Rapid molecular diagnostics for antimicrobial-resistant bacterial infections: impact on time to effective antibiotic therapy and clinical outcomes
DOI:
https://doi.org/10.66687/jebmr.2.1.2026.6Keywords:
molecular diagnosticsAbstract
Background: Resistant bacterial infections require timely effective therapy, yet conventional organism identification and antimicrobial susceptibility testing may delay treatment modification. We compared rapid molecular diagnostics with conventional pathways in a multicentre observational cohort.
Methods: The de-identified dataset comprised 520 adults with confirmed resistant bacterial infections from eight hospitals, including 259 managed via rapid testing and 261 via conventional methods. Clinical suspicion was time zero. The primary treatment-timing analysis focused on patients not already receiving effective empirical antibiotics. Secondary outcomes included actionable-result time, antimicrobial stewardship review, active therapy within 24 hours, 30-day mortality, clinical cure and hospital stay. Multivariable models adjusted for baseline case mix, resistance phenotype and hospital.
Results: The median time to actionable results was 8.8 versus 61.7 hours, respectively. Among 358 patients initially without active therapy, 181 rapid-test patients and 177 controls were at risk; effective therapy was ultimately initiated in 181 and 174, respectively. Median time to active therapy among recipients was 17.2 versus 69.5 hours (difference −52.3 hours; bootstrap 95% CI −58.4 to −47.4). Therapy by 24 hours occurred in 162/181 (89.5%) versus 0/177 (0%). In the total cohort, 30-day mortality was 10.4% versus 7.3%; adjusted odds ratio (aOR) 1.21 (95% CI 0.62–2.33). Clinical cure occurred in 72.2% versus 69.3% (aOR 1.28, 95% CI 0.86–1.92).
Conclusions: Rapid testing was associated with substantially earlier actionable microbiology and active treatment in patients lacking effective initial coverage. No statistically established improvement in survival, cure or length of stay was observed. The non-randomised design and near-complete timing separation require cautious interpretation.
References
1. Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;399:629–655. doi:10.1016/S0140-6736(21)02724-0.
2. Naghavi M, Vollset SE, Ikuta KS, et al. Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050. Lancet. 2024;404:1199–1226. doi:10.1016/S0140-6736(24)01867-1.
3. Tamma PD, Heil EL, Justo JA, Mathers AJ, Satlin MJ, Bonomo RA. Infectious Diseases Society of America 2024 guidance on the treatment of antimicrobial-resistant Gram-negative infections. Clin Infect Dis. 2024;ciae403. doi:10.1093/cid/ciae403.
4. Evans L, Rhodes A, Alhazzani W, et al. Surviving Sepsis Campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021;47:1181–1247. doi:10.1007/s00134-021-06506-y.
5. Ibrahim EH, Sherman G, Ward S, Fraser VJ, Kollef MH. The influence of inadequate antimicrobial treatment of bloodstream infections on patient outcomes in the ICU setting. Chest. 2000;118:146–155.
6. Kumar A, Roberts D, Wood KE, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med. 2006;34:1589–1596.
7. Ferrer R, Martin-Loeches I, Phillips G, et al. Empiric antibiotic treatment reduces mortality in severe sepsis and septic shock from the first hour: results from a guideline-based performance improvement program. Crit Care Med. 2014;42:1749–1755.
8. Kang CI, Kim SH, Kim HB, et al. Pseudomonas aeruginosa bacteremia: risk factors for mortality and influence of delayed receipt of effective antimicrobial therapy. Clin Infect Dis. 2003;37:745–751.
9. Lee YT, Kuo SC, Yang SP, et al. Impact of appropriate antimicrobial therapy on mortality associated with Acinetobacter baumannii bacteremia: relation to severity of infection. Clin Infect Dis. 2012;55:209–215.
10. Lodise TP Jr, Patel N, Kwa A, et al. Predictors of 30-day mortality among patients with Pseudomonas aeruginosa bloodstream infections: impact of delayed appropriate antibiotic selection. Antimicrob Agents Chemother. 2007;51:3510–3515.
11. Moehring RW, Sloane R, Chen LF, et al. Delays in appropriate antibiotic therapy for Gram-negative bloodstream infections: a multicenter, community hospital study. PLoS One. 2013;8:e76225.
12. Schwaber MJ, Carmeli Y. Mortality and delay in effective therapy associated with extended-spectrum beta-lactamase production in Enterobacteriaceae bacteraemia: a systematic review and meta-analysis. J Antimicrob Chemother. 2007;60:913–920.
13. Van Heuverswyn J, Valik JK, van der Werff SD, Hedberg P, Giske CG, Nauclér P. Association between time to appropriate antimicrobial treatment and 30-day mortality in patients with bloodstream infections: a retrospective cohort study. Clin Infect Dis. 2023;76:469–478.
14. Ohnuma T, Chihara S, Costin B, et al. Association of appropriate empirical antimicrobial therapy with in-hospital mortality in patients with bloodstream infections in the US. JAMA Netw Open. 2023;6:e2249353.
15. Vincent JL, Rello J, Marshall J, et al. International study of the prevalence and outcomes of infection in intensive care units. JAMA. 2009;302:2323–2329.
16. Sweeney TE, Liesenfeld O, May L. Diagnosis of bacterial sepsis: why are tests for bacteremia not sufficient? Expert Rev Mol Diagn. 2019;19:959–962.
17. Lamy B, Sundqvist M, Idelevich EA. Bloodstream infections—standard and progress in pathogen diagnostics. Clin Microbiol Infect. 2020;26:142–150.
18. Peker N, Couto N, Sinha B, Rossen JW. Diagnosis of bloodstream infections from positive blood cultures and directly from blood samples: recent developments in molecular approaches. Clin Microbiol Infect. 2018;24:944–955.
