Pulse palpation has been recommended as the first step of screening to detect atrial fibrillation. We aimed to determine and compare the accuracy of different methods for detecting pulse irregularities caused by atrial fibrillation. We systematically searched MEDLINE, EMBASE, CINAHL and LILACS until 16 March 2015. Two reviewers identified eligible studies, extracted data and appraised quality using the QUADAS-2 instrument. Meta-analysis, using the bivariate hierarchical random effects method, determined average operating points for sensitivities, specificities, positive and negative likelihood ratios (PLR, NLR); we constructed summary receiver operating characteristic plots. Twenty-one studies investigated 39 interventions (n = 15,129 pulse assessments) for detecting atrial fibrillation. Compared to 12-lead electrocardiography (ECG) diagnosed atrial fibrillation, blood pressure monitors (BPMs; seven interventions) and non-12-lead ECGs (20 interventions) had the greatest accuracy for detecting pulse irregularities attributable to atrial fibrillation (BPM: sensitivity 0.98 (95% confidence interval (CI) 0.92–1.00), specificity 0.92 (95% CI 0.88–0.95), PLR 12.1 (95% CI 8.2–17.8) and NLR 0.02 (95% CI 0.00–0.09); non-12-lead ECG: sensitivity 0.91 (95% CI 0.86–0.94), specificity 0.95 (95% CI 0.92–0.97), PLR 20.1 (95% CI 12–33.7), NLR 0.09 (95% CI 0.06–0.14)). There were similar findings for smartphone applications (six interventions) although these studies were small in size. The sensitivity and specificity of pulse palpation (six interventions) were 0.92 (95% CI 0.85–0.96) and 0.82 (95% CI 0.76–0.88), respectively (PLR 5.2 (95% CI 3.8–7.2), NLR 0.1 (95% CI 0.05–0.18)). BPMs and non-12-lead ECG were most accurate for detecting pulse irregularities caused by atrial fibrillation; other technologies may therefore be pragmatic alternatives to pulse palpation for the first step of atrial fibrillation screening.

Aims: In pregnant smoking cessation trial participants, to estimate (1) among women abstinent at the end of pregnancy, the proportion who re‐start smoking at time‐points afterwards (primary analysis) and (2) among all trial participants, the proportion smoking at the end of pregnancy and at selected time‐points during the postpartum period (secondary analysis). Methods: Trials identified from two Cochrane reviews plus searches of Medline and EMBASE . Twenty‐seven trials were included. The included trials were randomized or quasi‐randomized trials of within‐pregnancy cessation interventions given to smokers who reported abstinence both at end of pregnancy and at one or more defined time‐points after birth. Outcomes were validated biochemically and self‐reported continuous abstinence from smoking and 7‐day point prevalence abstinence. The primary random‐effects meta‐analysis used longitudinal data to estimate mean pooled proportions of re‐starting smoking; a secondary analysis used cross‐sectional data to estimate the mean proportions smoking at different postpartum time‐points. Subgroup analyses were performed on biochemically validated abstinence. Results: The pooled mean proportion re‐starting at 6 months postpartum was 43% [95% confidence interval (CI) = 16–72%, I ² = 96.7%] (11 trials, 571 abstinent women). The pooled mean proportion smoking at the end of pregnancy was 87% (95% CI = 84–90%, I ² = 93.2%) and 94% (95% CI = 92–96%, I ² = 88%) at 6 months postpartum (23 trials, 9262 trial participants). Findings were similar when using biochemically validated abstinence. Conclusions: In clinical trials of smoking cessation interventions during pregnancy only 13% are abstinent at term. Of these, 43% re‐start by 6 months postpartum.

Aims: To estimate the effectiveness of pregnancy smoking cessation support delivered by short message service (SMS) text message and key parameters needed to plan a definitive trial. Design: Multi‐centre, parallel‐group, single‐blinded, individual randomized controlled trial. Setting: Sixteen antenatal clinics in England. Participants: Four hundred and seven participants were randomized to the intervention ( n = 203) or usual care ( n = 204). Eligible women were < 25 weeks gestation, smoked at least one daily cigarette (> 5 pre‐pregnancy), were able to receive and understand English SMS texts and were not already using text‐based cessation support. Intervention: All participants received a smoking cessation leaflet; intervention participants also received a 12‐week programme of individually tailored, automated, interactive, self‐help smoking cessation text messages (MiQuit). Outcome measurements: Seven smoking outcomes, including validated continuous abstinence from 4 weeks post‐randomization until 36 weeks gestation, design parameters for a future trial and cost‐per‐quitter. Findings: Using the validated, continuous abstinence outcome, 5.4% (11 of 203) of MiQuit participants were abstinent versus 2.0% (four of 204) of usual care participants [odds ratio (OR) = 2.7, 95% confidence interval (CI) = 0.93–9.35]. The Bayes factor for this outcome was 2.23. Completeness of follow‐up at 36 weeks gestation was similar in both groups; provision of self‐report smoking data was 64% (MiQuit) and 65% (usual care) and abstinence validation rates were 56% (MiQuit) and 61% (usual care). The incremental cost‐per‐quitter was £133.53 (95% CI = –£395.78 to 843.62). Conclusions: There was some evidence, although not conclusive, that a text‐messaging programme may increase cessation rates in pregnant smokers when provided alongside routine NHS cessation care.

