Search

Background: Screening for atrial fibrillation (AF) using 12-lead-electrocardiograms (ECGs) has been recommended; however, the best method for interpreting ECGs to diagnose AF is not known. We compared accuracy of methods for diagnosing AF from ECGs. Methods: We searched MEDLINE, EMBASE, CINAHL and LILACS until March 24, 2014. 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) and enabled construction of Summary Receiver Operating Characteristic (SROC) plots. Results: 10 studies investigated 16 methods for interpreting ECGs (n = 55,376 participant ECGs). The sensitivity and specificity of automated software (8 studies; 9 methods) were 0.89 (95% C.I. 0.82–0.93) and 0.99 (95% C.I. 0.99–0.99), respectively; PLR 96.6 (95% C.I. 64.2–145.6); NLR 0.11 (95% C.I. 0.07–0.18). Indirect comparisons with software found healthcare professionals (5 studies; 7 methods) had similar sensitivity for diagnosing AF but lower specificity [sensitivity 0.92 (95% C.I. 0.81–0.97), specificity 0.93 (95% C.I. 0.76–0.98), PLR 13.9 (95% C.I. 3.5–55.3), NLR 0.09 (95% C.I. 0.03–0.22)]. Sub-group analyses of primary care professionals found greater specificity for GPs than nurses [GPs: sensitivity 0.91 (95% C.I. 0.68–1.00); specificity 0.96 (95% C.I. 0.89–1.00). Nurses: sensitivity 0.88 (95% C.I. 0.63–1.00); specificity 0.85 (95% C.I. 0.83–0.87)]. Conclusions: Automated ECG-interpreting software most accurately excluded AF, although its ability to diagnose this was similar to all healthcare professionals. Within primary care, the specificity of AF diagnosis from ECG was greater for GPs than nurses.

Background: 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. Methods: 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. Results: 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)). Conclusions: 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.

BACKGROUND: Single-item urges to smoke measures have been contemplated as important measures of nicotine dependence This study aimed to prospectively determine the relationships between measures of craving to smoke and smoking cessation, and compare their ability to predict cessation with the Heaviness of Smoking Index, an established measure of nicotine dependence. METHODS: We conducted a secondary analysis of data from the randomised controlled PORTSSS trial. Measures of nicotine dependence, ascertained before making a quit attempt, were the HSI, frequency of urges to smoke (FUTS) and strength of urges to smoke (SUTS). Self-reported abstinence at six months after quitting was the primary outcome measure. Multivariate logistic regression and Receiver Operating Characteristic (ROC) analysis were used to assess associations and abilities of the nicotine dependence measures to predict smoking cessation. RESULTS: Of 2,535 participants, 53.5% were female; the median (Interquartile range) age was 38 (28–50) years. Both FUTS and HSI were inversely associated with abstinence six months after quitting; for each point increase in HSI score, participants were 16% less likely to have stopped smoking (OR 0.84, 95% C.I 0.78-0.89, p < 0.0001). Compared to participants with the lowest possible FUTS scores, those with greater scores had generally lower odds of cessation (p across frequency of urges categories=0.0026). SUTS was not associated with smoking cessation. ROC analysis suggested the HSI and FUTS had similar predictive validity for cessation. CONCLUSIONS: Higher FUTS and HSI scores were inversely associated with successful smoking cessation six months after quit attempts began and both had similar validity for predicting cessation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13011-015-0011-8) contains supplementary material, which is available to authorized users.

Introduction: 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. Methods: 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. Results: 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. Conclusion: 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 p

BACKGROUND: The SNAP (Smoking and Nicotine in Pregnancy) trial compared nicotine replacement therapy (NRT) patches with placebo in pregnant smokers; although NRT doubled cessation rates in the first 4 weeks, by delivery no differences in maternal smoking or birth outcomes were noted. As a result, NRT used in standard doses during pregnancy is considered ineffective for smoking cessation. Subsequent effects of NRT on the children of treated mothers are unknown because no trials have investigated the effect of gestational NRT use beyond birth. To assess whether NRT use in pregnancy might cause harm to infants, we aimed to compare effects of NRT and placebo on infant development 2 years after delivery. METHODS: 1050 pregnant smokers aged 16-45 years, at 12-24 weeks' gestation, and smoking at least five cigarettes per day were recruited from seven hospitals in England between May 1, 2007, and Feb 26, 2010, and followed up until their infants were 2 years old. Participants were randomly assigned (1:1) to receive up to 8-weeks treatment with NRT (15 mg/16 h transdermal patches) or identically packaged and visually matched placebo patches (all patches manufactured by and purchased at market rate from United Pharmaceuticals, Amman, Jordan), issued as two 4-week supplies (521 for NRT group, 529 for placebo group) [Corrected]. Randomisation was stratified by site with participants, health-care professionals, and research staff masked to treatment allocation. The primary results for participants and infants at delivery were published in 2012; we present results from the trial cohort 2 years after birth. After delivery, questionnaires were posted to participants and, if there was no response, to family physicians. The primary outcome at 2 years was infants' survival without developmental impairment (ie, no disability or problems with behaviour or development). Treatment groups were compared on an intention-to-treat basis. The trial is registered with Controlled-Trials.com, numb

