Bacteriological Profile of Early Versus Late-onset Neonatal Sepsis at Tertiary Care Hospital in Nepal

Bacteriological Profile of Early Versus Late-onset Neonatal Sepsis at Tertiary Care Hospital in Nepal | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bacteriological Profile of Early Versus Late-onset Neonatal Sepsis at Tertiary Care Hospital in Nepal Rabita Karanjit, Sangita Sharma, Shyam Kumar Mishra, Hari Prasad Kattel, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5845225/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Jan, 2026 Read the published version in BMC Infectious Diseases → Version 1 posted 10 You are reading this latest preprint version Abstract Neonatal sepsis is one of the most common causes of neonatal mortality in developing countries like Nepal, ranking third after premature birth and birth asphyxia. This study intended to study the microbial etiology and antimicrobial susceptibility pattern of neonatal sepsis and its association with different birth conditions and C-reactive protein (CRP). Methods Blood samples were collected aseptically from 120 neonates suspected of sepsis, admitted to the Neonatal Intensive Care Unit (NICU) and Neonate wards of Tribhuvan University Teaching Hospital, Kathmandu, Nepal, and processed according to the protocol of the American Society for Microbiology (ASM). For antimicrobial susceptibility testing, the standard disc diffusion technique of the Kirby-Bauer method recommended by the Clinical and Laboratory Standards Institute (CLSI) 2019 was followed. Along with blood culture, a C-reactive protein (CRP) test was also carried out from each blood sample. Results Out of 120 blood cultures, 36 (30.0%) yielded microbial growth, 20 (55.5%) in the early-onset neonatal sepsis, and 16 (44.5%) in the late-onset neonatal sepsis. Among 36 blood culture-positive neonatal sepsis, 25 (69.5%) were born through normal delivery, 11 (30.5%) via Cesarean section (C-section); 23 (63.9%) were pre-term delivered neonates, 13 (36.1%) were termed delivered neonates; 23 (63.9%) were low birth weight neonates and 13 (36.1%) were normal birth weight. Among 36 isolates, 15 (41.7%) were gram-positive and 21 (58.3%) were gram-negative organisms. A higher percentage of Coagulase-negative Staphylococcus (n=5, 35.0%) was isolated in EONS, whereas Citrobacter freundii (n=5, 31.2%) was isolated in a higher percentage in LONS. Coagulase-negative Staphylococcus (n=11, 30.6%) were isolated in higher percentages followed by Citrobacter freundii (n=8, 22.2%), Klebsiella pneumoniae (n=6, 16.7%), Acinetobacter baumanii complex (n=5, 13.9%), Staphylococcus aureus (n=4, 11.1%), Acinetobacter lwoffii (n=1, 2.8%) , and Pseudomonas aeruginosa (n=1, 2.8%). Seventeen organisms (47.2%) showed multi-drug resistance of which one was an extended-spectrum beta-lactamase (ESBL) producer. A total of 40 blood samples (33.3%) tested positive for CRP, of which 35 had positive blood culture results. Based on blood culture results, CRP's sensitivity, specificity, and accuracy in this study were 97.2%, 94.0%, and 95.0% respectively which help to rule out the true infection and potential contamination of Coagulase-negative Staphylococcus in neonatal sepsis. Conclusion Gram-positive bacteria s tood out as the major causative agent of neonatal sepsis. MDR and ESBL were also prevalent in neonatal sepsis. Neonatal sepsis Gram-positive organisms Gram-negative organisms Normal delivery Cesarean section Multidrug resistance C-reactive protein Figures Figure 1 Figure 2 Introduction Neonatal sepsis is an infection that occurs within the first 28 days (4 weeks) of neonates' life involving their bloodstream. (1, 2) Sepsis in neonates may encompass various systemic infections like septicemia, meningitis, pneumonia, osteomyelitis, arthritis, and urinary tract infections (3), accompanied by bacteremia. (4) However, superficial infections like oral thrush and conjunctivitis are not considered neonatal sepsis. (5) Based on the time of symptom onset, neonatal sepsis can be dichotomized as Early-onset neonatal sepsis (EONS) and Late-onset neonatal sepsis (LONS). EONS typically present within the first 72 hours of life, whereas LONS appears after 72 hours, but before 28 days from birth. (3, 6) Usually, conditions of the maternal genital tract and perinatal status are proven risk factors for EONS infection including low birth weight (<2500 grams) or prematurity, febrile illness in the mother with bacterial infection occurring 2 weeks before childbirth, foul smelling and/or meconium stained liquor of neonates, prolonged rupture of membranes >24 hours, prolonged labor, single unclean or more than three sterile vaginal examinations during labor, and perinatal asphyxia. (7, 8) Unhygienic cord care can increase the risk of sepsis by nearly threefold. (9) These risk factors also caused LONS, with additional factors like poor hygiene of mother and neonate, poor cord care, bottle feeding, and pre-lacteal feeds. Neonates who received traditional substances on the umbilical cord were 2.8 times more likely to develop LONS compared to those who received antiseptic care. (10) LONS are either nosocomial infections or community-acquired infections. (7, 8, 11) Neonatal sepsis is the third most common cause of neonatal death after prematurity and asphyxia in the world. Globally, around 1.3 million cases of neonatal sepsis are estimated annually and 203,000 deaths occur per year. (12) The total incidence of culture-positive sepsis is 15.8 per 1000 live births according to South Asian hospitals report. (13) In Nepal, the incidence of neonatal mortality has remained the same from 2016 to 2022 i.e. 21 per 1000 live births shown by the study of Nepal Demographic and Health Survey 2022. (14) The most common cause of neonatal sepsis is bacterial, which differs according to the dimension of the globe. The source of infection acquired by patients also impacts the causative agent of infection. The most common causative agents of EONS are Escherichia coli, and Group B Streptococci. Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, CoNS, and Group B Streptococci are the most common bacteria found in both hospital-acquired infection and community-acquired infection which is linked to LONS . (15-20) In diagnosing and monitoring sepsis, C-reactive protein (CRP) serves as an acute-phase reactant that rises within two hours of infection onset and peaking within 48 hours. (21) It plays a role in defense mechanisms against inflammation and pathogen invasion. (22) However, CRP has low specificity for bacterial infections and also causes false positivity in non-infections inflammatory diseases. (23) This study focuses on identifying and comparing the bacteriological agents for early and late-onset neonatal sepsis and different conditions of birth causing neonatal sepsis and evaluating their antibiotic sensitivity pattern among neonates admitted to the NICU and neonatal wards of tertiary care hospitals in Nepal. Materials and Methods This was a prospective, cross-sectional study carried out from January 2021 to June 2021. A total of 120 blood samples were collected from the neonates who were suspected of sepsis and admitted to the NICU (14 beds) and neonate wards (70 beds) from birth to 28 days at Tribhuvan University Teaching Hospital (TUTH), an 850-bed tertiary care center of Nepal. Inclusion Criteria: Neonates admitted from birth to 28 days were included. Exclusion Criteria: Neonates with gross congenital malformation, severe cardiac abnormalities, and neonates taken against medical advice were excluded to minimize confounding factors and ensure an accurate assessment of sepsis-related outcomes. Ethical Clearance: Written informed consent was taken from every patient before enrollment. Sample Size: The sample size was calculated using Cochran's formula with a prevalence rate of 16.9%.( 24 ) $$\:SS=\frac{{z}^{2}\left(p\right)\left(1-p\right)}{{D}^{2}}$$ SS = sample size z = standard normal prevalence at 95% Confidence Interval = 1.96 p = prevalence rate = 0.169 D = Type I error = 10% = 0.1 $$\:SS=\frac{{\left(1.96\right)}^{2}.\left(0.169\right).\left(1-0.169\right)}{{\left(0.1\right)}^{2}}$$ SS = 53 Sample Collection and Processing: The 1.5 ml of blood samples were collected using aseptic techniques to eliminate contamination. One ml was collected in a gel vial tube for CRP test and 1ml was inoculated into BacT/ALERT culture bottles (BiomerieuxUSA, BacT/ALERT 3D, US, Pioneering Diagnostics) transported, and incubated for seven days in BacT/ALERT (BiomerieuxUSA, BacT/ALERT, US, Pioneering Diagnostics) blood culture system. The samples were sub-cultured from growth-positive bottles on blood agar and MacConkey agar plates. Identification of Isolates: Bacterial identification was done by using standard microbiological techniques following the protocol of the American Society for Microbiology (ASM). Initially, gram staining of isolates was performed. Then, catalase and coagulase tests were done to differentiate Staphylococcus aureus from other gram-positive cocci. For differentiating gram-negative bacteria catalase and oxidase tests were performed. Further biochemical tests were performed to differentiate gram-negative bacteria. The Triple Sugar Iron Agar (TSI), Sulphide Indole Motility (SIM), Simmons Citrate media, and Christensen's Urease media were used for biochemical testing. We also repeated cultures to eliminate contaminants and confirmed suspected contaminants. Antibiotic Susceptibility Testing: The antibiotic susceptibility testing (AST) of isolated organisms was processed on Muller Hinton Agar (MHA) using the disc diffusion Kirby-Bauer method. The standard ATCC strains of Escherichia coli (ATCC 25922) and Staphylococcus aureus (ATCC 25923) was used to maintain quality control. The zone sizes were interpreted following the breakpoints guidelines of the Clinical and Laboratory Standards Institute (CLSI) M100: 2019 Performance Standards for Antimicrobial Susceptibility Testing. ( 25 ) Detection of MDR: The isolates resistant to at least one agent in three or more antimicrobial categories were regarded as MDR. ( 25 ) Detection of MRSA and MR-CoNS: Cefoxitin (30µg) was used to detect MRSA and MR-CoNS. Staphylococcus aureus with a zone of inhibition ≤ 21 mm were confirmed as MRSA, while CoNS with a zone of inhibition ≤ 24 mm were confirmed as MR-CoNS. ( 25 ) Detection of ESBL: For the detection of potential ESBL producers, Ceftriaxone (CTR, 30µg) was used. The isolates with ≤ 13 mm of diameter were further confirmed for ESBL producers. As a confirmatory test double disc synergy test using Ceftazidime (CAZ, 30µg), Cefepime (CPM, 30µg), and Amoxicillin-Clavulanate (AMC, 20 µg + 10µg) was done. These were placed 20 mm apart, center to center, and incubated at 35 ± 2 ° C for 16–18 hours. The isolates that showed a cleared extension of the zone of inhibition around Ceftazidime and/or around Cefepime towards the disc containing clavulanate were confirmed as ESBL producers. ( 25 ) Parallelly, for control of ESBL detection negative control ( Escherichia coli ATCC 25922) and positive control ( Klebsiella pneumoniae ATCC 700603) were also used. ( 26 ) Detection of CRP: The latex agglutination slide test (PCR Slide, Giesse Diagnostics, Italy) was used for the qualitative detection of CRP in serum separated from blood samples collected from neonates. A CRP level greater than 5 mg/dl was considered the cut-off for a positive result. ( 27 ) Data Analysis: The collected data were entered and analyzed using SPSS 20.0. The chi-square test was performed for p-values with a level of significance of 95.0% (0.01) to show blood culture positivity, organism isolation, MDR association with different EONS, LONS, and different birth conditions, and CRP with blood culture. Microsoft Excel was used to prepare charts and tables. Results Demographic Study A total of 120 blood samples were collected from neonates admitted to the NICU and Neonate wards with suspected sepsis, among which 82 (68.3%) were male and 38 (31.7%) were female. Out of 120 samples, 36 (30.0%) yielded positive blood cultures of which 11 (30.5%) were from males and 25 (69.5%) from females. According to the time of sepsis onset, 95 (79.2%) neonates had suspected EONS and 25 (20.8%) had suspected LONS, with 20 (55.5%) and 16 (44.5%) culture-positive cases respectively. Out of 120 suspected neonatal sepsis cases, 55 (45.8%) neonates were born by normal vaginal delivery, and the remaining 65 (54.2%) by C-section. A higher percentage of bacteriological culture confirmed sepsis was observed in neonates delivered by C-section (n = 25, 69.5%) than by normal delivery (n = 11, 30.5%). According to the term of delivery, pre-term (n = 54, 45.0%) delivered neonates had a higher incidence of sepsis (n = 23, 63.8%) compared to term (n = 66, 55.0%) delivered neonates. The low birth weight (n = 23, 63.8%) neonates had a higher percentage of sepsis compared to normal birth weight (n = 13, 36.2%) neonates. A significant association was observed between different modes of delivery and blood culture results (p-value < 0.01). (Table 1 ) Table 1 Blood Culture Positivity According to Different Conditions of Child Birth Conditions Blood Culture (N = 120) p-value Positive (n = 36, 30.0%) Negative (n = 84, 70.0%) Time of Sepsis Onset EONS (n = 95, 79.2%) 20 (55.5%) 75 (89.3%) 0.00 LONS (n = 25, 20.8%) 16 (44.4%) 9 (10.7%) Mode of Delivery Normal Delivery (n = 55, 45.8%) 11 (30.5%) 44 (52.4%) 0.02 Cesarean Section (n = 65, 54.2%) 25 (69.5%) 40 (47.6%) Term of Delivery Pre-term (n = 54, 45.0%) 23 (63.9%) 31 (36.9%) 0.06 Term (n = 66, 55.0%) 13 (36.1%) 53 (63.0%) Weight on Birth Low Birth Weight (n = 52, 43.3%) 23 (63.9%) 29 (34.5%) 0.03 Normal Birth Weight (n = 68, 56.7%) 13 (36.1%) 55 (65.4%) Relation between Different Birth Conditions In this study, a significant association of EONS (n = 20, 55.5%) and LONS (n = 16, 44.5%) was observed with the mode of delivery (p-value = 0.04). However, there was no significant association between EONS and LONS in terms of delivery and neonates' birth weight. (Table 2 ) Table 2 Correlation between mode of delivery, term of delivery, and birth weight with onset time of sepsis Conditions Time of Sepsis Onset p-value EONS (n = 20, 55.5%) LONS (n = 16, 44.5%) Mode of Delivery Normal Delivery (n = 11, 30.5%) 8 (40.0%) 3 (18.8%) 0.04 Cesarean Section (n = 25, 69.5%) 12 (60.0%) 13 (81.2%) Term of Delivery Pre-term (n = 23, 63.8%) 12 (60.0%) 11 (68.8%) 0.73 Term (n = 13, 36.2%) 8 (40.0%) 5 (31.2%) Weight on Birth Low Birth Weight (n = 23, 63.8%) 14 (70.0%) 9 (56.3%) 0.59 Normal Birth Weight (n = 13, 36.2%) 6 (30.0%) 7 (43.7%) Isolates Distribution According To Blood Culture Out of 120 samples collected for blood cultures, 36 (30.0%) samples showed growth of organisms, among which 15 (41.7%) were gram-positive and 21 (58.3%) were gram-negative organisms. Among all isolates, coagulase-negative Staphylococcus (CoNS) (n = 11, 30.6%) was predominant followed by Citrobacter spp. (n = 8, 22.2%). (Fig. 1 ) Isolates Distribution according to Different Birth Conditions The EONS (n = 20, 55.5%) rate was higher than LONS (n = 16, 44.4%) in which CoNS and Citrobacter freundii were isolated in higher numbers respectively. In the mode of delivery, neonatal births from C-section were more infected than neonates from normal delivery. The pre-term neonates and neonates with low birth weight were more prone to sepsis. The organisms isolated in sepsis had no significant association with any birth condition (p-value > 0.01). (Table 3 ) Table 3 Distribution of Isolated Organisms According to Different Modes of Delivery Conditions Staphylococcus aureus (n = 4) CONS (n = 11) Klebsiella pneumoniae (n = 6) Pseudomonas aeruginosa (n = 1) ACB C (n = 5) Acinetobacter lowffii (n = 1) Citrobcter freundii (n = 8) p-value Time of Sepsis Onset EONS (n = 20) 3 (15.0%) 7 (35.0%) 2 (10.0%) 1 (5.0%) 3 (15.0%) 1 (5.0%) 3 (15.0%) 0.57 LONS (n = 16) 1 (6.3%) 4 (25.0%) 4 (25.0%) 0 (0.0%) 2 (12.5%) 0 (0.0%) 5 (31.2%) Mode of Delivery Normal Delivery (n = 11) 2 (18.2%) 3 (27.2%) 2 (18.2%) 0 (0.0%) 2 (18.2%) 1 (9.1%) 1 (9.1%) 0.55 Cesarean Section (n = 25) 2 (8.0%) 8 (32.0%) 4 (16.0%) 1 (4.0%) 3 (12.0%) 0 (0.0%) 7 (28.0%) Term of Delivery Pre-term (n-23) 3 (13.0%) 6 (26.1%) 3 (13.0%) 1 (4.4%) 4 (17.4%) 0 (0.0%) 6 (26.1%) 0.61 Term (n = 13) 1 (7.7%) 5 (38.5%) 3 (23.1%) 0 (0.0%) 1 (7.7%) 1 (7.7%) 2 (15.3%) Weight at Birth Low Birth Weight (n = 23) 2 (8.7%) 5 (21.7%) 4 (17.4%) 0 (0.0%) 4 (17.4%) 1 (4.4%) 7 (30.4%) 0.33 Normal Birth Weight (n = 13) 2 (15.3%) 6 (46.3%) 2 (15.3%) 1 (7.7%) 1 (7.7%) 0 (0.0%) 1 (7.7%) Pattern of AST in Gram-Positive Isolates The Staphylococcus aureus isolates showed 100.0% of sensitivity to Gentamicin, Amikacin, Vancomycin, Teicoplanin, and Chloramphenicol followed by 75.0% sensitivity to Cephalexin, Levofloxacin, Cloxacillin, Clindamycin, and Doxycycline. Additionally, Gentamicin, Amikacin, Vancomycin, and Teicoplanin exhibited 100% susceptibility, while Clindamycin showed 81.9% effectiveness against CoNS isolates. MRSA was detected in 25.0% of Staphylococcus aureus isolates, and 27.3% of CoNS were identified as MR-CoNS. (Table 4 ) Table 4 Antibiotic Susceptibility Testing of Gram-Positive Isolates Drugs Staphylococcu aureus (n = 4) CoNS (n = 11) Sensitive Resistant Sensitive Resistant Penicillin (10µg) 0 (0.0%) 4 (100.0%) 3 (27.3%) 8 (72.7%) Cephalexin (30µg) 3 (75.0%) 1 (25.0%) 8 (72.7%) 3 (27.3%) Cotrimoxazole (25µg) 2 (50.0%) 2 (50.0%) 8 (72.7%) 3 (27.3%) Gentamicin (10µg) 4 (100.0%) 4 (0.0%) 11 (100.0%) 0 (0.0%) Amikacin (30µg) 4 (100.0%) 4 (0.0%) 11 (100.0%) 0 (0.0%) Ciprofloxacin (5µg) 2 (50.0%) 2 (50.0%) 6 (54.5%) 5 (45.5%) Levofloxacin (5µg) 3 (75.0%) 1 (25.0%) 8 (72.7%) 3 (27.3%) Cloxacillin (5µg) 3 (75.0%) 1 (25.0%) 8 (72.7%) 3 (27.3%) Vancomycin (30µg) 4 (100.0%) 0 (0.0%) 11 (100.0%) 0 (0.0%) Teicoplanin (30µg) 4 (100.0%) 0 (0.0%) 11 (100.0%) 0 (0.0%) Erythromycin (15µg) 1 (25.0%) 3 (75.0%) 4 (36.3%) 7 (63.7%) Clindamycin (2µg) 3 (75.0%) 1 (25.0%) 9 (81.9%) 2 (18.1%) Doxycycline (30µg) 3 (75.0%) 1 (25.0%) 8 (72.7%) 3 (27.3%) Chloramphenicol (30µg) 4 (100.0%) 0 (0.0%) 8 (72.7%) 3 (27.3%) Pattern of AST for Gram-Negative Isolates Among all the gram-negative isolates, Imipenem, Meropenem, Polymyxin B, and Colistin (> 50.0%) were sensitive in a higher number of organisms, whereas the organisms were more resistant against Ampicillin, Ceftriaxone, and Ceftazidime (< 50.0%). (Table 5 ) Table 5 Antibiotic Susceptibility Testing for Gram-Negative Isolates Drugs Citrobacter freundii (n = 8) Klebsiella pneumoniae (n = 6) Pseudomonas aeruginosa (n = 1) Acinetobacter spp. (n = 6) Sensitive Resistant Sensitive Resistant Sensitive Resistant Sensitive Resistant Ampicillin (10µg) 0 (0.0%) 8 (100.0%) 0 (0.0%) 6 (100.0%) NR 2 NR 2 NR 2 NR 2 Piperacillin (100µg) ND 1 ND 1 ND 1 ND 1 0 (0.0%) 1 (100.0%) ND 1 ND 1 Amoxicillin + Clavulunate (20µg + 10µg) 0 (0.0%) 8 (100.0%) 3 (50.0%) 3 (50.0%) NR 2 NR 2 NR 2 NR 2 Piperacillin + Tazobactam (100µg + 10µg) 7 (87.5%) 1 (12.5%) 5 (83.3%) 1 (16.7%) 1 (100.0%) 0 (0.0%) 5 (83.3%) 1 (16.7%) Ceftriaxone (30µg) 0 (0.0%) 8 (100.0%) 1 (16.7%) 5 (83.3%) NR 2 NR 2 3 (50.0%) 3 (50.0%) Ceftazidime (30µg) 0 (0.0%) 8 (100.0%) 1 (16.7%) 5 (83.3%) 1 (100.0%) 0 (0.0%) 0 (0.0%) 6 (100.0%) Cefepime (30µg) 4 (50.0%) 4 (50.0%) 4 (66.7%) 2 (33.3%) 1 (100.0%) 0 (0.0%) 3 (50.0%) 3 (50.0%) Cotrimoxazole (25µg) NR 2 NR 2 2 (33.3%) 4 (66.7%) NR 2 NR 2 NR 2 NR 2 Amikacin (30µg) 7 (87.5%) 1 (12.5%) 5 (83.3%) 1 (16.7%) 1 (100.0%) 0 (0.0%) 5 (83.3%) 1 (16.7%) Gentamicin (10µg) 4 (50.0%) 4 (50.0%) 4 (66.7%) 2 (33.3%) 1 (100.0%) 0 (0.0%) 5 (83.3%) 1 (16.7%) Ciprofloxacin (5µg) 3 (37.5%) 5 (62.5%) 4 (66.7%) 2 (33.3%) 1 (100.0%) 0 (0.0%) 4 (66.7%) 2 (33.3%) Levofloxacin (5µg) 3 (37.5%) 5 (62.5%) 4 (66.7%) 2 (33.3%) 1 (100.0%) 0 (0.0%) 4 (66.7%) 2 (33.3%) Imipenem (10µg) 8 (100.0%) 0 (0.0%) 6 (100.0%) 0 (0.0%) 1 (100.0%) 0 (0.0%) 3 (50.0%) 3 (50.0%) Meropenem (10µg) 8 100.0%) 0 (0.0%) 6 (100.0%) 0 (0.0%) 1 (100.0%) 0 (0.0%) 3 (50.0%) 3 (50.0%) Doxycycline (30µg) 3 (37.5%) 5 (62.5%) 5 (83.3%) 1 (16.7%) NR 2 NR 2 4 (66.7%) 2 (33.3%) Polymyxin B (300µg) 8 (100.0%) 0 (0.0%) 6 (100.0%) 0 (0.0%) ND 1 ND 1 6 (100.0%) 0 (0.0%) Colistin sulphate (10µg) 8 100.0%) 0 (0.0%) 6 (100.0%) 0 (0.0%) NR 2 NR 2 NR 2 NR 2 Ampicillin-Sulbactam (10µg + 10µg) 0 (0.0%) 8 (100.0%) 2 (33.3%) 4 (66.7%) NR 2 NR 2 NR 2 NR 2 1 Not Done 2 Not Recommended The pattern of MDR and ESBL Production among Isolates Out of a total of 36 isolates, 17 (47.2%) isolated organisms showed MDR on AST. The CoNS (n = 5, 29.4%) has a higher percentage of MDR among all the isolates, followed by Citrobacter freundii (n = 4, 23.6%). The ESBL producer was found only in Klebsiella pneumoniae (n = 1, 5.9%). (Fig. 2 ) MDR Isolates in Different Conditions of Delivery The different conditions of delivery seemed to be insignificant to MDR isolates. (Table 6 ) Table 6 MDR Isolates in Different Conditions of Delivery Conditions of Delivery Time of Sepsis Onset Mode of Delivery Term of Delivery Weight at Birth EONS LONS C-Section Normal Delivery Pre-term Term Under Weight Normal Weight MDR Isolates (N = 17) 7 (41.2%) 10 (58.8%) 13 (76.5%) 4 (23.5%) 13 (76.5%) 4 (23.5%) 10 (58.8%) 7 (41.2%) p-value 0.10 0.38 0.13 0.54 CRP in Different Conditions In every sample collected for blood culture, qualitative CRP was also done. Almost every sample that developed positive culture later had positive CRP except one. However, CRP was found positive in 5 negative blood culture samples. CRR detection and blood culture were also associated with each other (p-value < 0.01). (Table 7 ) Predictive Outcome of CRP According to Blood Culture CRP test was done before the outcome of blood culture. According to this study, the sensitivity of the CRP test is 97.2% and its specificity is 94.0% with 95.0% accuracy. (Table 8 ) Table 8 Predictive Outcome and Validity of CRP with Blood Culture Sensitivity 97.2% Specificity 94.0% Predictive Positive 87.5% Predictive Negative 98.8% Accuracy 95.0% DISCUSSION Neonatal sepsis remains one of the leading causes of neonatal morbidity and mortality, especially in developing countries like Nepal. Limited studies of neonatal sepsis associated with MDR and ESBL production are found in Nepal. This study was intended to determine the distribution of organisms associated with bacteriologically proven neonatal sepsis and the identification of MDR and ESBL isolates. In this study, about one-third of the neonates had microbiologically confirmed sepsis. This finding is consistent with the study by Shrestha et al. ( 28 ), conducted at Nepal Medical College Teaching Hospital, Nepal which reported 30.8% of cases. This rate is also comparable with the rates reported in other developing countries like Bangladesh (34.88%) ( 29 ), Uganda (37%) ( 30 ), and Ethiopia (44.7%) ( 31 ). However, negative blood culture does not mean they do not have sepsis as sepsis can be caused due to anaerobes, viral, protozoal, and treponemal pathogens shown by a study by Shrestha et al. ( 32 ) and Shehab et al. ( 33 ). The lack of trained manpower, diagnostic tools, and laboratory equipment may be a possible reason for not finding every possible case of neonatal sepsis. Our study aligns with the findings of Nagaveni et al., which conclude that neonatal sepsis is more common in males than females. ( 24 , 34 ) Additionally, the incidence of EONS in our study is higher than that of LONS, consistent with a study from Nepal by Ansari et al. ( 35 ) and from India by Rusia et al. ( 36 ). However, our findings contradict those of Shaw et al. ( 37 ) and Kayange et al. ( 38 ), who reported a higher incidence of LONS compared to EONS. There is a significant association between EONS and LONS with bacterial culture (p-value < 0.01), suggesting the variation in incidence may be affected by the global environment factors as well as maternal and neonatal conditions. In this study, it was found that 69.4% of neonates with bacteriologically proven sepsis were delivered by Cesarean section, and 30.6% of them were delivered by normal vaginal delivery showing that neonates born by cesarean section had 2.26 times more sepsis compared to those delivered by normal vaginal delivery. The rate of neonatal