Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial

Brenner T, Skarabis A, Stevens P, Axnick J, Haug P, Grumaz S, Bruckner T, Luntz S, Witzke O, Pletz MW, Ruprecht TM, et al. (2021)
Trials 22(1): 714.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Autor*in
Brenner, Thorsten; Skarabis, Annabell; Stevens, Philip; Axnick, Jennifer; Haug, Peter; Grumaz, Silke; Bruckner, Thomas; Luntz, Steffen; Witzke, Oliver; Pletz, Mathias W; Ruprecht, Thomas M; Marschall, Ursula
Alle
Abstract / Bemerkung
BACKGROUND: Sepsis is triggered by an infection and represents one of the greatest challenges of modern intensive care medicine. With regard to a targeted antimicrobial treatment strategy, the earliest possible pathogen detection is of crucial importance. Until now, culture-based detection methods represent the diagnostic gold standard, although they are characterized by numerous limitations. Culture-independent molecular diagnostic procedures represent a promising alternative. In particular, the plasmatic detection of circulating, cell-free DNA by next-generation sequencing (NGS) has shown to be suitable for identifying disease-causing pathogens in patients with bloodstream infections.; METHODS: The DigiSep-Trial is a randomized, controlled, interventional, open-label, multicenter trial characterizing the effect of the combination of NGS-based digital precision diagnostics with standard-of-care microbiological analyses compared to solely standard-of-care microbiological analyses in the clinical picture of sepsis/septic shock. Additional anti-infective expert consultations are provided for both study groups. In 410 patients (n = 205 per arm) with sepsis/septic shock, the study examines whether the so-called DOOR-RADAR (Desirability of Outcome Ranking/Response Adjusted for Duration of Antibiotic Risk) score (representing a combined endpoint including the criteria (1) intensive/intermediate care unit length of stay, (2) consumption of antibiotics, (3) mortality, and (4) acute kidney injury (AKI)) can be improved by an additional NGS-based diagnostic concept. We also aim to investigate the cost-effectiveness of this new diagnostic procedure. It is postulated that intensive/intermediate care unit length of stay, mortality rate, incidence of AKI, the duration of antimicrobial therapy as well as the costs caused by complications and outpatient aftercare can be reduced. Moreover, a significant improvement in patient's quality of life is expected.; DISCUSSION: The authors previous work suggests that NGS-based diagnostics have a higher specificity and sensitivity compared to standard-of-care microbiological analyses for detecting bloodstream infections. In combination with the here presented DigiSep-Trial, this work provides the optimal basis to establish a new NGS-driven concept as part of the national standard based on the best possible evidence.; TRIAL REGISTRATIONS: DRKS-ID DRKS00022782 . Registered on August 25, 2020 ClinicalTrials.gov NCT04571801 . Registered October 1, 2020. © 2021. The Author(s).
Erscheinungsjahr
2021
Zeitschriftentitel
Trials
Band
22
Ausgabe
1
Art.-Nr.
714
eISSN
1745-6215
Page URI
https://pub.uni-bielefeld.de/record/2958748

Zitieren

Brenner T, Skarabis A, Stevens P, et al. Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial. Trials. 2021;22(1): 714.
Brenner, T., Skarabis, A., Stevens, P., Axnick, J., Haug, P., Grumaz, S., Bruckner, T., et al. (2021). Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial. Trials, 22(1), 714. https://doi.org/10.1186/s13063-021-05667-x
Brenner, T., Skarabis, A., Stevens, P., Axnick, J., Haug, P., Grumaz, S., Bruckner, T., Luntz, S., Witzke, O., Pletz, M. W., et al. (2021). Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial. Trials 22:714.
Brenner, T., et al., 2021. Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial. Trials, 22(1): 714.
T. Brenner, et al., “Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial”, Trials, vol. 22, 2021, : 714.
Brenner, T., Skarabis, A., Stevens, P., Axnick, J., Haug, P., Grumaz, S., Bruckner, T., Luntz, S., Witzke, O., Pletz, M.W., Ruprecht, T.M., Marschall, U., Altin, S., Greiner, W., Berger, M.M.: Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial. Trials. 22, : 714 (2021).
Brenner, Thorsten, Skarabis, Annabell, Stevens, Philip, Axnick, Jennifer, Haug, Peter, Grumaz, Silke, Bruckner, Thomas, Luntz, Steffen, Witzke, Oliver, Pletz, Mathias W, Ruprecht, Thomas M, Marschall, Ursula, Altin, Sibel, Greiner, Wolfgang, and Berger, Marc Moritz. “Optimization of sepsis therapy based on patient-specific digital precision diagnostics using next generation sequencing (DigiSep-Trial)-study protocol for a randomized, controlled, interventional, open-label, multicenter trial”. Trials 22.1 (2021): 714.

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®

Quellen

PMID: 34663439
PubMed | Europe PMC

Suchen in

Google Scholar