Abstract
Background
Presently, many laboratories are equipped with automated system for antimicrobial susceptibility testing (AST) for minimum inhibitory concentration-based reporting which enables the clinician to choose the right antimicrobial for timely treatment of sepsis. The study aimed to assess performance of direct AST from blood culture positive broth using automated AST system for accuracy and time taken to release the report.
Materials and methods
The present study conducted in a 25-bedded ICU in North India for 12 months. Single morphotype of bacteria on gram stain from positively flagged blood culture bottles were included, which was directly identified (using an in-house protocol) with MALDI-TOF-MS from positive blood culture broths. DAST was carried out from 200 such blood culture broths and results were compared with reference AST (RAST) which was also done using VITEK-2 using overnight grown bacterial colonies as per standard protocol.
Results
Among 60 isolates of Enterobacterales, 99% categorical agreement for both E. coli and K. pneumoniae observed by two methods were tested for AST. Among non-fermenters, Pseudomonas aeruginosa showed a categorical agreement of 99.6%, as compared with Acinetobacter spp. and exotic GNBs, which showed 95–96% agreement. A significant difference of 18–24 hours was noted in time to release the report between DAST and RAST, for GNB and GPC both.
Conclusion
Direct AST from positive flagged blood culture bottles can significantly reduce the time to release the bacterial susceptibility report by up to 24 hours, at the same time maintaining the accuracy.
How to cite this article
Singh V, Agarwal J, Nath SS, Sharma A. Evaluation of Direct Antimicrobial Susceptibility Testing from Positive Flagged Blood Cultures in Sepsis Patients. Indian J Crit Care Med 2024;28(4):387–392.
Keywords: Categorical agreement, Direct antimicrobial susceptibility testing, Enterobacterales, Essential agreement, Flagged blood culture, Gram-positive bacteria, Non-fermenters, Time to release report
Highlights
Timely reporting of antimicrobial therapy in sepsis patients plays a pivotal role in reducing mortality and morbidity. Direct antimicrobial susceptibility testing (DAST) protocol exhibited a significantly lower time to report when compared with reference AST (RAST). It is worth noting that there was less processing time substantially in the new protocol, leading to earlier availability of final result approximately 1 day earlier than usual.
Introduction
Bloodstream infections (BSIs) are potentially life-threatening medical emergencies that are associated with significant morbidity and mortality globally.1 Worldwide more than 3 lakh cases of sepsis occur annually, with mortality rates varying from 17.5 to 50% in different countries.2–6 The recommended procedure is culture of causative organism from paired blood samples for diagnosis of BSI.2 Surviving sepsis campaign of 2021 emphasizes the importance of paired blood culture, early diagnosis, and targeting microorganism-specific antimicrobial therapy at the earliest possible time. However, the conventional method of blood culture with a further 48 hours for AST after being positive prolongs laboratory turnaround time (TAT). With the availability of an automated blood culture system for sepsis patients, the duration required for positive blood culture containing microorganisms has decreased by 24–48 hours; however, AST still takes a further 48 hours and includes subculture from blood bottles and then targeted AST plate incubation and interpretation.3,4 From clinical acumen and perspective, early determination of antimicrobials to which organism is sensitive helps in judicious use of antibiotics which in turn plays a pivotal role in saving lives. There is an increase in mortality by 7.6% with every hour of delay in determining rapid diagnosis and initiating appropriate antimicrobial agents for BSIs.5
Prolonged empirical therapy, because of delayed MIC-based AST reports, has been blamed as a significant barrier to successful antibiotic stewardship programs. Moreover, it was also shown that when MIC-based reports were made available to the intensivists earlier, it was possible to successfully control and reverse the growing menace of antimicrobial resistance (AMR) in bacteria and also reduce the volume of antibiotics consumed.7
Performing DAST from flagged positive broths of blood culture can expedite AST by at least 24 hours.6,8 Since 2010, many studies have aimed to optimize DAST from blood cultures using conventional Kirby Bauer disc diffusion and automated testing.6,8–11 However, many studies reported mixed results for directly performing disc diffusion from broth.9,12 In the present study, we have tried to standardize the DAST from positive broths of blood culture bottle using automated method for different microbial pathogens and assess its impact on time to generate report, errors associated with the method adopted and technical ease of carrying out the DAST procedure.