Introduction: The Heaviness of Smoking Index (HSI) is validated to measure nicotine dependence in nonpregnant smokers, and in these smokers, mean salivary and serum cotinine levels are related by a ratio of 1.25. However, as nicotine metabolism increases during gestation, these findings may differ in pregnancy. We investigated the validity of HSI in pregnancy by comparing this with 3 biochemical measures; and in a search for a less-invasive cotinine measure in pregnancy, we also explored the relationship between mean blood and salivary cotinine levels. Methods: Cross-sectional analyses using baseline data from the Smoking, Nicotine, and Pregnancy Trial. Participants were 16–46 years old, 12–24 weeks gestation, smoked more than 5 cigarettes per day and had exhaled carbon monoxide (CO) readings of at least 8 ppm. Linear regression was used to examine correlations between HSI and blood cotinine, and salivary cotinine and exhaled CO. Correlation between blood and salivary cotinine was investigated using linear regression through the origin. Results: HSI scores were associated with blood cotinine (R2 = 0.20, n = 662, p < .001), salivary cotinine (R2 = 0.11, n = 967, p < .001), and exhaled CO (R2 = 0.13, n = 1,050, p < .001). Salivary and blood cotinine levels, taken simultaneously, were highly correlated (R2 = 0.91, n = 628, p < .001) and the saliva:blood level ratio was 1.01 (95% CI 0.99–1.04). Conclusions: Correlations between HSI and biochemical measures in pregnancy were comparable with those obtained outside pregnancy, suggesting that HSI has similar validity in pregnant smokers. Salivary and blood cotinine levels are roughly equivalent in pregnant smokers.

BACKGROUND: Smoking during pregnancy causes many adverse pregnancy and birth outcomes. Nicotine replacement therapy (NRT) is effective for cessation outside pregnancy but efficacy and safety in pregnancy are unknown. We hypothesised that NRT would increase smoking cessation in pregnancy without adversely affecting infants. OBJECTIVES: To compare (1) at delivery, the clinical effectiveness and cost-effectiveness for achieving biochemically validated smoking cessation of NRT patches with placebo patches in pregnancy and (2) in infants at 2 years of age, the effects of maternal NRT patch use with placebo patch use in pregnancy on behaviour, development and disability. DESIGN: Randomised, placebo-controlled, parallel-group trial and economic evaluation with follow-up at 4 weeks after randomisation, delivery and until infants were 2 years old. Randomisation was stratified by centre and a computer-generated sequence was used to allocate participants using a 1 : 1 ratio. Participants, site pharmacies and all study staff were blind to treatment allocation. SETTING: Seven antenatal hospitals in the Midlands and north-west England. PARTICIPANTS: Women between 12 and 24 weeks' gestation who smoked ≥ 10 cigarettes a day before and ≥ 5 during pregnancy, with an exhaled carbon monoxide (CO) reading of ≥ 8 parts per million (p.p.m.). INTERVENTIONS: NRT patches (15 mg per 16 hours) or matched placebo as an 8-week course issued in two equal batches. A second batch was dispensed at 4 weeks to those abstinent from smoking. MAIN OUTCOME MEASURES: PARTICIPANTS: self-reported, prolonged abstinence from smoking between a quit date and childbirth, validated at delivery by CO measurement and/or salivary cotinine (COT) (primary outcome). Infants, at 2 years: absence of impairment, defined as no disability or problems with behaviour and development. Economic: cost per 'quitter'. RESULTS: One thousand and fifty women enrolled (521 NRT, 529 placebo). There were 1010 live singleton births and 12