sepsis significantly varied with the mode of delivery (p-value = 0.02 ) . Another study from Ethiopia by Woldu et al. showed that the incidence of neonatal sepsis in those delivered by cesarean section was 6.2 times that of those delivered by normal vaginal delivery. (39) Neonates delivered by cesarean section are probably at risk for laceration from sharp instruments during the procedure. A fetal laceration is found to occur in about 0.1–3.1% of cesarean section deliveries (40, 41) and this can be a possible route of entry of microorganisms leading to neonatal sepsis. Cesarean section delivery results in a longer hospital stay compared to vaginal delivery, which also increases the risk of neonatal sepsis. (42) The microbiota of infants delivered by Cesarean section were different as compared to normally delivered ones, which also raises the possibility of neonatal sepsis. (43) Our study shows a significant correlation between neonatal weights during birth with neonatal sepsis (p-value = 0.03). The neonates with low birth weight have almost twice more chance of developing neonatal sepsis than normal birth weight neonates. This study supports that birth weight is also one of the risk factors for developing neonatal sepsis. ( 24 ) Our study shows a significant association between the development of EONS and LONS with mode of delivery (p-value 0.04), but not with other birth conditions. These findings are consistent with the study by Adatara et al., which also reported a statistically significant relationship between the time of sepsis onset and the mode of delivery. (44) Among the total blood culture isolates, 41.7% were gram-positive and 58.3% were gram-negative. Among gram-positive isolates, CoNS, and Staphylococcus aureus were isolated. While Citrobacter freundii , Klebsiella pneumoniae , Pseudomonas aeruginosa , Acinetobacter baumanii complex, and Acinetobacter lowffii were isolated gram-negative organisms. Other studies from Nepal report Staphylococcus aureus , Klebsiella pneumoniae , and CoNS as common isolates. (24, 45) The study by Jatsho et al. from Bhutan also reports the most common isolates as CoNS, followed by Klebsiella pneumoniae and Acinetobacter . (46) Staphylococcus aureus and CoNS were highly resistant to Penicillin. In contrast, resistance to Cephalexin, Levofloxacin, Cloxacillin, Clindamycin, and Doxycycline was comparatively lower in both isolates. Both isolates were 100.0% susceptible to Gentamicin, Amikacin, Vancomycin, and Teicoplanin. Gentamicin (90% isolates) was found the most sensitive and ampicillin (76% isolates) was found to be the antibiotic least effective against Staphylococcus aureus by another study. ( 24 ) Higher percentage of MRSA (75.0%) and MR-CoNS (72.7%) were isolated in our study. The literature review of Huang et al. from China also showed the wide prevalence of MRSA and MR-CoNS in neonatal sepsis. ( 12 ) Our study found most gram-negative organisms were highly resistant to Ampicillin and Piperacillin. The Citrobacter freundii was highly susceptible to Imipenem, Meropenem, Polymyxin B, and Colistin sulfate followed by Piperacillin + Tazobactum and Amikacin. While Citrobacter freundii was highly resistant to Amoxicillin + Clavulunate, Ceftriaxone, Ceftazidime, and Ampicillin-Sulbactum followed by Ciprofloxacin, Levofloxacin, and Doxycycline. The study of Yadav et al. in Nepal found that Ceftazidime and Amikacin were the most effective antibiotics against Citrobacter spp. ( 24 ) In this study, 17 (47.2%) isolates out of 36 culture isolates were found to be MDR, out of which 7 (41.2%) were gram-positive and 10 (58.8%) were gram-negative. The only ESBL producer was Klebsiella pneumoniae (n = 1, 5.9%) among all MDR isolates. The other study by Pokhrel et al. from Nepal showed MDR strains in their study to be 73.91% and MDR among gram-negatives and gram-positives was found to be 80.76% and 52.94% respectively. (45) This study showed that there was a high degree of antimicrobial-resistant bacteria causing neonatal sepsis, indicating that MDR and ESBL can be the rising emergence in neonate fatality. Among the MDR isolates, 7 were found in EONS and 10 were found in LONS. This result is consistent with the study by Mohsen et al. which also showed that MDR isolates were more in LONS than EONS. (47) Our study showed 13 (76.5%) isolates of MDR are present in C-section delivery and pre-term neonates each, and 10 (58.8%) in under-weight neonates at birth. However, no significant association was established between the MDR isolation and conditions of delivery in our study. This inconsistency may be attributed to the limited sample size or the influence of unmeasured confounding factors. It is also possible that local antimicrobial practices and infection control measures played a role in shaping the resistance patterns observed. These findings highlight the need for larger, multicenter studies to better understand the complex interplay between delivery conditions and the emergence of MDR pathogens in neonates. CRP test has been widely used as screening tests for many inflammatory diseases caused by injury, infections, or chronic diseases. In this study, CRP was also performed in each sample received for blood culture. Among 120 samples, 40 blood samples were positive for CRP and 80 were negative. As a confirmatory test of sepsis, a result of blood culture was considered. Our study data showed that the sensitivity, specificity, PPV, NPV, and significant accuracy of the CRP test is 97.2%, 94.0%, 87.5%, 98.8%, and 95.0% respectively. The study of Morad et. al showed CRP has sensitivity, specificity, PPV, NPV, and significant accuracy of 89.5%, 66.7%, 92.5%, 60.0%, and 86.0% respectively. (48) Though CRP has higher sensitivity and specificity, it can't be used solely for sepsis confirmation. (49) This was a cross-sectional study conducted for six months, and the samples were only processed for aerobic bacteriology. The samples were not processed for anaerobic bacteriology, viral, and fungal cultures. This limitation may result in an incomplete understanding of the causative agents of neonatal sepsis, thereby affecting the accuracy and scope of the study’s findings. Conclusion This study shows that gram-negative organisms were the predominant cause of neonatal sepsis, despite a higher prevalence of CoNS. The incidence of neonatal sepsis is increasing due to the emergence of MRSA, MR-CoNS, MDR, and ESBL. Our study shows EONS, C-section deliveries, and pre-term neonates, and under-weight neonates are more prone to neonatal sepsis. It is important to note that some neonates with culture-proven sepsis may have negative CRP results, highlighting the limitation of relying solely on CRP for diagnosis. However, due to the cross-sectional nature of the study and the exclusion of certain pathogens, the generalizability of these results should be interpreted with caution. Abbreviations ASM: American Society for Microbiology ATCC: American Type Culture Collection AST: Antimicrobial Susceptibility Test CRP: C-reactive protein CLSI: Clinical and Laboratory Standard Institute EON: Early Onset Neonatal Sepsis ESBL: Extended Spectrum β-lactamase LONS: Late Onset Neonatal Sepsis MDR: Multidrug Resistance MHA: Mueller Hinton Agar MRSA: Methicillin Resistant Staphylococcus aureus NICU: Neonatal Intensive Care Unit SPSS: Statistical Package for Social Science CoNS: Coagulase Negative Staphylococcus CDC: Centre for Disease Control and Prevention Declarations Ethical Consideration This study was conducted after obtaining ethical clearance from the Institutional Review Committee of the Institute of Medicine (Ref: 221 (6-11)E 2 /077/078). Written verbal informed consent was taken from study participants and their visitors. Patients’ details were kept confidential throughout the study period. Informed Consent The written verbal informed consent was obtained from all the study participants and their visitors. Availability of data and materials All the data generated during this study are presented in this paper. The primary raw data will be made available to interested researchers by the corresponding author upon request. Conflict of interest The author(s) declared no potential conflicts of interest concerning the research, authorship, and/or publication of this article. Funding There was no financial support received in this study. Author's contribution Rabita Karanjit and Sangita Sharma: conceived and designed the experiments; Rabita Karanjit and Sangita Sharma: methodology and experimental design; Rabita Karanjit, Sunita Makaju, and Sangita Sharma: conduct research; Rabita Karanjit, Sagun Suwal, Sunita Makaju, Sujata Baidya, Sangita Sharma, Hari Prasad Kattel, and Shyam Kumar Mishra: manage, organize, maintain, analyze and interpret data; Sangita Sharma, Hari Prasad Kattel and Shyam Kumar Mishra: verify data and results; Sangita Sharma and Shyam Kumar Mishra: data curation; Sajal Twanabasu and Sagun Suwal: draft preparation; Sujata Baidya, Sagun Suwal, Sajal Twanabasu, Sangita Sharma, Shyam Kumar Mishra and Hari Prasad Kattel: review and editing; Rabita Karanjit, Sunita Makaju, and Sagun Suwal: visual elements preparation; Sangita Sharma, Shyam Kumar Mishra, and Hari Prasad Kattel: supervision. All authors read and approved the final manuscript. Acknowledgments We are beholden to all the participants of this study. Our special thanks go to all the physicians and staff members of the neonatal ICU, laboratory staff, management, and officials of Tribhuvan University Teaching Hospital, Maharajgunj, Kathmandu for giving us the environment to carry out this research work. We would also like to thank the TUTH family for being supportive and courageous during the study. Trial Registration Not applicable. References Singh M, Deorari AK, Khajuria RC, Paul VK. Perinatal & neonatal mortality in a hospital. Indian J Med Res. 1991;94:1-5. Singh M, Narang A, Bhakoo ON. Predictive perinatal score in the diagnosis of neonatal sepsis. J Trop Pediatr. 1994;40(6):365-8. Klein JO. Bacteriology of neonatal sepsis. Pediatr Infect Dis J. 1990;9(10):778. Tripathi S, Malik G. Neonatal Sepsis: past, present and future; a review article. Internet Journal of Medical Update - EJOURNAL. 2010;5:45-54. Gebremedhin D, Berhe H, Gebrekirstos K. Risk Factors for Neonatal Sepsis in Public Hospitals of Mekelle City, North Ethiopia, 2015: Unmatched Case Control Study. PLoS One. 2016;11(5):e0154798. Teshome G, Hussen R, Abebe M, Melaku G, Wudneh A, Molla W, et al. Factors associated with early onset neonatal sepsis among neonates in public hospitals of Sidama region, Southern Ethiopia, 2021: Unmatched case control study. Ann Med Surg (Lond). 2022;81:104559. Pandit BR, Vyas A. Clinical Symptoms, Pathogen Spectrum, Risk Factors and Antibiogram of Suspected Neonatal Sepsis Cases in Tertiary Care Hospital of Southern Part of Nepal: A Descriptive Cross-sectional Study. JNMA J Nepal Med Assoc. 2020;58(232):976-82. Attia Hussein Mahmoud H, Parekh R, Dhandibhotla S, Sai T, Pradhan A, Alugula S, et al. Insight Into Neonatal Sepsis: An Overview. Cureus. 2023;15(9):e45530. Chaurasia S, Sivanandan S, Agarwal R, Ellis S, Sharland M, Sankar MJ. Neonatal sepsis in South Asia: huge burden and spiralling antimicrobial resistance. Bmj. 2019;364:k5314. NDaHS. Nepal Demographic and Health Survey 2022: Key Indicators Report 2022 [Available from: https://mohp.gov.np/uploads/Resources/Nepal %20Demographic%20and%20Health%20Survey%202022%20Key%20Indicators%20Report.pdf. Shrestha RK, Rai SK, Khanal LK, Manda PK. Bacteriological study of neonatal sepsis and antibiotic susceptibility pattern of isolates in Kathmandu, Nepal. Nepal Med Coll J. 2013;15(1):71-3. Vergnano S, Sharland M, Kazembe P, Mwansambo C, Heath PT. Neonatal sepsis: an international perspective. Arch Dis Child Fetal Neonatal Ed. 2005;90(3):F220-4. Zaidi AK, Huskins WC, Thaver D, Bhutta ZA, Abbas Z, Goldmann DA. Hospital-acquired neonatal infections in developing countries. Lancet. 