Materials and Methods
This prospective study was performed at a superspeciality public sector 1,000-beded hospital (with 25-bed intensive care unit) in North India, from February 2022 to January 2023. The study was intramurally funded and ethically approved by Institutional Ethics Committee (Dr. RMLIMS/IEC no.173/22). All positive flagged blood cultures (BACT/ALERT®BioMérieux, Marcyl'Etoile, France; aerobic and anaerobic) from patients admitted to ICU with suspicion of BSI were subjected to Gram staining. Blood cultures showing single type of morphology were further processed by an in-house protocol (details in Supplementary file), which included three steps centrifugation to obtain a pellet for bacterial identification by MALDI-TOF-MS (BioMérieux, Marcy-l'Etoile, France). After identification, appropriate AST cards (for GNB fermenters AST-405; GNB non-fermenters AST-406 and GPC AST-P628) were used for DAST using VITEK-2 system (BioMérieux, Marcy-l'Etoile, France). Direct antimicrobial susceptibility testing was compared with reference antimicrobial susceptibility testing (RAST) that included processing of overnight subculture from positively flagged blood culture broths on commonly used laboratory media blood agar and MacConkey agar to obtain bacterial colonies after overnight incubation, which were then identified using automated identification system MALDI-TOF-MS and AST using the automated system as per the manufacturer's protocol.
Positive blood culture broths that appeared polymicrobial on Gram staining, repeat isolate from the same patient and positive blood cultures showing contaminants such as diphtheroids and micrococci were excluded from the study. Considering confidence level of 95% (Z score = 1.96), and the detection of DAST from positive blood culture broth in a previous study sample size was calculated as 236.10
According to ISO 20776–2:2019 guidelines, categorical and essential agreement expression was used for comparison between DAST performance with RAST.12 Whenever a novel test procedure (DAST) yields similar sensitivity to the RAST method, it was said to be in agreement. The disagreement was categorized into minor error (mE), major error (ME), and very major error (VME). When DAST is intermediate and RAST is susceptible or resistant, it is referred as mE. When RAST yields a resistant category and DAST reports susceptible category, this type of error is known as VME. When RAST result is susceptible and DAST shows resistant result, it is called as ME. Essential agreement for an isolate–drug combination means that minimum inhibitory concentration (MICs obtained for the DAST was within ± 2-fold dilution of the RAST method. Any new method of AST is acceptable and is said to give “excellent agreement” when the selection criteria proposed by Jorgensen are met, which is <3% VME and <7% major and minor errors in combination, compared with the reference AST method.13 Data collected from DAST and RAST were entered into a Microsoft Excel and SPSS software version 22 was used for data analysis.
Results
Positive flagged 180 blood cultures in the study period were analyzed, which involved 60 isolates of Enterobacterales family (Klebsiella pneumoniae 41; Escherichia coli 19), 60 non-fermenters (Pseudomonas aeruginosa 35; Acinetobacter baumannii 25), 15 exotic GNBs (distribution enclosed in Supplementary file) and 65 Gram-positive cocci (Staphylococcus spp. 49; Enterococcus spp. 16). There was 100% concordance in identification of bacterial isolates when MALDI TOF-MS was performed from positive blood culture bottle broth and bacterial colony from overnight subculture plate.
DAST Result for Gram-negative Rods
Table 1 demonstrates performance of DAST compared with reference AST method in GNB. Klebsiella pneumoniae showed a categorical agreement of 99.2%, Escherichia coli: 99.1%, and among non-fermenters Pseudomonas aeruginosa: 99.6% and Acinetobacter baumannii: 96.8%. Assessment of categorical disagreement revealed, mE and ME were highest in A. baumannii (1.3 and 1.9%), while VME was only observed in exotic GNBs like Burkholderia spp, Elizabethkingiae meningoseptica (1.7%). Essential agreement was 98.7–99.6% for four common GNBs isolated in our study.
