A prospective study on the prevalence of MASLD in people with type-2 diabetes in the community. Cost effectiveness of screening strategies.

BACKGROUND AND AIMS: As screening for the liver disease and risk-stratification pathways are not established in patients with type-2 diabetes mellitus (T2DM), we evaluated the diagnostic performance and the cost-utility of different screening strategies for MASLD in the community. METHODS: Consecutive patients with T2DM from primary care underwent screening for liver diseases, ultrasound, ELF score and transient elastography (TE). Five strategies were compared to the standard of care: ultrasound plus abnormal liver function tests (LFTs), Fibrosis score-4 (FIB-4), NAFLD fibrosis score, Enhanced liver fibrosis test (ELF) and TE. Standard of care was defined as abnormal LFTs prompting referral to hospital. A Markov model was built based on the fibrosis stage, defined by TE. We generated the cost per quality-adjusted life year (QALY) gained and calculated the incremental cost-effectiveness ratio (ICER) over a lifetime horizon. RESULTS: Of 300 patients, 287 were included: 64% (186) had MASLD and 10% (28) had other causes of liver disease. Patients with significant fibrosis, advanced fibrosis, and cirrhosis due to MASLD were 17% (50/287), 11% (31/287) and 3% (8/287), respectively. Among those with significant fibrosis classified by LSM≥8.1 kPa, false negatives were 54% from ELF and 38% from FIB-4. On multivariate analysis, waist circumference, BMI, AST levels and education rank were independent predictors of significant and advanced fibrosis. All the screening strategies were associated with QALY gains, with TE (148.73 years) having the most substantial gains, followed by FIB-4 (134.07 years), ELF (131.68 years) and NAFLD fibrosis score (121.25 years). In the cost-utility analysis, ICER was £2480/QALY for TE, £2541.24/QALY for ELF and £2059.98/QALY for FIB-4. CONCLUSION: Screening for MASLD in the diabetic population in primary care is cost-effective and should become part of a holistic assessment. However, traditional screening strategies, including FIB-4 and ELF, underestimate the presence of significant liver disease in this setting.

Scalable optical manufacture of dynamic structural colour in stretchable materials.

Structurally coloured materials that change their colour in response to mechanical stimuli are uniquely suited for optical sensing and visual communication1-4. The main barrier to their widespread adoption is a lack of manufacturing techniques that offer spatial control of the materials' nanoscale structures across macroscale areas. Here, by adapting Lippmann photography5, we report an approach for producing large-area, structurally coloured sheets with a rich and easily controlled design space of colour patterns, spectral properties, angular scattering characteristics and responses to mechanical stimuli. Relying on just a digital projector and commercially available photosensitive elastomers, our approach is fast, scalable, affordable and relevant for a wide range of manufacturing settings. We also demonstrate prototypes for mechanosensitive healthcare materials and colorimetric strain and stress sensing for human-computer interaction and robotics.

Estimating the Size of High-risk Populations for COVID-19 Mortality across 442 US Cities

Reducing COVID-19 illness and mortality for populations in the future will require equitable and effective risk-based allocations of scarce preventive resources, including early available vaccines. To aid in this effort, we develop a risk calculator for COVID-19 mortality based on various socio-demographic factors and pre-existing conditions for the US adult population by combining information from the UK-based OpenSAFELY study, with mortality rates by age and ethnicity available across US states. We tailor the tool to produce absolute risks for individuals in future time frames by incorporating information on pandemic dynamics at the community level as available from forecasting models. We apply this risk calculation model to available data on prevalence and co-occurrences of the risk-factors from a variety of data sources to project risk for the general adult population across 477 US cities (defined as Census Places) and for the 65 years and older Medicare population across 3,113 US counties, respectively. Validation analyses based on these projected risks and data on tens of thousands of recent deaths show that the model is well calibrated for the US population. Projections show that the model can identify relatively small fractions of the population (e.g. 4.3%) which will lead to a disproportionately large number of deaths (e.g. 49.8%), and thus will be useful for effectively targeting individuals for early vaccinations, but there will be wide variation in risk distribution across US communities. We provide a web-based tool for individualized risk calculations and interactive maps for viewing the city-, county- and state-level risk projections.

Opportunity to reduce transfer of patients with mild traumatic brain injury and intracranial hemorrhage to a Level 1 trauma center.

OBJECTIVE: Current guidelines do not address the disposition of patients with mild traumatic brain injury (TBI) and resultant intracranial hemorrhage (ICH). Emergency medicine clinicians working in hospitals without neurosurgery coverage typically transfer patients with both to a trauma center with neurosurgery capability. Evidence is accruing which demonstrates that the risk of neurologic decompensation depends on the type of ICH and as a result, not every patient may need to be transferred. The purpose of this study was to identify risk factors for admission among patients with mild TBI and ICH who were transferred from a community hospital to the emergency department (ED) of a Level 1 trauma center. METHODS: Study subjects were patients ≥18years of age who were transferred from a community hospital to the ED of an urban, academic Level 1 trauma center between April 1, 2015 and March 31, 2016, and with an isolated traumatic ICH. Patients who had an epidural hematoma, were deemed to require a trauma center's level of service, were found to have non-traumatic ICHs, or had a Glasgow Coma Scale of <13 were excluded. Using a multivariable logistic regression model, we sought to determine patient factors and Computed Tomography (CT) findings which were associated with admission (to the floor, intensive care unit, or operating room with neurosurgery) of the Level 1 trauma center. RESULTS: 644 transferred patients were identified; 205 remained eligible after exclusion criteria. Presence of warfarin (odds ratio [OR] 4.09, 95% Confidence Interval [CI] 1.64, 10.25, p=0.0026) and a subdural hematoma (SDH) ≥1 cm (OR 6.28, 95% CI 1.24, 31.71, p=0.0263) were independently statistically significant factors predicting admission. Age, sex, GCS, presence of neurologic deficit, aspirin use, clopidogrel use, SDH <1 cm, IPH, and SAH were each independently not significant predictive factors of an admission. CONCLUSIONS: After controlling for factors, transferred patients with mild TBI with a SDH ≥1 cm or on warfarin have a higher odds ratio of requiring inpatient admission to a Level 1 trauma center. While these patients may require admission, there may be opportunities to develop and study a low risk traumatic intracranial hemorrhage protocol, which keeps a subgroup of patients with a mild TBI and resultant ICH at community hospitals with access to a nearby Level 1 trauma center.