedure Yes No	43 171	20.1 79.9
Previous hospital admission Yes No	56 158	26.2 73.8
Co morbidity Yes No	87 127	40.7 59.3
Type of chronic disease HIV/ADIS Diabetes mellitus Chronic liver disease Chronic kidney disease Chronic heart disease	18 20 12 10 30 123	8.4 9.3 5.6 4.7 14.5 57.5
Wound case Yes No	36 178	16.8 83.2
Burn Case Yes No	11 203	5.1 94.9
Length of hospital stay < 5 days > 5days	23 191	10.7 89.3

Prevalence of bacterial isolates

The overall bacterial isolates from this study was 45/214(21%, 95% CI; 14.6–25.2%, p=0.028) for blood culture to different bacterial species. Among the bacterial isolates, Gram-negative bacteria were the predominant isolate 25/45(55.6%, 95% CI; 47.2–53.5%) and Gram-positive bacteria were 20/45(44.4%, 95% CI; 35.1–52.7%). From the Gram-negative bacteria isolated K.pneumonia8/25(32%), E.coli6/25(24%), and P.aeruginosa4/25(16%) were the predominant bacteria isolated in the blood cultures (Fig. 1).

Twenty (44.4%) of Gram-positive bacteria isolates were found in this study. S.aureus 12/20(60%), Coagulase-negative staphylococcus (CONS) /204(20%), S.pyogenes 2/20(10%), and S. agalactia 2/20(10%) were the predominantly isolated bacteria in septicemia suspected patients. From the total bacterial isolate in the present study S.aureus 12/45(26.7%), K.pneumonia 8/45(17.8%), E.coli 6/45(13.3%), CoNS, and P.aroginosa 4/45 (8.9%) were the main bacterial isolates. All blood stream bacterial infections isolated during the study period were monomicrobial (Fig. 2).

Factors Associated with blood culture positivity and Septicemia

All associated factors were analyzed for their associations to septicemia by using binary logistic regression methods with explanatory variables. As we were seen in the analysis from the bivariate analysis, socio-demographic and clinical variables were associated with septicemia. Patients who had a temperature greater than 37⁰c, previous medical procedure had a risk factor, but not statistically significant at 95% CI. In this study from the bivariate analysis history of antibiotic usage was 2.21 times more likely blood culture positive as compared to those who had no antibiotic usage before and statistically significant at (95% CI;1.11–4.39, p = 0.024). In Bivariate logistic regression analysis, eight variables that indicated a p-value less or equal to 0.25 were candidate variables for the multivariate analysis to test the association. These candidate variables were age, ward type, fever, hospital admission, admission date in the hospital, previous medical procedure, antibiotic usage, and temperature were interviewee variables for multivariate analysis. By using the backward variable selection method, a multivariate logistic regression method showed that only three variables were associated with blood culture positivity. As shown in the multiple logistic regression analysis, patients who had previous hospital admission were 2.9 times more likely to expose septicemia as compared to patients who had no hospital admission. In this study in the multivariate analysis patients, who had fever were 61% less likely to expose to septicemia as compared to their counterparts (Table 2).