Table 1.
Performance of DAST compared with reference AST method test by VITEK-2 system
|
Organisms and antibiotic tested (n × Ab = N) |
Categorical agreement, n (%) | Categorical disagreement, n (%) among isolate–antibiotic combinations tested | Essential agreement | ||||
|---|---|---|---|---|---|---|---|
| Minor error | Major error | Very major error | Total | Agreed | Disagreed | ||
|
Escherichia coli
(19 × 18 = 342) |
339 (99.1%) | 0 (0%) | 3 (0.9%) | 0 (0%) | 3 (0.9%) | 340 (99.4%) | 02 (0.6%) |
|
Klebsiella pneumoniae (41 × 18 = 738) |
732 (99.2%) | 1 (0.2%) | 4 (0.5%) | 0 (0%) | 6 (0.78%) | 735 (99.6%) | 03 (0.4%) |
|
Acinetobacter baumannii
(25 × 15 = 375) |
363 (96.8%) | 5 (1.3%) | 7 (1.9%) | 0 (0%) | 12 (3.2%) | 370 (98.7%) | 05 (1.3%) |
|
Pseudomonas aeruginosa
(35 × 15 = 525) |
523 (99.6%) | 0 (0%) | 2 (0.4%) | 0 (0%) | 2 (0.4%) | 524 (99.8%) | 01 (0.2%) |
| Exotic GNB (15 × 15 = 225) |
215 (95.6%) | 0 (0%) | 6 (2.7%) | 4 (1.7%) | 10 (4.4%) | 221 (98.2%) | 04 (1.8%) |
Among Enterobacterales, antimicrobials present in the VITEK-2 panel in DAST protocol showed an excellent categorical agreement >99%, except imipenem (90%), meropenem (98.3%) and gentamicin (98.3%). Categorical disagreement for imipenem was more than acceptable level (>3%) in mE and ME. For meropenem and gentamicin ME showed categorical disagreement (<3%) which was within acceptable level. More than 3% essential disagreement was reported for imipenem (5.0%), meropenem (3.3%) and gentamicin (3.3%), as given in Table 2.
Table 2.
Performance of DAST compared with reference AST method for Enterobacterales by VITEK-2 system
| Enterobacterales (60) | Categorical agreement, n (%) | Categorical disagreement n (%) | Essential agreement | ||||
|---|---|---|---|---|---|---|---|
| Minor error | Major error | Very major error | Total | Agreed | Disagreed | ||
| Cefoperazone sulbactam | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Amoxicillin/clavulanic acid | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Piperacillin/tazobactam | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Cefuroxime | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Cefuroxime axetil | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Cefepime | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Ceftriaxone | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Imipenem | 54 (90.0%) | 2 (3.3%) | 4 (6.7%) | 0 (0.0%) | 6 (10.0%) | 57 (95%) | 3 (5.0%) |
| Meropenem | 59 (98.3%) | 0 (0.0%) | 1 (1.7%) | 0 (0.0%) | 1 (1.7%) | 58 (96.7%) | 2 (3.3%) |
| Amikacin | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Gentamicin | 59 (98.3%) | 0 (0.0%) | 1 (1.7%) | 0 (0.0%) | 1 (1.7%) | 58 (96.7%) | 2 (3.3%) |
| Ciprofloxacin | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100%) | 0 (0.0%) |
| Tigecycline | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100.0%) | 0 (0.0%) |
| Colistin | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100.0%) | 0 (0.0%) |
| Cotrimoxazole | 60 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 60 (100.0%) | 0 (0.0%) |
Categorical agreement of >95% also reported for non-fermenter GNB, except for piperacillin–tazobactam (93.3%). It was observed that VME was within acceptable categorical disagreement of 1.3% for aminoglycosides and levofloxacin (Table 3). Antimicrobials such as ceftazidime, cefepime, carbapenem, aminoglycosides, and fluoroquinolone showed acceptable categorical disagreement below 7% for minor and major error.
