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Bacteriological Profile of Endotracheal Aspirates and their Antibiotic Susceptibility Pattern.


Ventilator associated pneumonia (VAP) is a globally known notorious nosocomial infection that occurs more than 48 hours after a patient begins mechanical ventilation (MV)making recovery more difficult for patients who are already critically ill. (1) Early onset VAP is usually less severe, associated with a better prognosis, and is more likely to be caused by antibiotic-sensitive bacteria. Late-onset VAP, is usually caused by multidrug resistant (MDR) pathogens and is associated with increased morbidity and mortality (2,3). VAP results from microaspiration, which is primary route of bacterial entry into respiratory tract' The ET tube acts as an obstacle to host defences by inhibiting the action of cilia, swallowing, and spontaneous coughing by the patients. Risk factors that are associated with increased incidence of VAP are body position, state of consciousness, enteral nutrition, prior exposure to antibiotics, use of a nasotracheal tube and pre-existing conditions such as acute respiratory distress syndrome (4).

Typically, diagnosis includes clinical, radiologic and microbiologic evidence of infection. However, the exact criteria for diagnosis varies widely among institutions and thus results in a wide range of reported VAP mortality rates, which is stated to be anywhere from 0-76% (5,6,7). Many studies from India have investigated the causative organisms of VAP. Pseudomonas species, Acinetobacter species, Escherichia coli, Klebsiella pneumoniae and Staphylococcus aureus are the common pathogens with varying prevalence and quite often being MDR (6,8,9). Therefore, the local microbial flora causing VAP needs to be studied and an appropriate therapy based on the early ET aspirate report can reduce the mortality and cost in managing this group of patients Aim

In view of increasing incidence of VAP and MDR nature of pathogens in our hospital, this study was taken up to detect the bacteriological profile and sensitivity pattern of isolates from Endotracheal aspirates


The present study was carried out in the Department of Microbiology, JSS Hospital, Mysore, Karnataka, for a period of 1 year from January 2017 to December 2017. This was a prospective study. ET aspirates sent from various intensive care units sent to Microbiology laboratory formed the material of our study

Bacterial identification and isolation

The ET samples received in the Microbiology lab were subjected to microscopy and culture. Gram stain of Lower respiratory tract secretions is an immediate procedure that can guide management and it has a reasonable correlation with culture results Semiquantitative culture was done on blood agar and MacConkey agar and incubated overnight at 37[degrees]C for 24 to 48 hrs for bacterial growth and isolation. The isolated organisms were processed with Vitek 2 systems for identification as well as Antibiotic susceptibility testing. Colony count of 10 6 CFUml or more was considered significant for VAP . ET aspirates yielding growth between 10 2 to 10 6 CFU/ ml, whose microscopy revealed moderate to plenty of inflammatory cells were also processed.


A total number of 1432 samples were received in the lab for ET aspirate culture. Among these 1432 samples, 1055 showed growth ranging from [10.sup.2] to [10.sup.6] CFU/ml or more, 124 had no growth at all and 253 had no significant growth (<102 CFU/ml) Among 1055 bacterial growth isolates, 377 isolates showed growth 10 6 CFUml or more which is considered significant for VAP and 731 isolates ranging [10.sup.2] to [10.sup.6] CFU/ml.

Out of 1055 isolates, 1023 were Gram negative bacteria and 32 were Gram positive cocci. Out of 1023 GNB, 428 were Acinetobacter species,284 were Klebsiella species,225 were Pseudomonas species, 29 were E.coli, 3 Proteus spp, 6 Citrobacter spp, 6 Enterobacter spp, 20 Serratia, 14 Stenotrophomonas, 6 Burkholderia spp and 2 Morganella spp. Acinetobacter baumanii, Klebsiella pneumoniae and Pseudomonas aeruginosa were the most common isolates in our study. Amongst the 32 gram positive isolates 25 were Staphylococcus aureus, 3 Streptococcus pneumoniae, 2 Beta hemolytic Streptococci and 2 coagulase negative Staphylococcus.

Majority of Enterobacteriaceae apart from Klebsiella isolates were sensitive to Imipenem, Ertapenem, Meropenem, Gentamicin, Amikacin, Tigecycline, Colistin, Cotrimoxazole, Ampicillin. Among the 25 Staphylococcus aureus, 4 were Methicillin resistant Staphylococcus aureus sensitive Vancomycin and Linezolid.