Table 2

Bivariate and multivariate analysis for the socio-demographic and clinical variables associated with septicemia suspected patients at a hospital, in Northwest Ethiopia 2021
Variables	Positive (%) n = 45	Negative (%) n = 169	COR(95%CI)	P-Value	AOR(95%CI)	P-value
Sex Male Female	23(23.8) 22(19.8)	89(76.2) 80(80.2)	1 0.90(0.46,1.74)	0.753
Age 1month-11month 1–5 6–10 11–15 > 15	16(33.3) 10(19.6) 7(17.1) 2(12.5) 10(19.6)	32(66.7) 41(80.4) 34(82.9) 14(87.5) 48(80.4)	0.47(.19,1.14) 0.96(.37,2.49) 1.14(.40,3.23) 1.6(.32,8.28) 1	0.25*
Residence Rural Urban	14(18.9) 31(22.1)	60(81.1) 109(77.9)	0.82(.41,1.66) 1	0.582
Patient Ward Surgery Emergency Pediatrics Medical ICU	4(14.3) 5(15.6) 33(29.7) 2(7.4) 1(6.3)	24(85.7) 27(84.4) 78(70.3) 25(92.6) 15(93.7)	1 0.4(.0.04,3.93) 0.36(0.04,3.37) 0.16(0.02,1.42) 0.83(0.07,9.99)	0.432 0.371 0.079* 0.886
Co morbidity Yes No	25(21.6) 20(20.4)	91(79.6) 78(78.4)	1.07(0.55,2.07) 1	0.84
Fever Yes No	33(23.6) 12(16.2)	107(76.4) 62(83.8)	1.6(0.3,1.30) 1	0.026*	0.39(0.18,0.85) 1	0.012
Hospital admission Yes No	39(24.7) 6(10.7)	119(75.3) 50(89.3)	2.73(1.09,6.86) 1	0.032*	2.9(1.18,7.22) 1	0.020
Length of hospital stay < 5days ≥ 5days	11(57.9) 34(17.8)	8(42.1) 157(82.2)	1 6.35(1.34,42.7)	0.0001*	1 0.13(0.02,0.82)	0.03
Previous Medical procedure Yes No	38(23.9) 7(12.7)	121(76.1) 48(87.3)	2.15(0.90–5.15) 1	0.085*
Antibiotic usage Yes No	19(13.0) 26(38.2)	42(61.8) 127(87)	2.21(1.11,4.39) 1	0.024*
Temperature < 370c > 370c	35(8.8) 10(35.4)	108(91.2) 60(64.6)	1 1.9(.89,4.77)	0.095*
^{Key: COR: Crude odds ratio, CI: Confidence interval, AOR: Adjusted odds ratio * indicates to the variable entered into multiple logistic regression}

Antimicrobial Susceptibility Patterns of Bacterial Isolates

The Susceptibility of Gram-negatives

The susceptibility patterns of the bacterial species were checked using sixteen antimicrobial discs according to CLSI 2020 guideline. The sensitivity patterns of Gram-negative bacteria (n = 25) were isolated from the blood culture of patients suspected of septicemia against 11 antimicrobial discs (Table 3). The range of sensitivity and resistance of K. pneumonia in this study was from 0%-87.5%, and 0%-100%, respectively. K. pneumonia was (100%) resistant to ampicillin, and amoxicillin-clavulanic acid, (75%) for Ceftazidime and chloramphenicol, however, it showed 7/8 (87.5%) susceptible for amikacin. E.coli in the current study was (100%) sensitive to amikacin,(83.3%) for meropenem and imipenem. E.coli showed high resistance to gentamycin 5(83.3%), ampicillin 5(83.3%), amoxicillin-clavulanic acid 5(83.3%). P.aeruginosa was 4/4(100%) sensitive to imipenem, ¾(75%) ciprofloxacillin, amikacin, meropenem, and 75% resistance to gentamycin (Table 3).