2005;365(9465):1175-88. Zaidi AK, Thaver D, Ali SA, Khan TA. Pathogens associated with sepsis in newborns and young infants in developing countries. Pediatr Infect Dis J. 2009;28(1 Suppl):S10-8. Downie L, Armiento R, Subhi R, Kelly J, Clifford V, Duke T. Community-acquired neonatal and infant sepsis in developing countries: efficacy of WHO's currently recommended antibiotics--systematic review and meta-analysis. Arch Dis Child. 2013;98(2):146-54. Anush MM, Ashok VK, Sarma RI, Pillai SK. Role of C-reactive Protein as an Indicator for Determining the Outcome of Sepsis. Indian J Crit Care Med. 2019;23(1):11-4. Wu Y, Potempa LA, El Kebir D, Filep JG. C-reactive protein and inflammation: conformational changes affect function. Biol Chem. 2015;396(11):1181-97. Guidelines CLSIC. 2019 CATALOG: clsi; 2019 [Available from: https://clsi.org/media/3266/catalog2019_web.pdf. Ahmed AS, Chowdhury MA, Hoque M, Darmstadt GL. Clinical and bacteriological profile of neonatal septicemia in a tertiary level pediatric hospital in Bangladesh. Indian Pediatr. 2002;39(11):1034-9. Mugalu J, Nakakeeto MK, Kiguli S, Kaddu-Mulindwa DH. Aetiology, risk factors and immediate outcome of bacteriologically confirmed neonatal septicaemia in Mulago hospital, Uganda. Afr Health Sci. 2006;6(2):120-6. Shitaye D, Asrat D, Woldeamanuel Y, Worku B. Risk factors and etiology of neonatal sepsis in Tikur Anbessa University Hospital, Ethiopia. Ethiop Med J. 2010;48(1):11-21. Shrestha P, Das BK, Bhatta N, Jha DK, Setia A, Tiwari A. Clinical and Bacteriological Profiles of Blood Culture Positive Sepsis in Newborns. Journal of Nepal Paediatric Society. 2009;27. Shehab El-Din EMR, El-Sokkary MMA, Bassiouny MR, Hassan R. Epidemiology of neonatal sepsis and implicated pathogens: a study from Egypt. BioMed research international. 2015;2015. P N. CLINICAL PROFILE OF NEONATES ADMITTED WITH SEPSIS – A TERTIARY CARE EXPERIENCE. IOSR Journal of Dental and Medical Sciences. 2016. Yadav NS, Sharma S, Chaudhary DK, Panthi P, Pokhrel P, Shrestha A, et al. Bacteriological profile of neonatal sepsis and antibiotic susceptibility pattern of isolates admitted at Kanti Children's Hospital, Kathmandu, Nepal. BMC Res Notes. 2018;11(1):301. Ansari S, Nepal HP, Gautam R, Shrestha S, Neopane P, Chapagain ML. Neonatal Septicemia in Nepal: Early-Onset versus Late-Onset. Int J Pediatr. 2015;2015:379806. Varsha, Rusia U, Sikka M, Faridi MM, Madan N. Validity of hematologic parameters in identification of early and late onset neonatal infection. Indian J Pathol Microbiol. 2003;46(4):565-8. Shaw CK, Shaw P, Thapalial A. Neonatal sepsis bacterial isolates and antibiotic susceptibility patterns at a NICU in a tertiary care hospital in western Nepal: a retrospective analysis. Kathmandu Univ Med J (KUMJ). 2007;5(2):153-60. Kayange N, Kamugisha E, Mwizamholya DL, Jeremiah S, Mshana SE. Predictors of positive blood culture and deaths among neonates with suspected neonatal sepsis in a tertiary hospital, Mwanza-Tanzania. BMC Pediatr. 2010;10:39. Woldu MA, Guta MB, Lenjisa JL, Tegegne GT, Tesafye G, Dinsa H. Assessment of the incidence of neonatal sepsis, its risk factors, antimicrobials use and clinical outcomes in Bishoftu General Hospital, neonatal intensive care unit, Debrezeit-Ethiopia. Int J Contemp Pediatrics. 2017;1(3):135-41. Okaro J, Anya S. Accidental incision of the fetus at caesarian section. Nigerian journal of medicine: journal of the National Association of Resident Doctors of Nigeria. 2004;13(1):56-8. Dessole S, Cosmi E, Balata A, Uras L, Caserta D, Capobianco G, et al. Accidental fetal lacerations during cesarean delivery: experience in an Italian level III university hospital. American Journal of Obstetrics and Gynecology. 2004;191(5):1673-7. Adatara P, Afaya A, Salia SM, Afaya RA, Konlan KD, Agyabeng-Fandoh E, et al. Risk Factors Associated with Neonatal Sepsis: A Case Study at a Specialist Hospital in Ghana. The Scientific World Journal. 2019;2019:9369051. Pokhrel B, Koirala T, Shah G, Joshi S, Baral P. Bacteriological profile and antibiotic susceptibility of neonatal sepsis in neonatal intensive care unit of a tertiary hospital in Nepal. BMC Pediatr. 2018;18(1):208. Jatsho J, Nishizawa Y, Pelzom D, Sharma R. Clinical and Bacteriological Profile of Neonatal Sepsis: A Prospective Hospital-Based Study. International Journal of Pediatrics. 2020;2020(1):1835945. Mohsen L, Ramy N, Saied D, Akmal D, Salama N, Abdel Haleim MM, et al. Emerging antimicrobial resistance in early and late-onset neonatal sepsis. Antimicrobial Resistance & Infection Control. 2017;6(1):63. Morad EA, Rabie RA, Almalky MA, Gebriel MG. Evaluation of Procalcitonin, C-Reactive Protein, and Interleukin-6 as Early Markers for Diagnosis of Neonatal Sepsis. Int J Microbiol. 2020;2020:8889086. Hisamuddin E, Hisam A, Wahid S, Raza G. Validity of C-reactive protein (CRP) for diagnosis of neonatal sepsis. Pak J Med Sci. 2015;31(3):527-31. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5845225","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":446585829,"identity":"97135d17-a6d3-4245-9ab8-35b251b034cd","order_by":0,"name":"Rabita Karanjit","email":"","orcid":"","institution":"Dhading Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rabita","middleName":"","lastName":"Karanjit","suffix":""},{"id":446585832,"identity":"a4af5574-3eb8-4215-ab05-ecbd8240c760","order_by":1,"name":"Sangita 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01:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5845225/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5845225/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-026-12645-8","type":"published","date":"2026-01-23T15:59:13+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82046597,"identity":"61d27341-578e-42e9-a66e-9db1eb8df8c4","added_by":"auto","created_at":"2025-05-06 09:39:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36017,"visible":true,"origin":"","legend":"\u003cp\u003eDifferent Isolates from Positive Blood Culture\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5845225/v1/68bfd6f9c400eb9d213ad01b.png"},{"id":82046610,"identity":"61e0ae4e-7d08-427c-aa92-697ff02a83f6","added_by":"auto","created_at":"2025-05-06 09:39:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13889,"visible":true,"origin":"","legend":"\u003cp\u003eIsolates with MDR (n=17) and ESBL Percentage\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5845225/v1/59eade0a68d2feae335cdb6c.png"},{"id":101151915,"identity":"c42cc2f2-6be1-422b-9f0d-5b2f44902118","added_by":"auto","created_at":"2026-01-26 16:08:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1457192,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5845225/v1/e97a1738-573f-4190-8185-814496baeaa3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eBacteriological Profile of Early Versus Late-onset Neonatal Sepsis at Tertiary Care Hospital in Nepal\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNeonatal sepsis is an infection that occurs within the first 28 days (4 weeks) of neonates\u0026apos; life involving their bloodstream. (1, 2) Sepsis in neonates may encompass various systemic infections like septicemia, meningitis, pneumonia, osteomyelitis, arthritis, and urinary tract infections (3), accompanied by bacteremia. (4) However, superficial infections like oral thrush and conjunctivitis are not considered neonatal sepsis. (5)\u003c/p\u003e\n\u003cp\u003eBased on the time of symptom onset, neonatal sepsis can be dichotomized as Early-onset neonatal sepsis (EONS) and Late-onset neonatal sepsis (LONS). EONS typically present within the first 72 hours of life, whereas LONS appears after 72 hours, but before 28 days from birth. (3, 6)\u003c/p\u003e\n\u003cp\u003eUsually, conditions of the maternal genital tract and perinatal status are proven risk factors for EONS infection including low birth weight (\u0026lt;2500 grams) or prematurity, febrile illness in the mother with bacterial infection occurring 2 weeks before childbirth, foul smelling and/or meconium stained liquor of neonates, prolonged rupture of\u0026nbsp;membranes \u0026gt;24 hours, prolonged labor, single unclean or more than three sterile vaginal examinations during labor, and perinatal asphyxia. (7, 8) Unhygienic cord care can increase the risk of sepsis by nearly threefold. (9) These risk factors also caused LONS, with additional factors like poor hygiene of mother and neonate, poor cord care, bottle feeding, and pre-lacteal feeds. Neonates who received traditional substances on the umbilical cord were 2.8 times more likely to develop LONS compared to those who received antiseptic care. (10) LONS are either nosocomial infections or community-acquired infections. (7, 8, 11)\u003c/p\u003e\n\u003cp\u003eNeonatal sepsis is the third most common cause of neonatal death after prematurity and asphyxia in the world. Globally, around 1.3 million cases of neonatal sepsis are estimated annually and 203,000 deaths occur per year. (12) The total incidence of culture-positive sepsis is 15.8 per 1000 live births according to South Asian hospitals report. (13) In Nepal, the incidence of neonatal mortality has remained the same from 2016 to 2022 i.e. 21 per 1000 live births shown by the study of \u003cem\u003eNepal Demographic and Health Survey 2022.\u0026nbsp;\u003c/em\u003e(14)\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe most common cause of neonatal sepsis is bacterial, which differs according to the dimension of the globe. The source of infection acquired by patients also impacts the causative agent of infection. The most common causative agents of EONS are \u003cem\u003eEscherichia coli,\u0026nbsp;\u003c/em\u003eand Group B \u003cem\u003eStreptococci.\u003c/em\u003e \u003cem\u003eKlebsiella pneumoniae, Escherichia coli, Staphylococcus aureus,\u0026nbsp;\u003c/em\u003eCoNS, and Group B \u003cem\u003eStreptococci\u0026nbsp;\u003c/em\u003eare the most common bacteria found in both hospital-acquired infection and community-acquired infection which is linked to LONS\u003cem\u003e.\u0026nbsp;\u003c/em\u003e(15-20)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn diagnosing and monitoring sepsis, C-reactive protein (CRP) serves as an acute-phase reactant that rises within two hours of infection onset and peaking within 48 hours. (21) It plays a role in defense mechanisms against inflammation and pathogen invasion. (22) However, CRP has low specificity for bacterial infections and also causes false positivity in non-infections inflammatory diseases. (23)\u003c/p\u003e\n\u003cp\u003eThis study focuses on identifying and comparing the bacteriological agents for early and late-onset neonatal sepsis and different conditions of birth causing neonatal sepsis and evaluating their antibiotic sensitivity pattern among neonates admitted to the NICU and neonatal wards of tertiary care hospitals in Nepal.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis was a prospective, cross-sectional study carried out from January 2021 to June 2021. A total of 120 blood samples were collected from the neonates who were suspected of sepsis and admitted to the NICU (14 beds) and neonate wards (70 beds) from birth to 28 days at Tribhuvan University Teaching Hospital (TUTH), an 850-bed tertiary care center of Nepal.\u003c/p\u003e \u003cp\u003eInclusion Criteria: Neonates admitted from birth to 28 days were included.\u003c/p\u003e \u003cp\u003eExclusion Criteria: Neonates with gross congenital malformation, severe cardiac abnormalities, and neonates taken against medical advice were excluded to minimize confounding factors and ensure an accurate assessment of sepsis-related outcomes.\u003c/p\u003e \u003cp\u003eEthical Clearance: Written informed consent was taken from every patient before enrollment.\u003c/p\u003e \u003cp\u003eSample Size: The sample size was calculated using Cochran's formula with a prevalence rate of 16.9%.(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:SS=\\frac{{z}^{2}\\left(p\\right)\\left(1-p\\right)}{{D}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSS\u0026thinsp;=\u0026thinsp;sample size\u003c/p\u003e \u003cp\u003ez\u0026thinsp;=\u0026thinsp;standard normal prevalence at 95% Confidence Interval\u0026thinsp;=\u0026thinsp;1.96\u003c/p\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;prevalence rate\u0026thinsp;=\u0026thinsp;0.169\u003c/p\u003e \u003cp\u003eD\u0026thinsp;=\u0026thinsp;Type I error\u0026thinsp;=\u0026thinsp;10% = 0.1\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equb\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:SS=\\frac{{\\left(1.96\\right)}^{2}.