Prompt identification of organisms from ET aspirates in ventilated patients and accurate selection of antimicrobial agents, based on MIC represent important clinical goals in prevention of VAP. Sound knowledge of susceptibility pattern of the locally prevalent pathogens is necessary for choosing the appropriate antibiotics.

In our study, overall, Gram-negative bacilli predominated over Gram-positive cocci. Acinetobacter spp, Klebsiella spp followed by Pseudomonas were the most common isolates identified. Other significant Gram negative isolates were E.coli, Serratia, Stenotrophomonas, Enterobacter, Citrobacter, Proteus and Burkholderia. Among Gram positive organisms Staphylococcus aureus was most common. The antibiogram pattern of isolates showed that Maximum resistance of Acinetobacter spp and Pseudomonas were seen in Aztreonam, Cefipime, Doripenem, Imipenem, Ciprofloxacin, Piperacillin/ Tazobactum. Maximum sensitivity was observed with Colistin, Tigecycline and Minocycline. Our findings were similar to the other studies (6,7,8,9)

In last two decades, Gram negative bacteria have become important nosocomial pathogens throughout the world and is a leading problem in treatment owing to its multidrug resistance. Colistin, which is an old antimicrobial agent, is very active against these. Susceptibility to Colistin was reported as 97.9-100% in various studies. There was least resistance to Colistin in our study. It appeared to be a good option apart from Tigecycline, in the treatment of VAP developed with MDR pathogens.


We conclude that VAP in mechanically ventilated patients is on rise and has been continually associated with indiscriminate and irrational use of antibiotics which contribute to emergence of drug resistant strains. Knowledge of their causative microbial flora in a local setting along with information on the susceptibility patterns will help in selection of the appropriate antibiotic for therapeutic use and a better outcome. It is clear that Tigecycline and Colistin become the last resort antibiotics in most cases. Within no time in future, we can expect resistance to these antibiotics also making us reach the dead end. Hence, resistance rates should be pursued closely. Newer alternative drugs revealing promising results to solve the problem is the need of the hour. 10.22207/JPAM.12.4.69


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Ranjitha Shankare Gowda, Sowmya G.S. *, Pavithra N., Raghavendra Rao M., Krishna Karthik M. and Satya Sai B.

Department of Microbiology, JSS Medical College, JSSAHER, Mysore - 570 015, India.

* Correspondence:; +91-9886686854

(Received: 15 August 2018; accepted: 09 October 2018)
Table 1. Distribution of microbial isolates in colony forming
units per ml

                     [10.sup.2]   [10.sup.3]   [10.sup.4]

Acinetobacter            26           57           23
Klebsiella               19           32           20
Pseudomonas              10           27           9
E.coli                   2            2            2
Proteus                  0            0            0
Citrobacter              0            3            1
Enterobacter             0            0            2
Serratia                 2            1            2
Stenotrophomonas         1            2            4
Burkholderia             0            0            0
Morganella               0            1            0
S.aureus                 0            0            8
Coagulase negative       2            5            0

                     [10.sup.5]   [10.sup.6] or more

Acinetobacter           192              130
Klebsiella              136               77
Pseudomonas             117               62
E.coli                   12               11
Proteus                  0                3
Citrobacter              2                0
Enterobacter             3                1
Serratia                 10               5
Stenotrophomonas         4                3
Burkholderia             3                3
Morganella               0                1
S.aureus                 13               4
Coagulase negative       0                0

Table 2. Antibiotic Resistance pattern of Acinetobacter

Antibiotics               Sensitive     Intermediate   Resistant

Piperacillin/Tazobactum   33(7%)        3(0.7%)        392(92%)
Ceftazidine               18(4%)        20(4.6%)       390(92%)
Cefoperazone/Sulbactum    100(23%)      66(15%)        262(62%)
Cefepime                  31(7.2%)      14(3.2%)       383(89.4%)
Aztreonam                 10(2.0%)      5(1.16%)       413(95%)
Doripenem                 37(8.64%)                    391(92%)
Imipenem                  34(7.94%)     8(1.86%)       386(90.1%)
Meropenem                 39(9.11%)     8(1.86%)       381(89.01%)
Amikacin                  17(3.97%)     1(0.23%)       410(95.79%)
Gentamicin                78(18.22%)    32(7.4%)       318(74%)
Ciprofloxacin             30(7.9%)      12(2.80%)      386(90%)
Levofloxacin              32(7.4%)      52(12.14%)     344(80.3%)
Minocycline               242(56.54%)   46(10.74%)     140(32.7%)
Tigecycline               346(80.84%)   75(17.52%)     7(1.63%)
Colistin                  412(96.26%)                  16(3.7%)
Cotrimoxazole             69(16.12%)                   359(84%)

