Patients with severe acute‐on‐chronic liver failure are disadvantaged by model for end‐stage liver disease‐based organ allocation policy

Background: Mortality for patients with acute‐on‐chronic liver failure (ACLF) may be underestimated by the model for end‐stage liver disease‐sodium (MELD‐Na) score. / Aim: To assess waitlist outcomes across varying grades of ACLF among a cohort of patients listed with a MELD‐Na score ≥35, and therefore having similar priority for liver transplantation. / Methods: We analysed the United Network for Organ Sharing (UNOS) database, years 2010‐2017. Waitlist outcomes were evaluated using Fine and Gray's competing risks regression. / Results: We identified 6342 candidates at listing with a MELD‐Na score ≥35, of whom 3122 had ACLF‐3. Extra‐hepatic organ failures were present primarily in patients with four to six organ failures. Competing risks regression revealed that candidates listed with ACLF‐3 had a significantly higher risk for 90‐day waitlist mortality (Sub‐hazard ratio (SHR) = 1.41; 95% confidence interval [CI] 1.12‐1.78) relative to patients with lower ACLF grades. Subgroup analysis of ACLF‐3 revealed that both the presence of three organ failures (SHR = 1.40, 95% CI 1.20‐1.63) or four to six organ failures at listing (SHR = 3.01; 95% CI 2.54‐3.58) was associated with increased waitlist death. Candidates with four to six organ failures also had the lowest likelihood of receiving liver transplantation (SHR = 0.61, 95% CI 0.54‐0.68). The Share 35 rule was associated with reduced 90‐day waitlist mortality among the full cohort of patients listed with ACLF‐3 and MELD‐Na score ≥35 (SHR = 0.59; 95% CI 0.49‐0.70). However, Share 35 rule implementation was not associated with reduced waitlist mortality among patients with four to six organ failures (SHR = 0.76; 95% CI 0.58‐1.02). / Conclusion: The MELD‐Na score disadvantages patients with ACLF‐3, both with and without extra‐hepatic organ failures. Incorporation of organ failures into allocation policy warrants further exploration

In-street wind direction variability in the vicinity of a busy intersection in central London

We present results from fast-response wind measurements within and above a busy intersection between two street canyons (Marylebone Road and Gloucester Place) in Westminster, London taken as part of the DAPPLE (Dispersion of Air Pollution and Penetration into the Local Environment; www.dapple.org.uk) 2007 field campaign. The data reported here were collected using ultrasonic anemometers on the roof-top of a building adjacent to the intersection and at two heights on a pair of lamp-posts on opposite sides of the intersection. Site characteristics, data analysis and the variation of intersection flow with the above-roof wind direction (θref) are discussed. Evidence of both flow channelling and recirculation was identified within the canyon, only a few metres from the intersection for along-street and across-street roof-top winds respectively. Results also indicate that for oblique rooftop flows, the intersection flow is a complex combination of bifurcated channelled flows, recirculation and corner vortices. Asymmetries in local building geometry around the intersection and small changes in the background wind direction (changes in 15-min mean θref of 5–10 degrees) were also observed to have profound influences on the behaviour of intersection flow patterns. Consequently, short time-scale variability in the background flow direction can lead to highly scattered in-street mean flow angles masking the true multi-modal features of the flow and thus further complicating modelling challenges

Early transplantation maximizes survival in severe acute-on-chronic liver failure: results of a Markov decision process model

BACKGROUND: Uncertainties exist surrounding the timing of liver transplantation (LT) among patients with acute-on-chronic liver failure grade 3 (ACLF-3), regarding whether to accept a marginal quality donor organ to allow for earlier LT or wait for either an optimal organ offer or improvement in the number of organ failures, in order to increase post-LT survival. METHODS: We created a Markov decision process model to determine the timing of LT among patients with ACLF-3 within 7 days of listing, to maximize overall one-year survival probability. RESULTS: We analyzed six groups of candidates with ACLF-3: patients age ≤60 or >60 years, patients with 3 organ failures alone or 4-6 organ failures, and hepatic or extrahepatic ACLF-3. Among all groups, LT yielded significantly greater overall survival probability versus remaining on the waiting list for even 1 additional day (p 60 years or with 4-6 organ failures. Probability of improvement from ACLF-3 to ACLF-2 does not influence these recommendations, as the likelihood of organ recovery was less than 10%. CONCLUSION: During the first week after listing for patients with ACLF-3, earlier LT in general is favored over waiting for an optimal quality donor organ or for recovery of organ failures, with the understanding that the analysis is limited to consideration of only these three variables. LAY SUMMARY: In the setting of grade three acute-on-chronic liver failure (ACLF-3), questions remain regarding the timing of transplantation in terms of whether to proceed with liver transplantation with a marginal donor organ versus waiting for an optimal liver, and whether to transplant a patient with ACLF-3 or wait until improvement to ACLF-2. In this study, we used a Markov decision process model to demonstrate that earlier transplantation of patients listed with ACLF-3 maximizes overall survival, as opposed to waiting for an optimal donor organ or for improvement in the number of organ failures