Table 3

Antimicrobial susceptibility pattern of Gram-negative bacteria isolated from blood culture for patients suspected of septicemia at a hospital, in Northwest Ethiopia, 2021
GNB isolated from blood culture		Antimicrobial disks
GNB isolated from blood culture		MER	IPM	AMK	CPR	CTR	GM	C	TS	CAZ	AMP	AMC
K.pneumonia (n = 8)	S I R	5(62.5%) 0 3(37.5%)	5(62.5%) 1(12.5%) 2(25%)	7(87.5) 1(12.5) 0(0.00)	4(50%) 0 4(50%)	1(12.5) 0 7(87.5)	3(37.5 0 5(62.5	2(25) 0 6(75)	3(37.5) 1(12.5) 4(50)	2(25) 0 6(75)	0 0 8(100)	0 0 8(100)
E.coli (n = 6)	S I R	5(83.3) 0 1(16.7)	5(83.3) 0 1(16.7)	6(100) 0 0(0.0)	3(50.0) 0 3(50.0)	3(50.0) 0 3(50.0	1(16.7 0 5(83.3	2(33.3) 0 4(66.7	2(33.30 0 4(66.7	3(50.0) 1(16.7 2(33.3)	1(16.7 0 5(83.3	1(16.7 0 5(83.3)
P.aeruginosa (n = 4)	S I R	3(75) 0 1(25)	4(100) 0 0(0.0)	3(75) 0 1(25)	3(75) 0 1(25)	Nr Nr Nr	1(25) 0 3(75)	Nr Nr Nr	Nr Nr Nr	2(50.0) 0 2(50.0)	1(25) 0 3(75)	Nr Nr Nr
K.rhinose (n = 2)	S I R	1(50.0) 0 1(50.0)	0(0.0) 0 2(100)	1(50) 0 1(50.0)	1(50) 0 1(50)	0 0 1(50)	0 0 2(100	1(50) 0 1(50)	2(100) 0 0	0(0.0) 0 2(100	0(0.0) 0 2(100	1(50) 0 1(50)
E.aerogenes (n = 2)	S I R	2(100) 0 0	2(100) 0 0	2(100) 0 0	1(50.0) 0 1(50)	1(50.0) 0 1(50)	1(50.0 0 1(50)	1(50.0) 0 1(50)	1(50) 0 1(50)	0 0 2(100	0 0 2(100	0 0 2(100
Serratia spp (n = 2)	S I R	2(100) 0 0	2(100) 0 0	2(100) 0 0	2(100) 0 0	0 0 2(100)	1(50) 0 1(50)	1(50) 1(50) 0(0.0)	2(100.0 0 0	0 0 2(100)	1(50) 0 1(50)	0 0 2(100)
K.ozanae (n = 1)	S I R	1(100) 0 0	1(100) 0 0	1(100) 0 0	1(100) 0 0	0 0 1(100)	0 1(100 0	0 1(100 0	1(100) 0 0	0 0 1(100)	0 0 1(100)	0 0 1(100)
Total (n = 25)	S I R	19(76) 0(0) 6(24)	19(76) 1(4) 5(20)	22(88) 1(4) 2(8)	15(60) 0(0) 10(40)	5(23.8) 0(0) 16(76.2)	7(28) 1(4) 17(68)	7(33.3) 2(9.5) 12(57.2)	11(52.4) 1(4.8) 9(42.8)	7(28) 1(4) 17(68)	2(8) 0(0) 23(92)	3(14.3) 0(0) 18(85.7)
^{Key: −GNB: Gram−negative bacteria, MER: Meropenem, IPM: Imipenem, AMK: Amikacin, CPR: Ciprofloxacillin, CTR: Ceftriaxone, GM: Gentamycin, C: Chloramphenicol, TS: Trimethoprin−Sulfamethoxazole, CAZ: Ceftazidime, AMP: Ampicillin, AMC: Amoxicillin−clavulanic acid. S: Sensitive, I: Intermediate, R: Resistance, Nr: Not recommended}

Gram-positive bacteria

Antimicrobial sensitivity pattern results showed that Gram-positive bacteria, S.aureus 11(91.7%) was resistant to penicillin, 5(41.7%) was resistant to gentamycin, and 7 (58.3%) was resistant to ciprofloxacin (Table 5). From 12 S.aureus, 8 (66.7%) were methicillin resistance Staphylococcus (MRSA) by using cefoxitin disc whereas the remaining four (33.3%) were methicillin-sensitive S. aureus (MSSA).In other words, CONS were only one (25%) methicillin resistance, and three (75%) were methicillin-susceptible coagulase-negative staphylococci. S.pyogenes were (100%) susceptible to all antimicrobials used. S.agalactia was (100%) sensitive to ceftriaxone, trimethoprin-sulfamethoxazole and vancomacin, however (50%) resistance to ampicillin (Table 4).