\\left(0.169\\right).\\left(1-0.169\\right)}{{\\left(0.1\\right)}^{2}}$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cem\u003eSS\u0026thinsp;=\u003c/em\u003e\u0026thinsp;53\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eSample Collection and Processing: The 1.5 ml of blood samples were collected using aseptic techniques to eliminate contamination. One ml was collected in a gel vial tube for CRP test and 1ml was inoculated into BacT/ALERT culture bottles (BiomerieuxUSA, BacT/ALERT 3D, US, Pioneering Diagnostics) transported, and incubated for seven days in BacT/ALERT (BiomerieuxUSA, BacT/ALERT, US, Pioneering Diagnostics) blood culture system. The samples were sub-cultured from growth-positive bottles on blood agar and MacConkey agar plates.\u003c/p\u003e \u003cp\u003eIdentification of Isolates: Bacterial identification was done by using standard microbiological techniques following the protocol of the American Society for Microbiology (ASM). Initially, gram staining of isolates was performed. Then, catalase and coagulase tests were done to differentiate \u003cem\u003eStaphylococcus aureus\u003c/em\u003e from other gram-positive cocci. For differentiating gram-negative bacteria catalase and oxidase tests were performed. Further biochemical tests were performed to differentiate gram-negative bacteria. The Triple Sugar Iron Agar (TSI), Sulphide Indole Motility (SIM), Simmons Citrate media, and Christensen's Urease media were used for biochemical testing. We also repeated cultures to eliminate contaminants and confirmed suspected contaminants.\u003c/p\u003e \u003cp\u003eAntibiotic Susceptibility Testing: The antibiotic susceptibility testing (AST) of isolated organisms was processed on Muller Hinton Agar (MHA) using the disc diffusion Kirby-Bauer method. The standard ATCC strains of \u003cem\u003eEscherichia coli\u003c/em\u003e (ATCC 25922) and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (ATCC 25923) was used to maintain quality control. The zone sizes were interpreted following the breakpoints guidelines of the Clinical and Laboratory Standards Institute (CLSI) M100: 2019 Performance Standards for Antimicrobial Susceptibility Testing. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eDetection of MDR: The isolates resistant to at least one agent in three or more antimicrobial categories were regarded as MDR. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eDetection of MRSA and MR-CoNS: Cefoxitin (30\u0026micro;g) was used to detect MRSA and MR-CoNS. \u003cem\u003eStaphylococcus aureus\u003c/em\u003e with a zone of inhibition\u0026thinsp;\u0026le;\u0026thinsp;21 mm were confirmed as MRSA, while CoNS with a zone of inhibition\u0026thinsp;\u0026le;\u0026thinsp;24 mm were confirmed as MR-CoNS. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eDetection of ESBL: For the detection of potential ESBL producers, Ceftriaxone (CTR, 30\u0026micro;g) was used. The isolates with \u0026le;\u0026thinsp;13 mm of diameter were further confirmed for ESBL producers. As a confirmatory test double disc synergy test using Ceftazidime (CAZ, 30\u0026micro;g), Cefepime (CPM, 30\u0026micro;g), and Amoxicillin-Clavulanate (AMC, 20 \u0026micro;g\u0026thinsp;+\u0026thinsp;10\u0026micro;g) was done. These were placed 20 mm apart, center to center, and incubated at 35\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003csup\u003e\u0026deg;\u003c/sup\u003eC for 16\u0026ndash;18 hours. The isolates that showed a cleared extension of the zone of inhibition around Ceftazidime and/or around Cefepime towards the disc containing clavulanate were confirmed as ESBL producers. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) Parallelly, for control of ESBL detection negative control (\u003cem\u003eEscherichia coli\u003c/em\u003e ATCC 25922) and positive control (\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e ATCC 700603) were also used. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eDetection of CRP: The latex agglutination slide test (PCR Slide, Giesse Diagnostics, Italy) was used for the qualitative detection of CRP in serum separated from blood samples collected from neonates. A CRP level greater than 5 mg/dl was considered the cut-off for a positive result. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eData Analysis: The collected data were entered and analyzed using SPSS 20.0. The chi-square test was performed for p-values with a level of significance of 95.0% (0.01) to show blood culture positivity, organism isolation, MDR association with different EONS, LONS, and different birth conditions, and CRP with blood culture. Microsoft Excel was used to prepare charts and tables.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cstrong\u003eDemographic Study\u003c/strong\u003e \u003cp\u003eA total of 120 blood samples were collected from neonates admitted to the NICU and Neonate wards with suspected sepsis, among which 82 (68.3%) were male and 38 (31.7%) were female. Out of 120 samples, 36 (30.0%) yielded positive blood cultures of which 11 (30.5%) were from males and 25 (69.5%) from females. According to the time of sepsis onset, 95 (79.2%) neonates had suspected EONS and 25 (20.8%) had suspected LONS, with 20 (55.5%) and 16 (44.5%) culture-positive cases respectively. Out of 120 suspected neonatal sepsis cases, 55 (45.8%) neonates were born by normal vaginal delivery, and the remaining 65 (54.2%) by C-section. A higher percentage of bacteriological culture confirmed sepsis was observed in neonates delivered by C-section (n\u0026thinsp;=\u0026thinsp;25, 69.5%) than by normal delivery (n\u0026thinsp;=\u0026thinsp;11, 30.5%). According to the term of delivery, pre-term (n\u0026thinsp;=\u0026thinsp;54, 45.0%) delivered neonates had a higher incidence of sepsis (n\u0026thinsp;=\u0026thinsp;23, 63.8%) compared to term (n\u0026thinsp;=\u0026thinsp;66, 55.0%) delivered neonates. The low birth weight (n\u0026thinsp;=\u0026thinsp;23, 63.8%) neonates had a higher percentage of sepsis compared to normal birth weight (n\u0026thinsp;=\u0026thinsp;13, 36.2%) neonates. A significant association was observed between different modes of delivery and blood culture results (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBlood Culture Positivity According to Different Conditions of Child Birth\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eConditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eBlood Culture (N\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive (n\u0026thinsp;=\u0026thinsp;36, 30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNegative (n\u0026thinsp;=\u0026thinsp;84, 70.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime of Sepsis Onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEONS\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;95, 79.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (55.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75 (89.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLONS\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;25, 20.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMode of Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal Delivery\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;55, 45.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (30.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44 (52.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCesarean Section\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;65, 54.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (69.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40 (47.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTerm of Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-term\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;54, 45.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31 (36.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;66, 55.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (36.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53 (63.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeight on Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Birth Weight\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;52, 43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal Birth Weight\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;68, 56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (36.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55 (65.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRelation between Different Birth Conditions\u003c/strong\u003e \u003cp\u003eIn this study, a significant association of EONS (n\u0026thinsp;=\u0026thinsp;20, 55.5%) and LONS (n\u0026thinsp;=\u0026thinsp;16, 44.5%) was observed with the mode of delivery (p-value\u0026thinsp;=\u0026thinsp;0.04). However, there was no significant association between EONS and LONS in terms of delivery and neonates' birth weight. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between mode of delivery, term of delivery, and birth weight with onset time of sepsis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eConditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTime of Sepsis Onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEONS\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;20, 55.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLONS\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16, 44.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMode of Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal Delivery\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;11, 30.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCesarean Section\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;25, 69.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (60.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (81.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTerm of Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-term\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;23, 63.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (60.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (68.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;13, 36.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (31.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeight on Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Birth Weight\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;23, 63.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (70.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal Birth Weight\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;13, 36.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (43.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIsolates Distribution According To Blood Culture\u003c/strong\u003e \u003cp\u003eOut of 120 samples collected for blood cultures, 36 (30.0%) samples showed growth of organisms, among which 15 (41.7%) were gram-positive and 21 (58.3%) were gram-negative organisms. Among all isolates, coagulase-negative \u003cem\u003eStaphylococcus\u003c/em\u003e (CoNS) (n\u0026thinsp;=\u0026thinsp;11, 30.6%) was predominant followed by \u003cem\u003eCitrobacter\u003c/em\u003e spp. (n\u0026thinsp;=\u0026thinsp;8, 22.2%). (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIsolates Distribution according to Different Birth Conditions\u003c/strong\u003e \u003cp\u003eThe EONS (n\u0026thinsp;=\u0026thinsp;20, 55.5%) rate was higher than LONS (n\u0026thinsp;=\u0026thinsp;16, 44.4%) in which CoNS and \u003cem\u003eCitrobacter freundii\u003c/em\u003e were isolated in higher numbers respectively. In the mode of delivery, neonatal births from C-section were more infected than neonates from normal delivery. The pre-term neonates and neonates with low birth weight were more prone to sepsis. The organisms isolated in sepsis had no significant association with any birth condition (p-value\u0026thinsp;\u0026gt;\u0026thinsp;0.01). (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Isolated Organisms According to Different Modes of Delivery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eConditions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCONS (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eACB\u003c/em\u003eC (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter lowffii\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eCitrobcter freundii\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime of Sepsis Onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEONS (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7 (35.