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The potential increased risk of immune-related adverse events (irAEs) post-influenza vaccine is a concern in patients receiving immune checkpoint inhibitors (ICI). We conducted a systematic review with meta-analysis of studies reporting the effects of influenza vaccination in patients with cancer during ICI treatment. We searched five electronic databases until 01/2022. Two authors independently selected studies, appraised their quality, and collected data. The primary outcome was the determination of pooled irAE rates. Secondary outcomes included determination of immunogenicity and influenza infection rates and cancer-related outcomes. Nineteen studies (26 publications, n = 4705) were included; 89.5% were observational. Vaccinated patients reported slighter lower rates of irAEs compared to unvaccinated patients (32% versus 41%, respectively). Seroprotection for influenza type A was 78%–79%, and for type B was 75%. Influenza and irAE-related death rates were similar between groups. The pooled proportion of participants reporting a laboratory-confirmed infection was 2% (95% CI 0% to 6%), and influenza-like illness was 14% (95% CI 2% to 32%). No differences were reported on the rates of laboratory-confirmed infection between vaccinated and unvaccinated patients. Longer progression-free and overall survival was also observed in vaccinated compared with unvaccinated patients. Current evidence suggests that influenza vaccination is safe in patients receiving ICIs, does not increase the risk of irAEs, and may improve survival.

Background Understanding antimicrobial consumption is essential to mitigate the development of antimicrobial resistance, yet robust data in children are sparse and methodologically limited. Electronic prescribing systems provide an important opportunity to analyse and report antimicrobial consumption in detail. Objectives We investigated the value of electronic prescribing data from a tertiary children’s hospital to report temporal trends in antimicrobial consumption in hospitalized children and compare commonly used metrics of antimicrobial consumption. Methods Daily measures of antimicrobial consumption [days of therapy (DOT) and DDDs] were derived from the electronic prescribing system between 2010 and 2018. Autoregressive moving-average models were used to infer trends and the estimates were compared with simulated point prevalence surveys (PPSs). Results More than 1.3 million antimicrobial administrations were analysed. There was significant daily and seasonal variation in overall consumption, which reduced annually by 1.77% (95% CI 0.50% to 3.02%). Relative consumption of meropenem decreased by 6.6% annually (95% CI −3.5% to 15.8%) following the expansion of the hospital antimicrobial stewardship programme. DOT and DDDs exhibited similar trends for most antimicrobials, though inconsistencies were observed where changes to dosage guidelines altered consumption calculation by DDDs, but not DOT. PPS simulations resulted in estimates of change over time, which converged on the model estimates, but with much less precision. Conclusions Electronic prescribing systems offer significant opportunities to better understand and report antimicrobial consumption in children. This approach to modelling administration data overcomes the limitations of using interval data and dispensary data. It provides substantially more detailed inferences on prescribing patterns and the potential impact of stewardship interventions.

The cardiokymograph or displacement cardiograph (DCG) is a noncontacting device which senses movement of the heart throughout the cardiac cycle by the interaction of a radiofrequency (10-20 MHz) electromagnetic field, generated by a sensing coil, with the thorax. In the paper three different techniques of detecting this movement will be discussed: monitoring the changes in sensing resonant frequency (FM modulation), monitoring the changes in impedance of the coil at resonant frequency (AM modulation) and a new technique which monitors the changes in coil impedance at fixed frequency. The sensitivities of these three techniques will be compared. A simplified theory of the mode of coupling between the coil and the thorax will be studied in terms of a transformer model. Preliminary clinical measurements of anterior left and right ventricular motion will be given. The presence of higher-frequency features related to atrial motion and the opening and closing of the aortic and pulmonary values will also be described.

Radiofrequency coils are used as sensors in various applications such as nuclear magnetic resonance (NMR) imaging and displacement cardiograms (DCGs). In most cases the impedance and the resonant frequency of the coil are monitored to provide the required information. The paper describes the changes in reflected impedance and in resonant frequency of a coil when it is placed near a medium with properties ranging from a lossy dielectric to a pure conductor. The theory of interaction between the coil and the medium is investigated and a model based on the use of vector potentials is developed. One prediction of the theory is that placing the coil over body equivalent saline (lossy dielectric) at 15 MHz results in an increase in the inductance of the coil and a resultant decrease in resonant frequency. This prediction was supported experimentally.

BackgroundVasovagal syncope (VVS) is the most common form of syncope, accounting for 50-60% of unexplained syncope. Currently diagnosis is achieved via clinical assessment combined with the Head-Up Tilt Test (HUT).AimTo examine the utility of the active stand test (AS) to identify those with a positive HUT or diagnosis of VVS.DesignRetrospective study of hemodynamic responses to AS.MethodsContinuous blood pressure responses to AS from 101 patients attending a Falls and Blackouts Unit were acquired, including: 37 controls (CON), 64 with a clinical diagnosis of VVS (VVS+) (34 tilt-positive (HUT+) and 30 tilt-negative (HUT-)) with a mean age of 25 ± 9 years. A total of 33 hemodynamic features were extracted with a subset of these entered into linear discriminant classifier. Classification accuracy was assessed using N-fold cross-validation.ResultsResults indicated that it was possible to classify the outcome of the HUT with sensitivity of 58.8%, specificity of 63.3% and an accuracy of 60.9%. Using a multivariate classifier it was possible to identify those with a positive diagnosis of VVS with a sensitivity of 84.3%, specificity of 72.9% and an accuracy of 80.2%.ConclusionThis study highlights the existence of a unique AS hemodynamic response characterised by autonomic hypersensitivity exhibited by young patients prone to VVS which is detectable using a multi-parameter machine learning framework. With further verification, this approach may have applications in syncope and falls diagnosis, population studies and the tracking of treatment efficacy.

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