Table 3.
Performance of DAST compared with reference AST method for non-fermenters by VITEK-2 system
| Non-fermenters (75) | Categorical agreement, n (%) | Categorical disagreement (%) | Essential agreement | ||||
|---|---|---|---|---|---|---|---|
| Minor error | Major error | Very major error | Total | Agreed | Disagreed | ||
| Aztreonam | 75 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 75 (100.0%) | 0 (0.0%) |
| Piperacillin/tazobactam | 70 (93.3%) | 2 (2.6%) | 3 (4.1%) | 0 (0.0%) | 5 (6.7%) | 74 (98.7%) | 1 (1.3%) |
| Ceftazidime | 74 (98.7%) | 1 (1.3%) | 0 (0.0%) | 0 (0.0%) | 1 (1.3%) | 75 (100.0%) | 0 (0.0%) |
| Cefepime | 74 (98.7%) | 1 (1.3%) | 0 (0.0%) | 0 (0.0%) | 1 (1.3%) | 75 (100.0%) | 0 (0.0%) |
| Cotrimoxazole | 75 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 75 (100.0%) | 0 (0.0%) |
| Imipenem | 74 (98.7%) | 1 (1.3%) | 0 (0.0%) | 0 (0.0%) | 1 (1.3%) | 75 (100.0%) | 0 (0.0%) |
| Meropenem | 74 (98.7%) | 1 (1.3%) | 0 (0.0%) | 0 (0.0%) | 1 (1.3%) | 75 (100.0%) | 0 (0.0%) |
| Amikacin | 73 (97.4%) | 1 (1.3%) | 0 (0.0%) | 1 (1.3%) | 2 (2.6%) | 74 (98.7%) | 1 (1.3%) |
| Gentamicin | 74 (98.7%) | 0 (0.0%) | 0 (0.0%) | 1 (1.3%) | 1 (1.3%) | 75 (100.0%) | 0 (0.0%) |
| Ciprofloxacin | 72 (96.1%) | 1 (1.3%) | 2 (2.6%) | 0 (0.0%) | 3 (3.9%) | 74 (98.7%) | 1 (1.3%) |
| Levofloxacin | 72 (96.1%) | 1 (1.3%) | 1 (1.3%) | 1 (1.3%) | 3 (3.9%) | 74 (98.7%) | 1 (1.3%) |
| Minocycline | 75 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 75 (100.0%) | 0 (0.0%) |
| Tigecycline | 75 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 75 (100.0%) | 0 (0.0%) |
| Colistin | 75 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 75 (100.0%) | 0 (0.0%) |
DAST Result in GPC
As presented in Table 4, gram-positive organisms such as Staphylococcus spp. and Enterococcus spp. showed more than 99.2% categorical agreement and 99.2–99.6% essential agreement. Permitted levels of categorical disagreement was observed for mE, ME, and VME were <1% in this study. Minor error for glycopeptides and fluoroquinolones, ME for glycopeptides and macrolide antibiotics were reported in Staphylococcus spp. while two Enterococcus spp. isolates showed ME for glycopeptides.
Table 4.