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLONS (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5 (31.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMode of Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal Delivery (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (27.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCesarean Section (n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (32.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7 (28.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTerm of Delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-term (n-23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTerm (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeight at Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Birth Weight (n\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (21.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7 (30.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal Birth Weight (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePattern of AST in Gram-Positive Isolates\u003c/strong\u003e \u003cp\u003eThe \u003cem\u003eStaphylococcus aureus\u003c/em\u003e isolates showed 100.0% of sensitivity to Gentamicin, Amikacin, Vancomycin, Teicoplanin, and Chloramphenicol followed by 75.0% sensitivity to Cephalexin, Levofloxacin, Cloxacillin, Clindamycin, and Doxycycline. Additionally, Gentamicin, Amikacin, Vancomycin, and Teicoplanin exhibited 100% susceptibility, while Clindamycin showed 81.9% effectiveness against CoNS isolates. MRSA was detected in 25.0% of \u003cem\u003eStaphylococcus aureus\u003c/em\u003e isolates, and 27.3% of CoNS were identified as MR-CoNS. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAntibiotic Susceptibility Testing of Gram-Positive Isolates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDrugs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcu aureus\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCoNS (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePenicillin\u003c/b\u003e (10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCephalexin\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCotrimoxazole\u003c/b\u003e (25\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGentamicin\u003c/b\u003e (10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmikacin\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCiprofloxacin\u003c/b\u003e (5\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6 (54.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5 (45.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevofloxacin\u003c/b\u003e (5\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCloxacillin\u003c/b\u003e (5\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVancomycin\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTeicoplanin\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eErythromycin\u003c/b\u003e (15\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (36.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7 (63.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClindamycin\u003c/b\u003e (2\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (81.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2 (18.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDoxycycline\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChloramphenicol\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePattern of AST for Gram-Negative Isolates\u003c/strong\u003e \u003cp\u003eAmong all the gram-negative isolates, Imipenem, Meropenem, Polymyxin B, and Colistin (\u0026gt;\u0026thinsp;50.0%) were sensitive in a higher number of organisms, whereas the organisms were more resistant against Ampicillin, Ceftriaxone, and Ceftazidime (\u0026lt;\u0026thinsp;50.0%). (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAntibiotic Susceptibility Testing for Gram-Negative Isolates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDrugs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCitrobacter freundii\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter spp.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmpicillin\u003c/b\u003e (10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePiperacillin\u003c/b\u003e (100\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eND\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eND\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmoxicillin\u0026thinsp;+\u0026thinsp;Clavulunate\u003c/b\u003e (20\u0026micro;g\u0026thinsp;+\u0026thinsp;10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePiperacillin\u0026thinsp;+\u0026thinsp;Tazobactam\u003c/b\u003e (100\u0026micro;g\u0026thinsp;+\u0026thinsp;10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (87.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCeftriaxone\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCeftazidime\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCefepime\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCotrimoxazole\u003c/b\u003e (25\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmikacin\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (87.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGentamicin\u003c/b\u003e (10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCiprofloxacin\u003c/b\u003e (5\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevofloxacin\u003c/b\u003e (5\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eImipenem\u003c/b\u003e (10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMeropenem\u003c/b\u003e (10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDoxycycline\u003c/b\u003e (30\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePolymyxin B\u003c/b\u003e (300\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eColistin sulphate\u003c/b\u003e (10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmpicillin-Sulbactam\u003c/b\u003e (10\u0026micro;g\u0026thinsp;+\u0026thinsp;10\u0026micro;g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003e1\u003c/sup\u003e Not Done\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003e2\u003c/sup\u003e Not Recommended\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eThe pattern of MDR and ESBL Production among Isolates\u003c/strong\u003e \u003cp\u003eOut of a total of 36 isolates, 17 (47.2%) isolated organisms showed MDR on AST. The CoNS (n\u0026thinsp;=\u0026thinsp;5, 29.4%) has a higher percentage of MDR among all the isolates, followed by \u003cem\u003eCitrobacter freundii\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;4, 23.6%). The ESBL producer was found only in \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;1, 5.9%). (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMDR Isolates in Different Conditions of Delivery\u003c/strong\u003e \u003cp\u003eThe different conditions of delivery seemed to be insignificant to MDR isolates. (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMDR Isolates in Different Conditions of Delivery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConditions of Delivery\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTime of Sepsis Onset\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMode of Delivery\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTerm of Delivery\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eWeight at Birth\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEONS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLONS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC-Section\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNormal Delivery\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePre-term\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUnder Weight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNormal Weight\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMDR Isolates (N\u0026thinsp;=\u0026thinsp;17)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (41.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (58.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (76.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (76.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10 (58.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7 (41.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCRP in Different Conditions\u003c/strong\u003e \u003cp\u003eIn every sample collected for blood culture, qualitative CRP was also done. Almost every sample that developed positive culture later had positive CRP except one. However, CRP was found positive in 5 negative blood culture samples. CRR detection and blood culture were also associated with each other (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01). (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e \u003cstrong\u003ePredictive Outcome of CRP According to Blood Culture\u003c/strong\u003e \u003cp\u003eCRP test was done before the outcome of blood culture. According to this study, the sensitivity of the CRP test is 97.2% and its specificity is 94.0% with 95.0% accuracy. (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictive Outcome and Validity of CRP with Blood Culture\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97.2%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpecificity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePredictive Positive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePredictive Negative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAccuracy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eNeonatal sepsis remains one of the leading causes of neonatal morbidity and mortality, especially in developing countries like Nepal. Limited studies of neonatal sepsis associated with MDR and ESBL production are found in Nepal. This study was intended to determine the distribution of organisms associated with bacteriologically proven neonatal sepsis and the identification of MDR and ESBL isolates.\u003c/p\u003e \u003cp\u003eIn this study, about one-third of the neonates had microbiologically confirmed sepsis. This finding is consistent with the study by Shrestha et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), conducted at Nepal Medical College Teaching Hospital, Nepal which reported 30.8% of cases. This rate is also comparable with the rates reported in other developing countries like Bangladesh (34.88%) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), Uganda (37%) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), and Ethiopia (44.7%) (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). However, negative blood culture does not mean they do not have sepsis as sepsis can be caused due to anaerobes, viral, protozoal, and treponemal pathogens shown by a study by Shrestha et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) and Shehab et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). The lack of trained manpower, diagnostic tools, and laboratory equipment may be a possible reason for not finding every possible case of neonatal sepsis.\u003c/p\u003e \u003cp\u003eOur study aligns with the findings of Nagaveni et al., which conclude that neonatal sepsis is more common in males than females. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) Additionally, the incidence of EONS in our study is higher than that of LONS, consistent with a study from Nepal by Ansari et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) and from India by Rusia et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). However, our findings contradict those of Shaw et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) and Kayange et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), who reported a higher incidence of LONS compared to EONS. There is a significant association between EONS and LONS with bacterial culture (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting the variation in incidence may be affected by the global environment factors as well as maternal and neonatal conditions.\u003c/p\u003e \u003cp\u003eIn this study, it was found that 69.4% of neonates with bacteriologically proven sepsis were delivered by Cesarean section, and 30.6% of them were delivered by normal vaginal delivery showing that neonates born by cesarean section had 2.26 times more sepsis compared to those delivered by normal vaginal delivery. The rate of neonatal sepsis significantly varied with the mode of delivery (p-value\u0026thinsp;=\u0026thinsp;0.02\u003cb\u003e)\u003c/b\u003e. Another study from Ethiopia by Woldu et al. showed that the incidence of neonatal sepsis in those delivered by cesarean section was 6.2 times that of those delivered by normal vaginal delivery. (39) Neonates delivered by cesarean section are probably at risk for laceration from sharp instruments during the procedure. A fetal laceration is found to occur in about 0.1\u0026ndash;3.1% of cesarean section deliveries (40, 41) and this can be a possible route of entry of microorganisms leading to neonatal sepsis. Cesarean section delivery results in a longer hospital stay compared to vaginal delivery, which also increases the risk of neonatal sepsis. (42) The microbiota of infants delivered by Cesarean section were different as compared to normally delivered ones, which also raises the possibility of neonatal sepsis. (43)\u003c/p\u003e \u003cp\u003eOur study shows a significant correlation between neonatal weights during birth with neonatal sepsis (p-value\u0026thinsp;=\u0026thinsp;0.03). The neonates with low birth weight have almost twice more chance of developing neonatal sepsis than normal birth weight neonates. This study supports that birth weight is also one of the risk factors for developing neonatal sepsis. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eOur study shows a significant association between the development of EONS and LONS with mode of delivery (p-value 0.04), but not with other birth conditions. These findings are consistent with the study by Adatara et al., which also reported a statistically significant relationship between the time of sepsis onset and the mode of delivery. (44)\u003c/p\u003e \u003cp\u003eAmong the total blood culture isolates, 41.7% were gram-positive and 58.3% were gram-negative. Among gram-positive isolates, CoNS, and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e were isolated. While \u003cem\u003eCitrobacter freundii\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eAcinetobacter baumanii\u003c/em\u003e complex, and \u003cem\u003eAcinetobacter lowffii\u003c/em\u003e were isolated gram-negative organisms. Other studies from Nepal report \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, and CoNS as common isolates. (24, 45) The study by Jatsho et al. from Bhutan also reports the most common isolates as CoNS, followed by \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e and \u003cem\u003eAcinetobacter\u003c/em\u003e. (46)\u003c/p\u003e \u003cp\u003e \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and CoNS were highly resistant to Penicillin. In contrast, resistance to Cephalexin, Levofloxacin, Cloxacillin, Clindamycin, and Doxycycline was comparatively lower in both isolates. Both isolates were 100.0% susceptible to Gentamicin, Amikacin, Vancomycin, and Teicoplanin. Gentamicin (90% isolates) was found the most sensitive and ampicillin (76% isolates) was found to be the antibiotic least effective against \u003cem\u003eStaphylococcus aureus\u003c/em\u003e by another study. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) Higher percentage of MRSA (75.0%) and MR-CoNS (72.7%) were isolated in our study. The literature review of Huang et al. from China also showed the wide prevalence of MRSA and MR-CoNS in neonatal sepsis. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eOur study found most gram-negative organisms were highly resistant to Ampicillin and Piperacillin. The \u003cem\u003eCitrobacter freundii\u003c/em\u003e was highly susceptible to Imipenem, Meropenem, Polymyxin B, and Colistin sulfate followed by Piperacillin\u0026thinsp;+\u0026thinsp;Tazobactum and Amikacin. While \u003cem\u003eCitrobacter freundii was\u003c/em\u003e highly resistant to Amoxicillin\u0026thinsp;+\u0026thinsp;Clavulunate, Ceftriaxone, Ceftazidime, and Ampicillin-Sulbactum followed by Ciprofloxacin, Levofloxacin, and Doxycycline. The study of Yadav et al. in Nepal found that Ceftazidime and Amikacin were the most effective antibiotics against \u003cem\u003eCitrobacter\u003c/em\u003e spp. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn this study, 17 (47.2%) isolates out of 36 culture isolates were found to be MDR, out of which 7 (41.2%) were gram-positive and 10 (58.8%) were gram-negative. The only ESBL producer was \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;1, 5.9%) among all MDR isolates. The other study by Pokhrel et al. from Nepal showed MDR strains in their study to be 73.91% and MDR among gram-negatives and gram-positives was found to be 80.76% and 52.94% respectively. (45) This study showed that there was a high degree of antimicrobial-resistant bacteria causing neonatal sepsis, indicating that MDR and ESBL can be the rising emergence in neonate fatality.\u003c/p\u003e \u003cp\u003eAmong the MDR isolates, 7 were found in EONS and 10 were found in LONS. This result is consistent with the study by Mohsen et al. which also showed that MDR isolates were more in LONS than EONS. (47) Our study showed 13 (76.5%) isolates of MDR are present in C-section delivery and pre-term neonates each, and 10 (58.8%) in under-weight neonates at birth. However, no significant association was established between the MDR isolation and conditions of delivery in our study. This inconsistency may be attributed to the limited sample size or the influence of unmeasured confounding factors. It is also possible that local antimicrobial practices and infection control measures played a role in shaping the resistance patterns observed. These findings highlight the need for larger, multicenter studies to better understand the complex interplay between delivery conditions and the emergence of MDR pathogens in neonates.\u003c/p\u003e \u003cp\u003eCRP test has been widely used as screening tests for many inflammatory diseases caused by injury, infections, or chronic diseases. In this study, CRP was also performed in each sample received for blood culture. Among 120 samples, 40 blood samples were positive for CRP and 80 were negative. As a confirmatory test of sepsis, a result of blood culture was considered. Our study data showed that the sensitivity, specificity, PPV, NPV, and significant accuracy of the CRP test is 97.2%, 94.0%, 87.5%, 98.8%, and 95.0% respectively. The study of Morad et. al showed CRP has sensitivity, specificity, PPV, NPV, and significant accuracy of 89.5%, 66.7%, 92.5%, 60.0%, and 86.0% respectively. (48) Though CRP has higher sensitivity and specificity, it can't be used solely for sepsis confirmation. (49)\u003c/p\u003e \u003cp\u003eThis was a cross-sectional study conducted for six months, and the samples were only processed for aerobic bacteriology. The samples were not processed for anaerobic bacteriology, viral, and fungal cultures. This limitation may result in an incomplete understanding of the causative agents of neonatal sepsis, thereby affecting the accuracy and scope of the study\u0026rsquo;s findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study shows that gram-negative organisms were the predominant cause of neonatal sepsis, despite a higher prevalence of CoNS. The incidence of neonatal sepsis is increasing due to the emergence of MRSA, MR-CoNS, MDR, and ESBL. Our study shows EONS, C-section deliveries, and pre-term neonates, and under-weight neonates are more prone to neonatal sepsis. It is important to note that some neonates with culture-proven sepsis may have negative CRP results, highlighting the limitation of relying solely on CRP for diagnosis. However, due to the cross-sectional nature of the study and the exclusion of certain pathogens, the generalizability of these results should be interpreted with caution.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eASM: American Society for Microbiology\u003c/p\u003e \u003cp\u003eATCC: American Type Culture Collection\u003c/p\u003e \u003cp\u003eAST: Antimicrobial Susceptibility Test\u003c/p\u003e \u003cp\u003eCRP: C-reactive protein\u003c/p\u003e \u003cp\u003eCLSI: Clinical and Laboratory Standard Institute\u003c/p\u003e \u003cp\u003eEON: Early Onset Neonatal Sepsis\u003c/p\u003e \u003cp\u003eESBL: Extended Spectrum β-lactamase\u003c/p\u003e \u003cp\u003eLONS: Late Onset Neonatal Sepsis\u003c/p\u003e \u003cp\u003eMDR: Multidrug Resistance\u003c/p\u003e \u003cp\u003eMHA: Mueller Hinton Agar\u003c/p\u003e \u003cp\u003eMRSA: Methicillin Resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e \u003cp\u003eNICU: Neonatal Intensive Care Unit\u003c/p\u003e \u003cp\u003eSPSS: Statistical Package for Social Science\u003c/p\u003e \u003cp\u003eCoNS: Coagulase Negative Staphylococcus\u003c/p\u003e \u003cp\u003eCDC: Centre for Disease Control and Prevention\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted after obtaining ethical clearance from the Institutional Review Committee of the Institute of Medicine (Ref: 221 (6-11)E\u003csup\u003e2\u003c/sup\u003e/077/078).\u0026nbsp;Written verbal informed consent was taken from study participants and their visitors. Patients\u0026rsquo; details were kept confidential throughout the study period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe written verbal informed consent was obtained from all the study participants and their visitors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data generated during this study are presented in this paper. The primary raw data will be made available to interested researchers by the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declared no potential conflicts of interest concerning the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no financial support received in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026apos;s contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRabita Karanjit and Sangita Sharma: conceived and designed the experiments;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRabita Karanjit and Sangita Sharma: methodology and experimental design;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRabita Karanjit, Sunita Makaju, and Sangita Sharma: conduct research;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRabita Karanjit, Sagun Suwal, Sunita Makaju, Sujata Baidya, Sangita Sharma, Hari Prasad Kattel, and Shyam Kumar Mishra: manage, organize, maintain, analyze and interpret data;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSangita Sharma, Hari Prasad Kattel and Shyam Kumar Mishra: verify data and results;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSangita Sharma and Shyam Kumar Mishra: data curation;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSajal Twanabasu and Sagun Suwal: draft preparation;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSujata Baidya, Sagun Suwal, Sajal Twanabasu, Sangita Sharma, Shyam Kumar Mishra and Hari Prasad Kattel: review and editing;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRabita Karanjit, Sunita Makaju, and Sagun Suwal: visual elements preparation;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSangita Sharma, Shyam Kumar Mishra, and Hari Prasad Kattel: supervision.