Modelling potential/current distribution in microbial electrochemical systems shows how the optimal bioanode architecture depends on electrolyte conductivity.

The theoretical bases for modelling the distribution of the electrostatic potential in microbial electrochemical systems are described. The secondary potential distribution (i.e. without mass transport limitation of the substrate) is shown to be sufficient to validly address microbial electrolysis cells (MECs). MECs are modelled with two different ionic conductivities of the solution (1 and 5.3 S m(-1)) and two bioanode kinetics (jmax = 5.8 or 34 A m(-2)). A conventional reactor configuration, with the anode and the cathode face to face, is compared with a configuration where the bioanode perpendicular to the cathode implements the electrochemical reaction on its two sides. The low solution conductivity is shown to have a crucial impact, which cancels out the advantages obtained by setting the bioanode perpendicular to the cathode. For the same reason, when the surface area of the anode is increased by multiplying the number of plates, care must be taken not to create too dense anode architecture. Actually, the advantages of increasing the surface area by multiplying the number of plates can be lost through worsening of the electrochemical conditions in the multi-layered anode, because of the increase of the electrostatic potential of the solution inside the anode structure. The model gives the first theoretical bases for scaling up MECs in a rather simple but rigorous way.

Impact of interactive computerised decision support for hospital antibiotic use (COMPASS): an open-label, cluster-randomised trial in three Swiss hospitals.

BACKGROUND: Computerised decision-support systems (CDSSs) for antibiotic stewardship could help to assist physicians in the appropriate prescribing of antibiotics. However, high-quality evidence for their effect on the quantity and quality of antibiotic use remains scarce. The aim of our study was to assess whether a computerised decision support for antimicrobial stewardship combined with feedback on prescribing indicators can reduce antimicrobial prescriptions for adults admitted to hospital. METHODS: The Computerised Antibiotic Stewardship Study (COMPASS) was a multicentre, cluster-randomised, parallel-group, open-label superiority trial that aimed to assess whether a multimodal computerised antibiotic-stewardship intervention is effective in reducing antibiotic use for adults admitted to hospital. After pairwise matching, 24 wards in three Swiss tertiary-care and secondary-care hospitals were randomised (1:1) to the CDSS intervention or to standard antibiotic stewardship measures using an online random sequence generator. The multimodal intervention consisted of a CDSS providing support for choice, duration, and re-evaluation of antimicrobial therapy, and feedback on antimicrobial prescribing quality. The primary outcome was overall systemic antibiotic use measured in days of therapy per admission, using adjusted-hurdle negative-binomial mixed-effects models. The analysis was done by intention to treat and per protocol. The study was registered with ClinicalTrials.gov (identifier NCT03120975). FINDINGS: 24 clusters (16 at Geneva University Hospitals and eight at Ticino Regional Hospitals) were eligible and randomly assigned to control or intervention between Oct 1, 2018, and Dec 31, 2019. Overall, 4578 (40·2%) of 11 384 admissions received antibiotic therapy in the intervention group and 4142 (42·8%) of 9673 in the control group. The unadjusted overall mean days of therapy per admission was slightly lower in the intervention group than in the control group (3·2 days of therapy per admission, SD 6·2, vs 3·5 days of therapy per admission, SD 6·8; p<0·0001), and was similar among patients receiving antibiotics (7·9 days of therapy per admission, SD 7·6, vs 8·1 days of therapy per admission, SD 8·4; p=0·50). After adjusting for confounders, there was no statistically significant difference between groups for the odds of an admission receiving antibiotics (odds ratio [OR] for intervention vs control 1·12, 95% CI 0·94-1·33). For admissions with antibiotic exposure, days of therapy per admission were also similar (incidence rate ratio 0·98, 95% CI 0·90-1·07). Overall, the CDSS was used at least once in 3466 (75·7%) of 4578 admissions with any antibiotic prescription, but from the first day of antibiotic treatment for only 1602 (58·9%) of 2721 admissions in Geneva. For those for whom the CDSS was not used from the first day, mean time to use of CDSS was 8·9 days. Based on the manual review of 1195 randomly selected charts, transition from intravenous to oral therapy was significantly more frequent in the intervention group after adjusting for confounders (154 [76·6%] of 201 vs 187 [87%] of 215, +10·4%; OR 1·9, 95% CI 1·1-3·3). Consultations by infectious disease specialists were less frequent in the intervention group (388 [13·4%] of 2889) versus the control group (405 [16·9%] of 2390; OR 0·84, 95% CI 0·59-1·25). INTERPRETATION: An integrated multimodal computerised antibiotic stewardship intervention did not significantly reduce overall antibiotic use, the primary outcome of the study. Contributing factors were probably insufficient uptake, a setting with relatively low antibiotic use at baseline, and delays between ward admission and first CDSS use. FUNDING: Swiss National Science Foundation. TRANSLATIONS: For the French and Italian translations of the abstract see Supplementary Materials section.

Industrially scalable surface treatments to enhance the current density output from graphite bioanodes fueled by real domestic wastewater.

Acid and electrochemical surface treatments of graphite electrode, used individually or in combination, significantly improved the microbial anode current production, by +17% to +56%, in well-regulated and duplicated electroanalytical experimental systems. Of all the consequences induced by surface treatments, the modifications of the surface nano-topography preferentially justify an improvement in the fixation of bacteria, and an increase of the specific surface area and the electrochemically accessible surface of graphite electrodes, which are at the origin of the higher performances of the bioanodes supplied with domestic wastewater. The evolution of the chemical composition and the appearance of C-O, C=O, and O=C-O groups on the graphite surface created by combining acid and electrochemical treatments was prejudicial to the formation of efficient domestic-wastewater-oxidizing bioanodes. The comparative discussion, focused on the positioning of the performances, shows the industrial interest of applying the surface treatment method to the world of bioelectrochemical systems.

How to Develop and Implement a Computerized Decision Support System Integrated for Antimicrobial Stewardship? Experiences From Two Swiss Hospital Systems.

Background: Computerized decision support systems (CDSS) provide new opportunities for automating antimicrobial stewardship (AMS) interventions and integrating them in routine healthcare. CDSS are recommended as part of AMS programs by international guidelines but few have been implemented so far. In the context of the publicly funded COMPuterized Antibiotic Stewardship Study (COMPASS), we developed and implemented two CDSSs for antimicrobial prescriptions integrated into the in-house electronic health records of two public hospitals in Switzerland. Developing and implementing such systems was a unique opportunity for learning during which we faced several challenges. In this narrative review we describe key lessons learned. Recommendations: (1) During the initial planning and development stage, start by drafting the CDSS as an algorithm and use a standardized format to communicate clearly the desired functionalities of the tool to all stakeholders. (2) Set up a multidisciplinary team bringing together Information Technologies (IT) specialists with development expertise, clinicians familiar with "real-life" processes in the wards and if possible, involve collaborators having knowledge in both areas. (3) When designing the CDSS, make the underlying decision-making process transparent for physicians and start simple and make sure to find the right balance between force and persuasion to ensure adoption by end-users. (4) Correctly assess the clinical and economic impact of your tool, therefore try to use standardized terminologies and limit the use of free text for analysis purpose. (5) At the implementation stage, plan usability testing early, develop an appropriate training plan suitable to end users' skills and time-constraints and think ahead of additional challenges related to the study design that may occur (such as a cluster randomized trial). Stay also tuned to react quickly during the intervention phase. (6) Finally, during the assessment stage plan ahead maintenance, adaptation and related financial challenges and stay connected with institutional partners to leverage potential synergies with other informatics projects.