Performance of DAST compared with reference AST method for GPC by VITEK-2 System
| Organisms and antibiotic tested (n × Ab = N) | Categorical agreement, n (%) | Categorical disagreement, n (%) among isolate-antibiotic combinations tested | Essential agreement | ||||
|---|---|---|---|---|---|---|---|
| Minor error | Major error | Very major error | Total | Agreed | Disagreed | ||
| Staphylococcus spp. (49 × 15 = 735) | 729 (99.2%) | 3 (0.4%) | 2 (0.27%) | 1 (0.13%) | 6 (0.8%) | 732 (99.6%) | 03 (0.4%) |
| Enterococcus spp. (16 × 15 = 240) | 238 (99.2%) | 0 (0.0%) | 2 (0.8%) | 0 (0.0%) | 2 (0.8%) | 238 (99.2%) | 02 (0.8%) |
| Antibiotics tested (N = 65) | Categorical agreement, n (%) | Categorical disagreement (%) | Essential agreement | ||||
| Minor error | Major error | Very major error | Total | Agreed | Disagreed | ||
| Benzyl penicillin | 65 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 65 (100.0%) | 0 (0.0%) |
| Tetracycline | 65 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 65 (100.0%) | 0 (0.0%) |
| Teicoplanin | 60 (92.3%) | 3 (4.6%) | 2 (3.1%) | 0 (0.0%) | 5 (7.7%) | 63 (96.9%) | 2 (3.1%) |
| Vancomycin | 58 (89.2%) | 3 (4.6%) | 4 (6.2%) | 0 (0.0%) | 7 (10.8%) | 62 (95.4%) | 3 (4.6%) |
| Erythromycin | 63 (96.9%) | 0 (0.0%) | 2 (3.1%) | 0 (0.0%) | 2 (3.1%) | 65 (100.0%) | 0 (0.0%) |
| Clindamycin | 64 (98.5%) | 0 (0.0%) | 1 (1.5%) | 0 (0.0%) | 1 (1.5%) | 65 (100.0%) | 0 (0.0%) |
| Linezolid | 65 (100.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 65 (100.0%) | 0 (0.0%) |
| Levofloxacin | 62 (95.4%) | 3 (4.6%) | 0 (0.0%) | 0 (0.0%) | 3 (4.6%) | 64 (98.5%) | 1 (1.5%) |
| Ciprofloxacin | 62 (95.4%) | 3 (4.6%) | 0 (0.0%) | 0 (0.0%) | 3 (4.6%) | 64 (98.5%) | 1 (1.5%) |
| Cotrimoxazole | 63 (96.9%) | 0 (0.0%) | 2 (3.1%) | 0 (0.0%) | 2 (3.1%) | 65 (100.0%) | 0 (0.0%) |
Among GPCs, many antimicrobials present in automated AST cartridges demonstrated >95% categorical agreement, except teicoplanin (92.3%) and vancomycin (89.2%). Categorical disagreement for glycopeptides was more than acceptable level (>3%) for mE and ME. The essential disagreement of >3% was also seen in teicoplanin (3.1%) and vancomycin (4.6%), as given in Tables 4 to 6.
Table 6.
Difference in time taken to release the report for gram-positive bacteria
| Microorganisms |
DAST
Time in minutes |
RAST
Time in minutes |
|---|---|---|
| Staphylococcus aureus | 695 | 1935 |
| Coagulase negative Staphylococcus | 690 | 1865 |
| Enterococcus spp. | 770 | 2170 |
| Average time | 698.33 | 1990.00 |
Table 5.
Difference in time taken to release the report for gram-negative bacteria
| Microorganisms |
DAST
Time in minutes |
RAST
Time in minutes |
|---|---|---|
| Escherichia coli | 625 | 1765 |
| Klebsiella pneumoniae | 650 | 1997 |
| Pseudomonas aeruginosa | 900 | 2128 |
| Acinetobacter baumannii | 955 | 2227 |
| Average time | 755.00 | 2029.25 |
Turnaround Time
The present study also recorded the turnaround time for the release of report of different organisms tested using DAST method and compared with the reporting time taken by Reference AST.
(A)For GNB
Mean difference: 1274.250 minutes (DAST vs RAST).
T-statistic value: 54.522 and p-value: p < 0.0001 significance level.
(B)For GPC
Mean difference reported: 1291.670 minutes (RAST Time – DAST Time).
T-statistic value: 61.024 and p-value < 0.0001 significance level.
The inference from above findings is that the difference in two means (average time taken to release the report between DAST and RAST) is significant.