Table 4

Antimicrobial susceptibility pattern of Gram-positive bacteria isolated from blood culture for patients suspected of septicemia at a hospital, in Northwest Ethiopia, 2021
Gram positive bacteria		Antimicrobial disks
Gram positive bacteria		PEN	GM	CPR	CXT	CFP	CTR	AMP	TS	VAN
S.aureus (n = 12)	S I R	1(8.3) 0 11(91.7)	9(75) 0 3(25)	10(83.3) 0 2(17.3)	4(33.3) 0 8(66.7)	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr
CONS (n = 4)	S I R	3(75) 0 1(25)	3(75) 0 1(25)	3(75) 0 1(25)	3(75) 0 1(25)	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr
S.pyogenes (n = 2)	S I R	2(100) 0 0	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr	2(100) 0 0	2(100) 0 0	2(100) 0 0	Nr Nr Nr	2(100) 0 0
S.agalactia (n = 2)	S I R	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr	Nr Nr Nr	2(100) 0 0(0.0)	1(50) 0 1(50)	2(100) 0 0	2(100) 0 0
Total (n = 20)	S I R	6(33.3) 0(0.0) 12(66.7)	12(75) 0 4(25)	13(81.3) 0 3(18.7)	7(43.7) 0 9(56.3)	2(100) 0 0	4(100) 0 0	3 (75) 0 1(25)	2(100) 0 0	4(100) 0 0
^{Key: −CONS: Coagulas−enegative Staphylococcus, PEN: Penicillin, GM: Gentamicin, CPR: Ciprofloxacillin, CXT: Cefoxitin, CFP: Cefepime, CTR: Ceftriaxone, AMP: Ampicillin, TS: Trimethoprin−Sulfamethoxazole, VAN: Vancomacin, S: Sensitive, I: Intermediate, R: Resistance, Nr: Not recommended}

Multidrug resistance (MDR)

In our study, the prevalence of multidrug resistance was 27/45 (60%). Whereas three (6.7%) blood bacterial isolates were sensitive to all antimicrobials tested and one of the isolated bacteria was resistant for all of the antimicrobial groups examined. However, the result of drug resistance patterns compared with species-specific observed two (100%) of k.rhinose, two (100%) of Serratia spp, six (75%) of K.pneumonia, and three (75%) of p.aeruginosa were MDR pathogens in this study (Table 5).

Table 5

Multi-drug resistance patterns of bacteria isolated from septicemia suspected patients at a hospital, in Northwest Ethiopia, 2021
Bacteria isolate	Antimicrobial Resistance pattern N (%)
Bacteria isolate	R0	R1	R2	R3	R4	R5	R6	R7	MDR
S.aureus	1(8.3)	3(25)	1(8.3)	2(16.7)	5(41.7)	0(0)	0(0)	0(0)	7(58.3)
CONS	0(0)	3(75)	0(0)	0(0)	1(25)	0(0)	0(0)	0(0)	1(25)
S.pyogenes	0(0)	2(100)	0(0)	0(0)	0(0)	0(0)	0(0)	0(0)	0(0)
S.agalactia	0(0)	0(0)	1(50)	1(50)	0(0)	0(0)	0(0)	0(0)	1(50)
K.pneumonia	1(12.5)	1(12.5)	0(0)	2(25)	1(12.5)	1(12.5)	2(25)	0(0)	6(75)
E.coli	1(16.7)	0(0)	1(16.7)	0(0)	1(16.7)	1(16.7)	1(16.7)	1(16.7)	4(66.7)
P.aeruginosa	0(0)	1(25)	1(25)	2(50)	0(0)	0(0)	1(25)	0(0)	3((75)
E.aerogenes	0(0)	0(0)	1(50)	0(0)	0(0)	1(50)	0(0)	0(0)	1(50)
K.rhinose	0(0)	0(0)	0(0)	1(50)	0(0)	0(0)	1(50)	0(0)	2(100)
Serratia spp	0(0)	0(0)	0(0)	1(50)	1(50)	0(0)	0(0)	0(0)	2(100)
K.ozane	0(0)	0(0)	1(100)	0(0)	0(0)	0(0)	0(0)	0(0)	0(0)
Total	3(6.7)	10(22.2)	6(13.3)	9(20)	9(20)	3(6.7)	5(11.1)	1(2.2)	27(60)
^{Key:−RO: Sensitive for all antimicrobial groups, R1: resistance for only one antimicrobial groups, R2: resistance for two antimicrobial groups, R3: resistance for three antimicrobial groups, R4: resistance for four antimicrobial groups, R5: resistance for five antimicrobial groups, R6: resistance for six antimicrobial, and R7: resistance for seven antimicrobial groups}.