Barriers and facilitators to infection prevention and control in a neonatal unit in Zimbabwe – a theory-driven qualitative study to inform design of a behaviour change intervention

BACKGROUND: Hospital-acquired infection (HAI) is an increasing cause of neonatal morbidity/mortality in low-income settings. Hospital staff behaviours (e.g. hand hygiene) are key contributors to HAI. Understanding the drivers of these can inform interventions to improve infection prevention and control (IPC). AIM: To explore barriers/facilitators to IPC in a neonatal unit in Harare, Zimbabwe. METHODS: Interviews were conducted with fifteen staff members of neonatal and maternity units alongside ethnographic observations. The interview guide and data analysis were informed by the COM-B (Capability, Opportunity, Motivation-Behaviour) model and explored individual, socio-cultural, and organisational barriers/facilitators to IPC. Potential interventions were identified using the Behaviour-Change Wheel. FINDINGS: Enablers within Capability included awareness of IPC, and within Motivation beliefs that IPC was crucial to one's role, and concerns about consequences of poor IPC. Staff were optimistic that IPC could improve, contingent upon resource availability (Opportunity). Barriers included: limited knowledge of guidelines, no formal feedback on performance (Capability), lack of resources (Opportunity), often leading to improvisation and poor habit formation. Further barriers included the unit's hierarchy e.g. low engagement of cleaners and mothers in IPC, and staff witnessing implementation of poor practices by other team members (Opportunity). Potential interventions could include role-modelling, engaging mothers and staff across cadres, audit and feedback and flexible protocols (adaptable to water/handrub availability). CONCLUSIONS: Most barriers to IPC fell within Opportunity, whilst most enablers fell under Capability and Motivation. Theory-based investigation provides basis for systematically identifying and developing interventions to address barriers and enablers to IPC in low-income settings

The Atrial Fibrillation Risk Score for Hyperthyroidism Patients

Thyrotoxicosis (TT) is associated with an increase in both total and cardiovascu-lar mortality. One of the main thyrotoxicosis risks is Atrial Fibrillation (AF). Right AF predicts help medical personal prescribe the correct medicaments and correct surgical or radioiodine therapy. The main goal of this study is creating a method for practical treatment and diagnostic AF. This study proposes a new method for assessing the risk of occurrence atrial fibrillation for patients with TT. This method considers both the features of the complication and the specifics of the chronic disease. A model is created based on case histories of patients with thyrotoxicosis. We used Machine Learning methods for creating several models. Each model has advantages and disadvantages depending on the diagnostic and medical purposes. The resulting models show high results in the different metrics of the prediction of AF. These models interpreted and simple for use. Therefore, models can be used as part of the support and decision-making system (DSS) by medical specialists in the treatment and diagnostic of AF

Modelling microbiome recovery after antibiotics using a stability landscape framework

Treatment with antibiotics is one of the most extreme perturbations to the human microbiome. Even standard courses of antibiotics dramatically reduce the microbiome’s diversity and can cause transitions to dysbiotic states. Conceptually, this is often described as a ‘stability landscape’: the microbiome sits in a landscape with multiple stable equilibria, and sufficiently strong perturbations can shift the microbiome from its normal equilibrium to another state. However, this picture is only qualitative and has not been incorporated in previous mathematical models of the effects of antibiotics. Here, we outline a simple quantitative model based on the stability landscape concept and demonstrate its success on real data. Our analytical impulse-response model has minimal assumptions with three parameters. We fit this model in a Bayesian framework to data from a previous study of the year-long effects of short courses of four common antibiotics on the gut and oral microbiomes, allowing us to compare parameters between antibiotics and microbiomes, and further validate our model using data from another study looking at the impact of a combination of last-resort antibiotics on the gut microbiome. Using Bayesian model selection we find support for a long-term transition to an alternative microbiome state after courses of certain antibiotics in both the gut and oral microbiomes. Quantitative stability landscape frameworks are an exciting avenue for future microbiome modelling

A False Start in the Race Against Doping in Sport: Concerns With Cycling’s Biological Passport

Professional cycling has suffered from a number of doping scandals. The sport’s governing bodies have responded by implementing an aggressive new antidoping program known as the biological passport. Cycling’s biological passport marks a departure from traditional antidoping efforts, which have focused on directly detecting prohibited substances in a cyclist’s system. Instead, the biological passport tracks biological variables in a cyclist’s blood and urine over time, monitoring for fluctuations that are thought to indirectly reveal the effects of doping. Although this method of indirect detection is promising, it also raises serious legal and scientific concerns. Since its introduction, the cycling community has debated the reliability of indirect biological-passport evidence and the clarity, consistency, and transparency of its use in proving doping violations. Such uncertainty undermines the legitimacy of finding cyclists guilty of doping based on this indirect evidence alone. Antidoping authorities should address these important concerns before continuing to pursue doping sanctions against cyclists solely on the basis of their biological passports