Uptake and 4-week quit rates from an opt-out co-located smoking cessation service delivered alongside community-based low-dose computed tomography screening within the Yorkshire Lung Screening Trial.

BACKGROUND: Up to 50% of those attending for low-dose computed tomography screening for lung cancer continue to smoke and co-delivery of smoking cessation services alongside screening may maximise clinical benefit. Here we present data from an opt-out co-located smoking cessation service delivered alongside the Yorkshire Lung Screening Trial (YLST). METHODS: Eligible YLST participants were offered an immediate consultation with a smoking cessation practitioner (SCP) at their screening visit with ongoing smoking cessation support over subsequent weeks. RESULTS: Of 2150 eligible participants, 1905 (89%) accepted the offer of an SCP consultation during their initial visit, with 1609 (75%) receiving ongoing smoking cessation support over subsequent weeks. Uptake of ongoing support was not associated with age, ethnicity, deprivation or educational level in multivariable analyses, although men were less likely to engage (adjusted OR (ORadj) 0.71, 95% CI 0.56-0.89). Uptake was higher in those with higher nicotine dependency, motivation to stop smoking and self-efficacy for quitting. Overall, 323 participants self-reported quitting at 4 weeks (15.0% of the eligible population); 266 were validated by exhaled carbon monoxide (12.4%). Multivariable analyses of eligible smokers suggested 4-week quitting was more likely in men (ORadj 1.43, 95% CI 1.11-1.84), those with higher motivation to quit and previous quit attempts, while those with a stronger smoking habit in terms of cigarettes per day were less likely to quit. CONCLUSIONS: There was high uptake for co-located opt-out smoking cessation support across a wide range of participant demographics. Protected funding for integrated smoking cessation services should be considered to maximise programme equity and benefit

Nurse-Led Medicines' Monitoring for Patients with Dementia in Care Homes: A Pragmatic Cohort Stepped Wedge Cluster Randomised Trial

People with dementia are susceptible to adverse drug reactions (ADRs). However, they are not always closely monitored for potential problems relating to their medicines: structured nurse-led ADR Profiles have the potential to address this care gap. We aimed to assess the number and nature of clinical problems identified and addressed and changes in prescribing following introduction of nurse-led medicines' monitoring.Pragmatic cohort stepped-wedge cluster Randomised Controlled Trial (RCT) of structured nurse-led medicines' monitoring versus usual care.Five UK private sector care homes.41 service users, taking at least one antipsychotic, antidepressant or anti-epileptic medicine.Nurses completed the West Wales ADR (WWADR) Profile for Mental Health Medicines with each participant according to trial step.Problems addressed and changes in medicines prescribed.Information was collected from participants' notes before randomisation and after each of five monthly trial steps. The impact of the Profile on problems found, actions taken and reduction in mental health medicines was explored in multivariate analyses, accounting for data collection step and site.Five of 10 sites and 43 of 49 service users approached participated. Profile administration increased the number of problems addressed from a mean of 6.02 [SD 2.92] to 9.86 [4.48], effect size 3.84, 95% CI 2.57-4.11, P <0.001. For example, pain was more likely to be treated (adjusted Odds Ratio [aOR] 3.84, 1.78-8.30), and more patients attended dentists and opticians (aOR 52.76 [11.80-235.90] and 5.12 [1.45-18.03] respectively). Profile use was associated with reduction in mental health medicines (aOR 4.45, 1.15-17.22).The WWADR Profile for Mental Health Medicines can improve the quality and safety of care, and warrants further investigation as a strategy to mitigate the known adverse effects of prescribed medicines.ISRCTN 48133332

Booms and busts in China's stock market: estimates based on fundamentals

This article empirically models China's stock prices using conventional fundamentals: corporate earnings, risk-free interest rate and a proxy for equity risk premium. It uses the estimated long-run stock price misalignments to date booms and busts, and analyses equity market reforms and excess liquidity as potential drivers of these stock price misalignments. Results show that China's equity prices can be well modelled using fundamentals, but that various booms and busts can be identified. Policy actions, either taking the form of deposit rate changes, equity market reforms or excess liquidity, have significantly contributed to these misalignments.