Right dose, right now: bedside, real-time, data-driven, and personalised antibiotic dosing in critically ill patients with sepsis or septic shock—a two-centre randomised clinical trial

Abstract

Background Adequate antibiotic dosing may improve outcomes in critically ill patients but is challenging due to altered and variable pharmacokinetics. To address this challenge, AutoKinetics was developed, a decision support system for bedside, real-time, data-driven and personalised antibiotic dosing. This study evaluates the feasibility, safety and efficacy of its clinical implementation. Methods In this two-centre randomised clinical trial, critically ill patients with sepsis or septic shock were randomised to AutoKinetics dosing or standard dosing for four antibiotics: vancomycin, ciprofloxacin, meropenem, and ceftriaxone. Adult patients with a confirmed or suspected infection and either lactate > 2 mmol/L or vasopressor requirement were eligible for inclusion. The primary outcome was pharmacokinetic target attainment in the first 24 h after randomisation. Clinical endpoints included mortality, ICU length of stay and incidence of acute kidney injury. Results After inclusion of 252 patients, the study was stopped early due to the COVID-19 pandemic. In the ciprofloxacin intervention group, the primary outcome was obtained in 69% compared to 3% in the control group (OR 62.5, CI 11.4–1173.78, p < 0.001). Furthermore, target attainment was faster (26 h, CI 18–42 h, p < 0.001) and better (65% increase, CI 49–84%, p < 0.001). For the other antibiotics, AutoKinetics dosing did not improve target attainment. Clinical endpoints were not significantly different. Importantly, higher dosing did not lead to increased mortality or renal failure. Conclusions In critically ill patients, personalised dosing was feasible, safe and significantly improved target attainment for ciprofloxacin. Trial registration: The trial was prospectively registered at Netherlands Trial Register (NTR), NL6501/NTR6689 on 25 August 2017 and at the European Clinical Trials Database (EudraCT), 2017-002478-37 on 6 November 2017.

Update on Therapeutic Drug Monitoring of Beta-Lactam Antibiotics in Critically Ill Patients—A Narrative Review

“…No benefit in terms of shortening the length of stay was observed, while target attainment in both MIDP and control groups was similar [ 139 ]. In a two-center Dutch trial, the adaptive dosing of four antibiotics including meropenem and ceftriaxone in septic patients did not lead to the better target attainment of these beta-lactams nor did it improve any clinical outcome [ 140 ]. While the effectiveness of the TDM guided approach to beta-lactam prescription has not been proven, it may be beneficial in certain subgroups of critically ill patients.…”

Association between serum sodium and 28‐day mortality in sepsis patients: A secondary data analysis from three large critical illness cohorts

“…The selection of these factors was mostly based on our clinical experience and the literature. [19,20]…”

Global research trends in artificial intelligence for critical care with a focus on chord network charts: Bibliometric analysis

“…AI utilization in critical care primarily encompasses disease diagnosis, prediction of disease progression (clinical deterioration), and characterization of specific disease phenotypes or endotypes, [3] such as those found in sepsis, [14] septic shock, [15,16] and acute respiratory distress syndrome. [17] For example, in a large multicenter database, authors [18] compared various techniques for detecting clinical deterioration on wards and found that an AI expert algorithm was developed [19] to predict sepsis early.…”