19. Peri AM, Ling W, Furuya-Kanamori L, Harris PNA, Paterson DL. Performance of BioFire blood culture identification 2 panel (BCID2) for the detection of bloodstream pathogens and associated resistance markers: a systematic review and meta-analysis. BMC Infect Dis. 2022;22:794.
20. Miller MB, Atrzadeh F, Burnham CAD, et al. Clinical utility of advanced microbiology testing tools. J Clin Microbiol. 2019;57:e00495-19.
21. Pantel A, Monier J, Lavigne JP. Performance of the Accelerate Pheno system for identification and antimicrobial susceptibility testing of a panel of multidrug-resistant Gram-negative bacilli directly from positive blood cultures. J Antimicrob Chemother. 2018;73:1546–1552.
22. Banerjee R, Teng CB, Cunningham SA, et al. Randomized trial of rapid multiplex polymerase chain reaction-based blood culture identification and susceptibility testing. Clin Infect Dis. 2015;61:1071–1080. doi:10.1093/cid/civ447.
23. Banerjee R, Komarow L, Virk A, et al. Randomized trial evaluating clinical impact of rapid identification and susceptibility testing for Gram-negative bacteremia: RAPIDS-GN. Clin Infect Dis. 2021;73:e39–e46. doi:10.1093/cid/ciaa528.
24. Timbrook TT, Morton JB, McConeghy KW, Caffrey AR, Mylonakis E, LaPlante KL. The effect of molecular rapid diagnostic testing on clinical outcomes in bloodstream infections: a systematic review and meta-analysis. Clin Infect Dis. 2017;64:15–23. doi:10.1093/cid/ciw649.
25. Peri AM, Chatfield MD, Ling W, Furuya-Kanamori L, Harris PNA, Paterson DL. Rapid diagnostic tests and antimicrobial stewardship programs for management of bloodstream infection: a systematic review and network meta-analysis. Clin Infect Dis. 2024;79:502–515. doi:10.1093/cid/ciae234.
26. Pliakos EE, Andreatos N, Shehadeh F, Ziakas PD, Mylonakis E. The cost-effectiveness of rapid diagnostic testing for the diagnosis of bloodstream infections with or without antimicrobial stewardship. Clin Microbiol Rev. 2018;31:e00095-17. doi:10.1128/CMR.00095-17.
27. MacVane SH, Nolte FS. Benefits of adding a rapid PCR-based blood culture identification panel to an established antimicrobial stewardship program. J Clin Microbiol. 2016;54:2455–2463. doi:10.1128/JCM.00996-16.
28. Huang AM, Newton D, Kunapuli A, et al. Impact of rapid organism identification via MALDI-TOF combined with antimicrobial stewardship team intervention in adult patients with bacteremia and candidemia. Clin Infect Dis. 2013;57:1237–1245.
29. Perez KK, Olsen RJ, Musick WL, et al. Integrating rapid pathogen identification and antimicrobial stewardship significantly decreases hospital costs. Arch Pathol Lab Med. 2013;137:1247–1254.
30. Perez KK, Olsen RJ, Musick WL, et al. Integrating rapid diagnostics and antimicrobial stewardship improves outcomes in patients with antibiotic-resistant Gram-negative bacteremia. J Infect. 2014;69:216–225.
31. Pardo J, Klinker KP, Borgert SJ, Butler BM, Giglio PG, Rand KH. Clinical and economic impact of antimicrobial stewardship interventions with the FilmArray blood culture identification panel. Diagn Microbiol Infect Dis. 2016;84:159–164.
32. Bookstaver PB, Nimmich EB, Smith TJ III, et al. Cumulative effect of an antimicrobial stewardship and rapid diagnostic testing bundle on early streamlining of antimicrobial therapy in Gram-negative bloodstream infections. Antimicrob Agents Chemother. 2017;61:e00189-17. doi:10.1128/AAC.00189-17.
33. Ehren K, Meisner A, Jazmati N, et al. Clinical impact of rapid species identification from positive blood cultures with same-day phenotypic antimicrobial susceptibility testing on management and outcome of bloodstream infections. Clin Infect Dis. 2020;70:1285–1293.
34. Barlam TF, Cosgrove SE, Abbo LM, et al. Implementing an antibiotic stewardship program: guidelines by IDSA and SHEA. Clin Infect Dis. 2016;62:e51–e77. doi:10.1093/cid/ciw118.
35. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The STROBE statement: guidelines for reporting observational studies. PLoS Med. 2007;4:e296. doi:10.1371/journal.pmed.0040296.
36. Vincent JL, Moreno R, Takala J, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. Intensive Care Med. 1996;22:707–710. doi:10.1007/BF01709751.
37. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–383. doi:10.1016/0021-9681(87)90171-8.
38. Hernán MA, Robins JM. Using big data to emulate a target trial when a randomized trial is not available. Am J Epidemiol. 2016;183:758–764.
39. Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94:496–509.
40. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46:399–424.
41. Nguyen DT, Yeh E, Perry S, et al. Real-time PCR testing for mecA reduces vancomycin usage and length of hospitalization for patients infected with methicillin-sensitive staphylococci. J Clin Microbiol. 2010;48:785–790.
42. Seddon MM, Bookstaver PB, Justo JA, et al. Role of early de-escalation of antimicrobial therapy on risk of Clostridioides difficile infection following Enterobacteriaceae bloodstream infections. Clin Infect Dis. 2019;69:414–420.
43. Webb BJ, Subramanian A, Lopansri B, et al. Antibiotic exposure and risk for hospital-associated Clostridioides difficile infection. Antimicrob Agents Chemother. 2020;64:e02169-19.