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are beholden to all the participants of this study. Our special thanks go to all the physicians and staff members of the neonatal ICU, laboratory staff, management, and officials of Tribhuvan University Teaching Hospital, Maharajgunj, Kathmandu for giving us the environment to carry out this research work. We would also like to thank the TUTH family for being supportive and courageous during the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSingh M, Deorari AK, Khajuria RC, Paul VK. Perinatal \u0026amp; neonatal mortality in a hospital. Indian J Med Res. 1991;94:1-5.\u003c/li\u003e\n\u003cli\u003eSingh M, Narang A, Bhakoo ON. Predictive perinatal score in the diagnosis of neonatal sepsis. J Trop Pediatr. 1994;40(6):365-8.\u003c/li\u003e\n\u003cli\u003eKlein JO. Bacteriology of neonatal sepsis. 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JNMA J Nepal Med Assoc. 2020;58(232):976-82.\u003c/li\u003e\n\u003cli\u003eAttia Hussein Mahmoud H, Parekh R, Dhandibhotla S, Sai T, Pradhan A, Alugula S, et al. Insight Into Neonatal Sepsis: An Overview. Cureus. 2023;15(9):e45530.\u003c/li\u003e\n\u003cli\u003eChaurasia S, Sivanandan S, Agarwal R, Ellis S, Sharland M, Sankar MJ. Neonatal sepsis in South Asia: huge burden and spiralling antimicrobial resistance. Bmj. 2019;364:k5314.\u003c/li\u003e\n\u003cli\u003eNDaHS. Nepal Demographic and Health Survey 2022: Key Indicators Report 2022 [Available from: https://mohp.gov.np/uploads/Resources/Nepal\u003cbr\u003e%20Demographic%20and%20Health%20Survey%202022%20Key%20Indicators%20Report.pdf.\u003c/li\u003e\n\u003cli\u003eShrestha RK, Rai SK, Khanal LK, Manda PK. Bacteriological study of neonatal sepsis and antibiotic susceptibility pattern of isolates in Kathmandu, Nepal. 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Role of C-reactive Protein as an Indicator for Determining the Outcome of Sepsis. Indian J Crit Care Med. 2019;23(1):11-4.\u003c/li\u003e\n\u003cli\u003eWu Y, Potempa LA, El Kebir D, Filep JG. C-reactive protein and inflammation: conformational changes affect function. Biol Chem. 2015;396(11):1181-97.\u003c/li\u003e\n\u003cli\u003eGuidelines CLSIC. 2019 CATALOG: clsi; 2019 [Available from: https://clsi.org/media/3266/catalog2019_web.pdf.\u003c/li\u003e\n\u003cli\u003eAhmed AS, Chowdhury MA, Hoque M, Darmstadt GL. Clinical and bacteriological profile of neonatal septicemia in a tertiary level pediatric hospital in Bangladesh. Indian Pediatr. 2002;39(11):1034-9.\u003c/li\u003e\n\u003cli\u003eMugalu J, Nakakeeto MK, Kiguli S, Kaddu-Mulindwa DH. Aetiology, risk factors and immediate outcome of bacteriologically confirmed neonatal septicaemia in Mulago hospital, Uganda. Afr Health Sci. 2006;6(2):120-6.\u003c/li\u003e\n\u003cli\u003eShitaye D, Asrat D, Woldeamanuel Y, Worku B. Risk factors and etiology of neonatal sepsis in Tikur Anbessa University Hospital, Ethiopia. Ethiop Med J. 2010;48(1):11-21.\u003c/li\u003e\n\u003cli\u003eShrestha P, Das BK, Bhatta N, Jha DK, Setia A, Tiwari A. Clinical and Bacteriological Profiles of Blood Culture Positive Sepsis in Newborns. Journal of Nepal Paediatric Society. 2009;27.\u003c/li\u003e\n\u003cli\u003eShehab El-Din EMR, El-Sokkary MMA, Bassiouny MR, Hassan R. Epidemiology of neonatal sepsis and implicated pathogens: a study from Egypt. BioMed research international. 2015;2015.\u003c/li\u003e\n\u003cli\u003eP N. CLINICAL PROFILE OF NEONATES ADMITTED WITH SEPSIS \u0026ndash; A TERTIARY CARE EXPERIENCE. IOSR Journal of Dental and Medical Sciences. 2016.\u003c/li\u003e\n\u003cli\u003eYadav NS, Sharma S, Chaudhary DK, Panthi P, Pokhrel P, Shrestha A, et al. Bacteriological profile of neonatal sepsis and antibiotic susceptibility pattern of isolates admitted at Kanti Children\u0026apos;s Hospital, Kathmandu, Nepal. BMC Res Notes. 2018;11(1):301.\u003c/li\u003e\n\u003cli\u003eAnsari S, Nepal HP, Gautam R, Shrestha S, Neopane P, Chapagain ML. Neonatal Septicemia in Nepal: Early-Onset versus Late-Onset. Int J Pediatr. 2015;2015:379806.\u003c/li\u003e\n\u003cli\u003eVarsha, Rusia U, Sikka M, Faridi MM, Madan N. Validity of hematologic parameters in identification of early and late onset neonatal infection. Indian J Pathol Microbiol. 2003;46(4):565-8.\u003c/li\u003e\n\u003cli\u003eShaw CK, Shaw P, Thapalial A. Neonatal sepsis bacterial isolates and antibiotic susceptibility patterns at a NICU in a tertiary care hospital in western Nepal: a retrospective analysis. Kathmandu Univ Med J (KUMJ). 2007;5(2):153-60.\u003c/li\u003e\n\u003cli\u003eKayange N, Kamugisha E, Mwizamholya DL, Jeremiah S, Mshana SE. Predictors of positive blood culture and deaths among neonates with suspected neonatal sepsis in a tertiary hospital, Mwanza-Tanzania. BMC Pediatr. 2010;10:39.\u003c/li\u003e\n\u003cli\u003eWoldu MA, Guta MB, Lenjisa JL, Tegegne GT, Tesafye G, Dinsa H. Assessment of the incidence of neonatal sepsis, its risk factors, antimicrobials use and clinical outcomes in Bishoftu General Hospital, neonatal intensive care unit, Debrezeit-Ethiopia. Int J Contemp Pediatrics. 2017;1(3):135-41.\u003c/li\u003e\n\u003cli\u003eOkaro J, Anya S. Accidental incision of the fetus at caesarian section. Nigerian journal of medicine: journal of the National Association of Resident Doctors of Nigeria. 2004;13(1):56-8.\u003c/li\u003e\n\u003cli\u003eDessole S, Cosmi E, Balata A, Uras L, Caserta D, Capobianco G, et al. Accidental fetal lacerations during cesarean delivery: experience in an Italian level III university hospital. American Journal of Obstetrics and Gynecology. 2004;191(5):1673-7.\u003c/li\u003e\n\u003cli\u003eAdatara P, Afaya A, Salia SM, Afaya RA, Konlan KD, Agyabeng-Fandoh E, et al. Risk Factors Associated with Neonatal Sepsis: A Case Study at a Specialist Hospital in Ghana. The Scientific World Journal. 2019;2019:9369051.\u003c/li\u003e\n\u003cli\u003ePokhrel B, Koirala T, Shah G, Joshi S, Baral P. Bacteriological profile and antibiotic susceptibility of neonatal sepsis in neonatal intensive care unit of a tertiary hospital in Nepal. BMC Pediatr. 2018;18(1):208.\u003c/li\u003e\n\u003cli\u003eJatsho J, Nishizawa Y, Pelzom D, Sharma R. Clinical and Bacteriological Profile of Neonatal Sepsis: A Prospective Hospital-Based Study. International Journal of Pediatrics. 2020;2020(1):1835945.\u003c/li\u003e\n\u003cli\u003eMohsen L, Ramy N, Saied D, Akmal D, Salama N, Abdel Haleim MM, et al. Emerging antimicrobial resistance in early and late-onset neonatal sepsis. Antimicrobial Resistance \u0026amp; Infection Control. 2017;6(1):63.\u003c/li\u003e\n\u003cli\u003eMorad EA, Rabie RA, Almalky MA, Gebriel MG. Evaluation of Procalcitonin, C-Reactive Protein, and Interleukin-6 as Early Markers for Diagnosis of Neonatal Sepsis. Int J Microbiol. 2020;2020:8889086.\u003c/li\u003e\n\u003cli\u003eHisamuddin E, Hisam A, Wahid S, Raza G. Validity of C-reactive protein (CRP) for diagnosis of neonatal sepsis. Pak J Med Sci. 2015;31(3):527-31.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Neonatal sepsis, Gram-positive organisms, Gram-negative organisms, Normal delivery, Cesarean section, Multidrug resistance, C-reactive protein","lastPublishedDoi":"10.21203/rs.3.rs-5845225/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5845225/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNeonatal sepsis is one of the most common causes of neonatal mortality in developing countries like Nepal, ranking third after premature birth and birth asphyxia. This study intended to study the microbial etiology and antimicrobial susceptibility pattern of neonatal sepsis and its association with different birth conditions and C-reactive protein (CRP).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood samples were collected aseptically from 120 neonates suspected of sepsis, admitted to the Neonatal Intensive Care Unit (NICU) and Neonate wards of Tribhuvan University Teaching Hospital, Kathmandu, Nepal, and processed according to the protocol of the American Society for Microbiology (ASM). For antimicrobial susceptibility testing, the standard disc diffusion technique of the Kirby-Bauer method recommended by the Clinical and Laboratory Standards Institute (CLSI) 2019 was followed. Along with blood culture, a C-reactive protein (CRP) test was also carried out from each blood sample.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOut of 120 blood cultures, 36 (30.0%) yielded microbial growth, 20 (55.5%) in the early-onset neonatal sepsis, and 16 (44.5%) in the late-onset neonatal sepsis. Among 36 blood culture-positive neonatal sepsis, 25 (69.5%) were born through normal delivery, 11 (30.5%) via Cesarean section (C-section); 23 (63.9%) were pre-term delivered neonates, 13 (36.1%) were termed delivered neonates; 23 (63.9%) were low birth weight neonates and 13 (36.1%) were normal birth weight. Among 36 isolates, 15 (41.7%) were gram-positive and 21 (58.3%) were gram-negative organisms. A higher percentage of Coagulase-negative \u003cem\u003eStaphylococcus \u003c/em\u003e(n=5, 35.0%) was isolated in EONS, whereas \u003cem\u003eCitrobacter freundii \u003c/em\u003e(n=5, 31.2%) was isolated in a higher percentage in LONS. Coagulase-negative \u003cem\u003eStaphylococcus\u003c/em\u003e (n=11, 30.6%) were isolated in higher percentages followed by \u003cem\u003eCitrobacter freundii \u003c/em\u003e(n=8, 22.2%), \u003cem\u003eKlebsiella pneumoniae \u003c/em\u003e(n=6, 16.7%), \u003cem\u003eAcinetobacter baumanii \u003c/em\u003ecomplex (n=5, 13.9%), \u003cem\u003eStaphylococcus aureus \u003c/em\u003e(n=4, 11.1%), \u003cem\u003eAcinetobacter lwoffii \u003c/em\u003e(n=1, 2.8%)\u003cem\u003e, \u003c/em\u003eand\u003cem\u003e Pseudomonas aeruginosa \u003c/em\u003e(n=1, 2.8%). Seventeen organisms (47.2%) showed multi-drug resistance of which one was an extended-spectrum beta-lactamase (ESBL) producer. A total of 40 blood samples (33.3%) tested positive for CRP, of which 35 had positive blood culture results. Based on blood culture results, CRP's sensitivity, specificity, and accuracy in this study were 97.2%, 94.0%, and 95.0% respectively which help to rule out the true infection and potential contamination of Coagulase-negative \u003cem\u003eStaphylococcus \u003c/em\u003ein neonatal sepsis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGram-positive bacteria\u003cstrong\u003e s\u003c/strong\u003etood out as the major causative agent of neonatal sepsis. MDR and ESBL were also prevalent in neonatal sepsis.\u003c/p\u003e","manuscriptTitle":"Bacteriological Profile of Early Versus Late-onset Neonatal Sepsis at Tertiary Care Hospital in Nepal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 09:38:57","doi":"10.21203/rs.3.rs-5845225/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-30T12:30:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-05T09:40:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-01T19:31:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-25T13:43:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"319041343618722959053620767655648801507","date":"2025-04-25T06:47:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"160238786474864677963718272520138166708","date":"2025-04-22T23:12:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334673175416876269537771439231069981372","date":"2025-04-22T18:20:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-22T09:24:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-22T01:35:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-04-21T17:03:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5aad8150-9bda-4466-b86a-c72d68134572","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-26T16:04:24+00:00","versionOfRecord":{"articleIdentity":"rs-5845225","link":"https://doi.org/10.1186/s12879-026-12645-8","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2026-01-23 15:59:13","publishedOnDateReadable":"January 23rd, 2026"},"versionCreatedAt":"2025-05-06 09:38:57","video":"","vorDoi":"10.1186/s12879-026-12645-8","vorDoiUrl":"https://doi.org/10.1186/s12879-026-12645-8","workflowStages":[]},"version":"v1","identity":"rs-5845225","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5845225","identity":"rs-5845225","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}