Discussion
The availability of AST reports in a shorter time is the need of the hour for saving precious lives lost due to inappropriate antibiotic therapy. Most of the DAST studies from blood culture broth in cases of sepsis in the past were done using the disk diffusion AST method.10,13–16 The present study emphasizes the importance of DAST based on an automated AST system, and the available literature for which is scanty.
In the present study, there was more than 95–99% and 98–99% categorical agreement and essential agreement, respectively between various GNB and GPC organisms tested directly from flagged blood culture bottle and by reference method using overnight grown bacterial colonies. Kavipriya D et al. conducted similar study in South India in 2021, but only for GNB.8 They have reported >95% concordance of DAST result for GNB with RAST, which was similar to our study. Barnini et al. in 2016 conducted a similar study in Italy, where the essential agreement for direct AST by two different protocols for all isolate/antimicrobial agent combinations was 87.8 and 90.5% for GNB and 93.1 and 93.8% for GPC, respectively.17 Mauri et al. observed 98.1% categorical agreement for GNBs-antimicrobial combination and essential agreement between drug–bug combination found to be 97.7%. In their study, MALDI-TOF mass spectrometry was used for bacterial identification and VITEK-2 on 3-hour subculture plates from positively flagged blood culture bottles.18 In comparison to other studies, the present study has a much less technically cumbersome, more economical and faster protocol for Direct AST.15–18Also, most studies have used cards AST 280 and AST 281 while we have conducted this study on cards like AST-405 and AST-406 cards for fermenter GNB and non-fermenter GNB, respectively.14–16
Among GNB isolates tested by DAST, maximum essential disagreement (1.3%) was observed in A.baumannii. A.baumannii also showed highest categorical disagreement in mE and ME, whereas VME was higher in Exotic GNB organisms which were lower in numbers in our study and are in general not isolated very frequently from blood culture. However, all these errors were within acceptable range of <3%, a finding also reported by Kavipriya et al. from South India.8 Mauri et al. did not report any ME and VME in K. pneumoniae and A. baumannii isolates; but their sample size was small.18 Among GPC isolates tested by DAST, the present study has shown excellent and >99% acceptable categorical and essential agreement. There are very few studies on GPC isolates tested directly from flagged blood culture bottles; one such study by Barnini et al. demonstrated only 93% agreement.17 It becomes important that for DAST pellet after washing, suspension should be equivalent to 0.5 MacFarland for getting the appropriate result or else errors will increase.
For Enterobacterales, different antimicrobial analysis showed less essential agreement than the permitted level (<95%) for imipenem, with 2 mE and 4 ME categorical errors. A study from South India by Kavipriya et al. reported maximum categorical error for Enterobacterales and piperacillin–tazobactam combination.8 Amoxicillin–clavulanic acid and piperacillin–tazobactam showed mE for Enterobacterales in the study done by Mauri et al. also.18 The present study has shown permissible level of disagreement (<3% for any error) 2.7% ME and 1.7% VME in exotic GNBs, in order to understand the reason behind this low percentage of error could be because of multiple mechanisms involved in drug resistance as suggested by artificial intelligence of automated system. Among non-fermenters, the piperacillin–tazobactam drug bug combination has shown maximum disagreement of 6.7%; rest all have >95% acceptable categorical and essential agreement. Kavipriya et al. reported essential disagreement <95% for levofloxacin and minocycline among non-fermenters.8 In our study, mEs and VMEs were not significant in the non-fermenter, which was in accordance with other studies.16–18 Less essential agreement for carbapenem and cephalosporin group of the drugs was reported by Pan et al., which was not the case in this study.19 The present study also analyzed the drug–bug combination DAST for GPC, where the categorical agreement was <95% in the case of vancomycin and teicoplanin. Other GPC–drug combination showed excellent acceptable agreement in terms of categorical and essential data. Barnini et al. who used two protocols for GPC bug–drug combination showed agreement of 78.6–93.1% for first protocol and 76.7–93.8% for second protocol; both are less compared with the protocol used in present study.17
In addition to good agreement rates for antimicrobial susceptibility testing, our DAST protocol demonstrated remarkably less time to report when compared with RAST. It is worth noting that final result made available approximately 1 day earlier than usual duration of reporting. We however noted that non-fermenter GNB and Enterococcus spp. took longer time (≥5 hours) for DAST results compared with Enterobacterales and Staphylococcus spp., respectively. Authors are of the view that this could be due to the antimicrobial agent's ability to slowly permeate into these microbes. Though, to corroborate these observations, we need further studies from different centers. Decreasing TAT especially in the case of blood culture diagnostics and sepsis prevention remains a critical factor in patient management. Less hands-on time and slightly lower cost (by avoiding a subculture) are the added advantages of using automated DAST.18,19
Limitations of the Study
The present study comprises of small sample size of isolates and is from a single center. To validate our observations, we need larger, multicentric studies.