Screening for atrial fibrillation (AF) in primary care has been recommended; however, the views of healthcare professionals (HCPs) are not known. This study aimed to determine the opinions of HCP about the feasibility of implementing screening within a primary care setting. A cross-sectional mixed methods census survey of 418 HCPs from 59 inner-city practices (Nottingham, UK) was conducted between October-December 2014. Postal and web-surveys ascertained data on existing methods, knowledge, skills, attitudes, barriers and facilitators to AF screening using Likert scale and open-ended questions. Responses, categorized according to HCP group, were summarized using proportions, adjusting for clustering by practice, with 95% C.Is and free-text responses using thematic analysis. At least one General Practitioner (GP) responded from 48 (81%) practices. There were 212/418 (51%) respondents; 118/229 GPs, 67/129 nurses [50 practice nurses; 17 Nurse Practitioners (NPs)], 27/60 healthcare assistants (HCAs). 39/48 (81%) practices had an ECG machine and diagnosed AF in-house. Non-GP HCPs reported having less knowledge about ECG interpretation, diagnosing and treating AF than GPs. A greater proportion of non-GP HCPs reported they would benefit from ECG training specifically for AF diagnosis than GPs [proportion (95% CI) GPs: 11.9% (6.8–20.0); HCAs: 37.0% (21.7–55.5); nurses: 44.0% (30.0–59.0); NPs 41.2% (21.9–63.7)]. Barriers included time, workload and capacity to undertake screening activities, although training to diagnose and manage AF was a required facilitator. Inner-city general practices were found to have adequate access to resources for AF screening. There is enthusiasm by non-GP HCPs to up-skill in the diagnosis and management of AF and they may have a role in future AF screening. However, organisational barriers, such as lack of time, staff and capacity, should be overcome for AF screening to be feasibly implemented within primary care.

Aims To test efficacy of “MiQuit’, a tailored, self-help, text message stop smoking programme for pregnancy, as an adjunct to usual care (UC) for smoking cessation in pregnancy. Design Multicentre, open, two-arm, parallel-group, superiority randomised controlled trial (RCT) and a Trial Sequential Analysis (TSA) meta-analysis combining trial findings with two previous ones. Setting 24 English hospital antenatal clinics. Participants 1002 pregnant women who were ≥16 years old, were ≤ 25 weeks gestation, and smoked ≥ one daily cigarette and accepted information on cessation with no requirement to set quit dates. Interventions UC or UC plus ‘MiQuit’: 12 weeks of tailored, smoking cessation text messages focussed on inducing and aiding cessation. Measurements Primary outcome: biochemically-validated cessation between 4 weeks after randomisation and late pregnancy. Secondary outcomes: shorter and non-validated abstinence periods, pregnancy outcomes and incremental cost-effectiveness ratios. Findings RCT: cessation was 5.19% (26/501) and 4.59% (23/501) in MiQuit and UC groups [adjusted odds ratio (adj OR) for quitting with MiQuit versus UC, 95% confidence interval (CI), 1.15 (0.65 to 2.04)]; other abstinence findings were similar, with higher point estimates. Primary outcome ascertainment was 61.7% (309) and 67.3% (337) in MiQuit and UC groups with 71.1% (54/76) and 69.5% (41/59) abstinence validation rates, respectively. Pregnancy outcomes were similar and the incremental cost per Quality-Adjusted Life Year was -£1,118 (95% CI -£4,806 to £1,911). More MiQuit group women reported making at least one quit attempt (adj OR (95% CI) for making an attempt, 1.50 (1.07 to 2.09).TSA Meta-analysis: This found no significant difference in prolonged abstinence between MiQuit and UC (pooled OR 1.49, adjusted 95% CI 0.62 to 3.60). Conclusions Irrespective of whether they want to try quitting, when offered a tailored, self-help, text message stop smoking programme for pregnancy (MiQuit) as an adjunct to usual care, pregnant women are not more likely to stop smoking until childbirth but they report more attempts at stopping smoking.