The result of this study showed that the overall prevalence of bacteria isolated from septicemia suspected patients by blood culture method were 21%, which was in line with studies conducted in varieties of countries in the world outside and inside Ethiopia, in India, (16.08–22.3%) [22, 24, 34, 35], Jimma (18.2%) [1] Gondar (18.2%, 19.4%) [7, 12]. Similarly the same results were also found in Mozambique 15.1% [36], Iran 21.1% [37],Ghanaian hospital (23.16%) [26], Nigeria 20.4% [28]. On the other hand, the prevalence of bacteria isolated from this study was lower than articles conducted in India (90%,30.6) [29, 38], Iran (38%)[39], Cameroon (28.3%) [25], Addis Ababa (27.9%,32.8%) [3, 40], Mekelle (28%) [13] and Bahir Dar (32%, 39.2%) [41, 42]. However, the current study was higher prevalence than from the studies done in Addis Ababa (13%) [11], Jimma (8.8%) [43], Arba Minich (11.3%) [2], Nepal (10.6%) [15], Kuwait (2.3%) [21], New Zealand (9.5%) [44], India (4.4%) [45], Bangladesh (13.2%) [44], Ghana (11.2%) [46], and Southern Africa (5.5%) [47]. The possible reason for this variation might be explained by the fact that difference in the geographical location, the study population, method of study design, sample size, epidemiological variation, implementation of infection prevention and control, blood culture diagnostic system, study duration, and health care policy systems in these different countries.

In our present study, Gram-negative bacteria were more predominantly isolated than Gram-positive bacteria, which a prevalence of 55.6% and 44.4%, respectively. Similarly, concordant findings were observed in the study conducted in India (51.2%) [38], Iran (55.4%) [37], and Nepal (52.3%, 50.5%) of the isolates were gramnegative bacteria which was the same with the current study[15, 48]. However, our finding was lower than other studies conducted, where grampositive bacteria was the predominant isolated bacteria than gram negative bacteria in India (60.9%61.4%) [43, 49], Jimma (53.3%) [1],Addis Ababa (77.4%) [40], Gondar (66%) [12] from this Grampositive bacteria were predominant. The varying percentages could be due to methodology difference and the patient safety practice, diagnostic method.

Among blood bacteria isolates in this study were S. aureus, K.pneumonia, E. coli, CONS, and P.aeruginosa were the most plentiful causative agent for septicemia, which had orderly put the prevalence(26.7%),(17.8%),(13.3%),(8.9%),(8.9%) and similar findings were found in Indonesia which was K.pneumonia (17%), P.aeruginosa (12%)[50].Greater or a lesser amount of similar results have been seen in studies conducted in septicemia suspected patients from different regions in Ethiopia. Although, the frequency and bacterial magnitude were varied in Addis Ababa, Ethiopia 50%,26.21% 14.02% [40],in Mekelle, Ethiopia37.5%,11.1% [13], and Southern Ethiopia 32.2%,14.3% [2].These bacteria are normal microbiota of the skin, and in the majority of the time found in the hospital areas as a result cause infection in immune susceptible patients.

In the present study, different associated factors were evaluated for various associations with septicemia. Nevertheless, not all of the socio-demographic variables in the current study were statistically associated with septicemia. However, this study indicated that males were more infected than females (23.8% vs 19.2%), respectively, but there was no a statistically significant difference in gender variation (p = 0.632). This slight variation has been reported in different studies [12, 13, 51]. Patients in under-five age group were more infected with septicemia as compared to the adult age group. The possible reason for this is the children have more susceptible to infection due to less immune system and colonized by normal microbiota. Nevertheless, in this study the category of age groups were not statistically significant (p = 0.186). This finding disagrees with the research done in southern Ethiopia [2],Rwanda [52], Nepal [15], and the USA [53]. The possible reason for this difference might be due to the none representative of samples in each ward from this study.