Table 3. showing Antibiotic resistance pattern of Pseudomonas

Antibiotics                   Sensitive     Intermediate   Resistant

Ticarcillin/Clavulinic acid   72(32%)       59(26.22%)     94(42.22%)
Piperacillin/Tazobactum       110(48.88%)   25(11.11%)     90(40%)
Ceftazidine                   125(55.55%)   20(8.88%)      80(35.55%)
Cefoperazone/ Sulbactum       127(56.44%)   49(21.77%)     49(21.77%)
Cefepime                      119(52.8%)    20(8.88%)      86(38.22%)
Aztreonam                     81(36%)       59(26.22%)     85(37.77%)
Doripenem                     132(58.66%)   3(1.33%)       90(40%)
Imipenem                      136(60.4%)    0(0%)          89(39.5%)
Meropenem                     126(56%)      13(5.7%)       86(38.22%)
Amikacin                      150(66.6%)    71(31.5%)      4(1.7%)
Gentamicin                    119(52.88%)   3(1.33%)       32(14.22%)
Ciprofloxacin                 118(52.44%)   13(5.77%)      94(41.77%)
Levofloxacin                  121(53.77%)   9(4%)          95(42.22%)
Colistin                      206(91.55%)   2(0.8%)        17(7.55%)

Table 4. Antibiotic resistance pattern of Klebsiella

Antibiotics               Sensitive     Intermediate   Resistant

Amoxyclav                 41(14.43%)    44(15.49%)     199(70.07%)
Piperacillin/Tazobactum   48(16.9%)     10(3.5%)       226(79.5%)
Cefuroxime                43(15%)       6(2.11%)       235(82.7%)
Cefuroxime axetil         48(16.9%)     5(1.76%)       231(81.3%)
Cefoperazone/ Sulbactum   77(21%)       3(1%)          204(71.83%)
Cefipime                  49(17%)       13(4.57%)      222(78.3%)
Ertapenem                 98(34.5%)     13(4.57%)      173(60.91%)
Nalidixic acid            74(26.05%)    16(5.63%)      194(68%)
Imipenem                  119(41.90%)   63(22.18%)     102(35.91%)
Meropenem                 84(29.57%)    10(3.52%)      190(66.90%)
Amikacin                  169(59.5%)    40(14.08%)     75(26.40%)
Gentamicin                120(42.2%)    6(2.11%)       158(55.63%)
Ciprofloxacin             83(29.22%)    24(8.45%)      177(62.32%)
Tigecycline               180(63.3%)    64(22.53%)     40(14%)
Colistin                  270(95%)      1(0.35%)       13(4.57%)
Cotrimaxozole             102(35.9%)    2(0.70%)       180(63.38%)
Ceftriaxone               40(14.08%)    2(0.70%)       242(85.21%)

Table 5. Range of Values of MIC of Tigecycline and Colistin for most
frequent MDR isolates.

Oraganisms         Sensitive      Intermediate   Resistant
                [less than or         >2-6         >8-16
                equal to] 0.5-2

Acinetobacter         346              75            7
Klebsiella            180              64           40
Pseudomonas                           206            2

Oraganisms         Sensitive      Intermediate   Resistant
                 [less than or        >2-6         >8-16
                equal to] 0.5-2

Acinetobacter         412              0            16
Klebsiella            270              1            13
Pseudomonas           17
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Author:Gowda, Ranjitha Shankare; G.S., Sowmya; N., Pavithra; M., Raghavendra Rao; M., Krishna Karthik; B.,
Publication:Journal of Pure and Applied Microbiology
Article Type:Report
Date:Dec 1, 2018
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