Conclusion
The present study compared the RAST and DAST methods from blood cultures flagging positive in an automated system. In the present study, we observed that direct automated VITEK-2 AST from positive blood culture broth could provide prompt and precise antimicrobial sensitivity reports for commonly isolated Enterobacterales, non-fermenters, and GPCs. The direct automated AST method reduces the turnaround time to generate AST reports by 18–24 hours.
Ethical Clearance
Ethically approved by Institutional Ethics Committee (Dr. RMLIMS/IEC no.173/22).
Orcid
Vikramjeet Singh https://orcid.org/0000-0002-5380-7559
Jyotsna Agarwal https://orcid.org/0000-0003-0568-7959
Soumya S Nath https://orcid.org/0000-0002-5981-5437
Avneesh Sharma https://orcid.org/0009-0001-8489-4624
Acknowledgment
Authors would like to acknowledge the help of Mr Anurag of Biostatistics team, Dr RMLIMS, Lucknow for assistance in applying statistical tool in this study.
Supplementary Material
All the supplementary materials are available online on the website of www.IJCCM.org.
Footnotes
Source of support: Yes, received Intramural Grant from Dr. RMLIMS, Lucknow, Uttar Pradesh, India
Conflict of interest: None
References
- 1.Rajni E, Garg VK, Bacchani D, Sharma R, Vohra R, Mamoria V, et al. Prevalence of bloodstream infections and their etiology in COVID-19 patients admitted in a tertiary care hospital in Jaipur. Indian J Crit Care Med. 2021;25(4):369–373. doi: 10.5005/jp-journals-10071-23781. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Rudd KE, Johnson SC, Agesa KM, Shackelford KA, Tsoi D, Kievlan DR, et al. Global, regional, and national sepsis incidence and mortality, 1990–2017: Analysis for the Global Burden of Disease Study. Lancet. 2020;395(10219):200–211. doi: 10.1016/S0140-6736(19)32989-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Tjandra KC, Ram-Mohan N, Abe R, Hashemi MM, Lee JH, Chin SM, et al. Diagnosis of bloodstream infections: An evolution of technologies towards accurate and rapid identification and antibiotic susceptibility testing. Antibiotics (Basel) 2022;11(4):511. doi: 10.3390/antibiotics11040511. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, et al. Surviving sepsis campaign: International guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021;47(11):1181–1247. doi: 10.1007/s00134-021-06506-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Duncan CF, Youngstein T, Kirrane MD, Lonsdale DO. Diagnostic Challenges in Sepsis. Curr Infect Dis Rep. 2021;23(12):22. doi: 10.1007/s11908-021-00765-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Hogan CA, Watz N, Budvytiene I, Banaei N. Rapid antimicrobial susceptibility testing by VITEK®2 directly from blood cultures in patients with Gram-negative rod bacteremia. Diagn Microbiol Infect Dis. 2019;94(2):116–121. doi: 10.1016/j.diagmicrobio.2019.01.001. [DOI] [PubMed] [Google Scholar]
- 7.Agarwal J, Singh V, Das A, Nath SS, Kumar R, Sen M. Reversing the trend of antimicrobial resistance in icu: Role of antimicrobial and diagnostic Stewardship. Indian J Crit Care Med. 2021;25(6):635–641. doi: 10.5005/jp-journals-10071-23861. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Kavipriya D, Prakash SS, Dhandapani S, Rajshekar D, Sastry AS. Evaluation of the performance of direct susceptibility test by VITEK-2 from positively flagged blood culture broth for gram-negative bacilli. J Lab Physicians. 2021;13(4):374–379. doi: 10.1055/s-0041-1732489. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Rajshekar D, Chaudhari KV, Bhat P, Prakash SS, Raghvan R, Vasanth S, et al. Evaluation of performance of direct disk diffusion test from positively flagged blood culture broth: A large scale study from South India. J Lab Physicians. 2019;11(2):154–160. doi: 10.4103/JLP.JLP_137_18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kumar M, Shergill SPS, Tandel K, Sahai K, Gupta RM. Direct antimicrobial susceptibility testing from positive blood culture bottles in laboratories lacking automated antimicrobial susceptibility testing systems. Med J Armed Forces India. 2019;75(4):450–457. doi: 10.1016/j.mjafi.2018.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Hazelton B, Thomas LC, Olma T, Kok J, O'Sullivan M, Chen SCA, et al. Rapid and accurate direct antibiotic susceptibility testing of blood culture broths using MALDI Sepsityper combined with the BD Phoenix automated system. J Med Microbiol. 2014;63(Pt 12):1590–1594. doi: 10.1099/jmm.0.075580-0. [DOI] [PubMed] [Google Scholar]
- 12.ISO 20776–1:2006 Clinical laboratory testing and in vitro diagnostic test systems. Susceptibility testing of infectious agents and evaluation of performance of antimicrobial susceptibility test devices—part 2: Evaluation of performance of antimicrobial susceptibility test devices.https://www.iso.org/standard/41631.html Available at: [Google Scholar]
- 13.Jorgensen JH. Selection criteria for an antimicrobial susceptibility testing system. J Clin Microbiol. 1993;31(11):2841–2844. doi: 10.1128/jcm.31.11.2841-2844.1993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Heather CS, Maley M. Automated direct screening for resistance of Gram-negative blood cultures using the BD KiestraWork Cell. Eur J Clin Microbiol Infect Dis. 2018;37(1):117–125. doi: 10.1007/s10096-017-3109-2. [DOI] [PubMed] [Google Scholar]
- 15.Coyle MB, McGonagle LA, Plorde JJ, Clausen CR, Schoenknecht FD. Rapid antimicrobial susceptibility testing of isolates from blood cultures by direct inoculation and early reading of disk diffusion tests. J Clin Microbiol. 1984;20(3):473–477. doi: 10.1128/jcm.20.3.473-477.1984. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Coorevits L, Boelens J, Claeys G. Direct susceptibility testing by disk diffusion on clinical samples: A rapid and accurate tool for antibiotic stewardship. Eur J Clin Microbiol Infect Dis. 2015;34(6):1207–1212. doi: 10.1007/s10096-015-2349-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Barnini S, Brucculeri V, Morici P, Ghelardi E, Florio W, Lupetti A. A new rapid method for direct antimicrobial susceptibility testing of bacteria from positive blood cultures. BMC Microbiol. 2016;16(1):185. doi: 10.1186/s12866-016-0805-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Mauri C, Principe L, Bracco S, Meroni E, Corbo N, Pini B, et al. Identification by mass spectrometry and automated susceptibility testing from positive bottles: A simple, rapid, and standardized approach to reduce the turnaround time in the management of blood cultures. BMC Infect Dis. 2017;17(1):749. doi: 10.1186/s12879-017-2851-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Pan HW, Li W, Li RG, Li Y, Zhang Y, Sun EH. Simple sample preparation method for direct microbial identification and susceptibility testing from positive blood cultures. Front Microbiol. 2018;9:481. doi: 10.3389/fmicb.2018.00481. [DOI] [PMC free article] [PubMed] [Google Scholar]