Previous hospitalization in this study was 2.9 times more likely associated with septicemia in the current study. This research finding is consistent with the study conducted in Ethiopia AOR = 5.54 and AOR = 3.2[2, 9]. This association might be due to health care associated infections, high number of patients admitted to hospitals for prolonged periods, delayed request for blood culture, and a weak patient safety, and management system in the hospital. As a result, fast intervention had a must to minimize the infection.

The assessment of antimicrobial susceptibility pattern that differs in isolated bacteria, and the rates of resistance were high in this study, this may cause a serious therapeutic challenge for the management of common blood bacterial infections. The overall resistance of gram-positive and gram-negative bacteria in this study were 25%-66.7% and 8%-92% respectively, which was similar to the result reported in Mekelle for gram-positive 0-83.3% and gram-negative 0–100% [13], Jimma, 0-85.7% for gram-negative and 0%to 100% Gram-positive [1].This condition gives severe anxiety to the population. This high rate of resistance might indicate misuse and inappropriate usage of the antibacterial drugs. However, the resistance is different from the study conducted in Gondar where the rate of resistance for Gram positive bacteria ranged from 23.5–58.8% and gram negative bacteria 20–100% [12]. The observed variation may be due to the arbitrary use of antimicrobials in the study area, self-prescribing antimicrobials in private drug stores and empirical treatment of hospital acquired infections without real etiological agent identification.

In our study, S.aureus was 91.7% resistant to penicillin, but susceptible to 75% gentamicin, and 83.3% ciprofloxacillin. This was similar with reports conducted in different countries 40%-97% [22, 35, 40]. This is due to the unrestrained use of antimicrobials without sensitivity testing in the study area. (66.7%) of methicillin, resistance Staphylococcus aureus (MRSA) was detected. In order of, the same report was done in Indian and Ethiopian researches [7, 22, 45].The incident of MRSA is more common because of the haphazard use of higher antimicrobials empirically and genetic proficiency to obtain antibiotic resistance. S. pyogenes were 100% sensitive to cefepime, ampicilin, and vancomycin from our study. This was in line with the study reports, which had in 100%, 87% [14, 35]. Vancomycin was 100% sensitive to S. agalactia. This finding was similar to the reports done in Mekelle [13]. The possible reason for the absence of vancomycin resistant bacteria in this study is that the use of vancomycin by clinicians is controlled in the management of patients in the study setting, and in the nation as an entire.

K.pneumonia. E.coli, P.aeruginosa, K.rhinose, and Serratia spp in our study were 50–100% sensitive to meropenem, imipenem, and amikacin. This finding was similar to the reports [2, 22, 38, 45]. K.pneumonia and E.aerogenes were 100% resistant to ampicillin, amoxicillin -clavulanic acid. In addition, E.coli (83.3%) for gentamicin and P.aeruginosa (75%) for gentamicin and ampicillin resistance were observed in this study. These were consistent to other studies conducted in Ghana 74%[46], Ethiopia 86% and 94%[9, 41] and India 93%, 87%[45, 54].The finding of this study indicates most of the gram-negative bacteria were 50–100% resistance to ciprofloxacillin, gentamicin, ceftriaxone, chloramphenicol, trimethoprin-sulfamethoxazole, and ceftazidime. This was concordant with the research done in Cameroon 45%-100% [25] and Ethiopia [9, 11, 43].

The limitation of this study was done in a single hospital, and only a phenotypic test was done, which may under estimate the prevalence of bacteria for the different geographical areas. This study has not detected fungemia and anaerobic bacteria due to scarcity of the media.

In this study, the overall prevalence of blood culture positivity among septicemia suspected patients was moderately high. Gram-negative bacteria were the predominant etiological agents for septicemia in the study populations. S.aureus, K.pneumonia, E.coli, CONS, and P. aeruginosa were the predominant causative agent for septicemia; however, S. aureus was the highest prevalence in the bacterial isolates. Previous hospital admission, fever, and length of hospital stay of the patients were significantly associated with septicemia in our study. Gram-negative bacteria were highly resistant to ampicillin, amoxicillin-clavulanic acid, ceftriaxone, chloramphenicol, and trimethoprim-sulfamethoxazole, but susceptible to meropenem, imipenem and amikacin. While S. aureus was highly resistance to penicillin, although, susceptible to gentamicin and ciprofloxaccillin. High multi-drug resistance rates were observed in most bacterial isolates. The study calls researchers to conduct a further study with a large sample size, with better study design and budget. Clinicians are better to establish hospital antibiotic stewardship to minimize antimicrobial resistance among septicemia suspected patients. It is also essential to conduct constant antimicrobial sensitivity surveillance on blood culture isolates and ensuring more rational antimicrobial use and a combination of antimicrobial therapy may help to verify the appearance of resistance.

AMR: Antimicrobial Resistance, ATCC: American Type Culture Collection, BAP: Blood agar plate, BSIs Blood Stream Infections, CAP: Chocolate agar plate, CLSI: Clinical Laboratory Standards Institute, CONS: Coagulase-negative Staphylococcus, DMCSH: Debre Markos Comprehensive Specialized Hospital, ICU: Intensive Care Unit, LMICS: Low and Middle Income Countries, MAC: MacConkey Agar, MDR: Multidrug Resistance, MHA: Mueller Hinton Agar, MSA: Mannitol Salt Agar, QC: Quality control, SOPS: Standard Operating Procedures, SPSS: Statistical package of social science, TSB: Trypton soy broth, WHO: World health organization

Ethical approval and Informed consent

Ethical approval was obtained from the institutional review board (IRB) of Debre Markos University, College of Health Sciences (Ref No: HSC/R/C/Ser/PG/Co/ 281/12/13). A permission letter was obtained from the medical director of Debre Markos Comprehensive Specialized Hospital.Written informed consent and assent were obtained from all participants and their caregivers. Before sample collection, participants were informed clearly about the objective and procedure of the study.Participation was voluntary bases. All information obtained in this study was maintained confidentiality and utilized only for the study. For positive cases, the results were communicated with the attending physician for appropriate treatment of the participants.

Consent of publication

Not applicable

Availability of data and materials

All relevant data were present within the manuscript. The datasets used during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

Debre Markos University contributed financial support for the study.

Authors’ Contributions

HB was the primary researcher, conceived the study, designed, participated in data collection, laboratory work, conducted data analysis, drafted and finalized the manuscript for publication. WT, TD and AM and interpreted the results, and reviewed the initial and finaldrafts of the manuscript. All authors read and approved the final manuscript.

Author details

¹Departement of Medical Laboratory science, College of Health Sciences, Debre Markos University, P.o. Box 269, Debre Markos, Ethiopia.

AKNOWLEDGMENTS

First,we would like to acknowledge the Department of Medical Laboratory Science, College of Health Sciences, Debre Markos University for special support to conduct the study.

We would like to express our great appreciation to Ethiopian public health institute (EPHI), Armauer Hansen Research institute(AHRI), and Amhara public health institute (APHI) for their contribution to culture media, biochemical tests and antibiotic discs for this research.

Finally yet importantly, we express my gratitude to the study participants who participated in the study. We also thank the staff members of DMCSH staff members in pediatrics, medical, surgery, emergency and ICU wards for their professional assistance during the data collection. Finally, my special acknowledgment goes to Samirawit Tefera and Abeba Tigabe (MSc in Medical Microbiology) for their professional technical support during laboratory analysis and bacterial isolation.

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No competing interests reported.

Phenotypic Bacterial Isolates, Antimicrobial Susceptibility Pattern and Associated Factors among Septicemia Suspected Patients at a hospital, in Northwest Ethiopia. Prospective cross- sectional study

Archived Versions:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Study design, Period and Settings

Sample size determination and Sampling

Operational Definition

Data collection, Specimen processing and culturing for Identification of Bacterial isolates

Antimicrobial susceptibility pattern

Quality control

Data analysis and Interpretation

Results

Socio-demographic and Clinical characteristics

Prevalence of bacterial isolates

Factors Associated with blood culture positivity and Septicemia

Antimicrobial Susceptibility Patterns of Bacterial Isolates

The Susceptibility of Gram-negatives

Gram-positive bacteria

Discussions

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Archived Versions:

Version 1