The optimal management of hypertension in people with dementia is uncertain. This review explores if people with dementia experience greater adverse effects from antihypertensive medications, if cognitive function is protected or worsened by controlling blood pressure (BP) and if there are subgroups of people with dementia for whom antihypertensive therapy is more likely to be harmful. Robust evidence is scant, trials of antihypertensive medications have generally excluded those with dementia. Observational data show changes in risk association over the life course, with high BP being a risk factor for cognitive decline in mid-life, while low BP is predictive in later life. It is therefore possible that excessive BP lowering in older people with dementia might harm cognition. From the existing literature, there is no direct evidence of benefit or harm from treating hypertension in people with dementia. So what practical steps can the clinician take? Assess capacity, establish patient preferences when making treatment decisions, use ambulatory monitoring to thoroughly assess BP, individualise and consider deprescribing where side effects (e.g. hypotension) outweigh the benefits. Future research might include pragmatic randomised trials of targeted deprescribing, which include patient-centred outcome measures to help support decision-making and studies to address mechanistic uncertainties.

OBJECTIVES: A purpose of the Hypertension in Dementia feasibility study was to explore recruitment of people with dementia and essential hypertension in primary care practices to prepare a withdrawal study of their antihypertensive medication. METHODS: Primary care practices were invited by phone to support the study, which would entail screening their databases to identify people with diagnoses of both dementia and essential hypertension, and sending out letters to these people asking them to indicate their willingness participate in the feasibility withdrawal study. Practice managers or GPs from practices that declined to support the study were asked to give their reasons. RESULTS: All primary care practices in Nottingham and Nottinghamshire were contacted (n=145). Of those, 12 (8%) practices agreed to support the study. Between them they identified and sent out a total of 249 letters to potential participants. Of these 19 (7%) people responded and only 6 (2%) met the eligibility criteria for withdrawing antihypertensive medication. 80/133 (60%) non responding practices gave reasons for why they did not support the study: the most common responses were that 31 (39%) were ‘too busy’, staff changes or short staffed were cited in 11 (14%) and “too time consuming” was cited in 7 (9%). CONCLUSIONS: Recruitment of a sufficiently large and representative population for a larger trial would not be feasible in primary care practices using these methods, due to the high workload in UK primary care.

The optimal management of hypertension in people with dementia is uncertain. This review explores if people with dementia experience greater adverse effects from antihypertensive medications, if cognitive function is protected or worsened by controlling blood pressure (BP) and if there are subgroups of people with dementia for whom antihypertensive therapy is more likely to be harmful. Robust evidence is scant, trials of antihypertensive medications have generally excluded those with dementia. Observational data show changes in risk association over the life course, with high BP being a risk factor for cognitive decline in mid-life, while low BP is predictive in later life. It is therefore possible that excessive BP lowering in older people with dementia might harm cognition. From the existing literature, there is no direct evidence of benefit or harm from treating hypertension in people with dementia. So what practical steps can the clinician take? Assess capacity, establish patient preferences when making treatment decisions, use ambulatory monitoring to thoroughly assess BP, individualise and consider deprescribing where side effects (e.g. hypotension) outweigh the benefits. Future research might include pragmatic randomised trials of targeted deprescribing, which include patient-centred outcome measures to help support decision-making and studies to address mechanistic uncertainties.

Background: Screening for atrial fibrillation (AF) using 12-lead-electrocardiograms (ECGs) has been recommended; however, the best method for interpreting ECGs to diagnose AF is not known. We compared accuracy of methods for diagnosing AF from ECGs. Methods: We searched MEDLINE, EMBASE, CINAHL and LILACS until March 24, 2014. 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) and enabled construction of Summary Receiver Operating Characteristic (SROC) plots. Results: 10 studies investigated 16 methods for interpreting ECGs (n = 55,376 participant ECGs). The sensitivity and specificity of automated software (8 studies; 9 methods) were 0.89 (95% C.I. 0.82–0.93) and 0.99 (95% C.I. 0.99–0.99), respectively; PLR 96.6 (95% C.I. 64.2–145.6); NLR 0.11 (95% C.I. 0.07–0.18). Indirect comparisons with software found healthcare professionals (5 studies; 7 methods) had similar sensitivity for diagnosing AF but lower specificity [sensitivity 0.92 (95% C.I. 0.81–0.97), specificity 0.93 (95% C.I. 0.76–0.98), PLR 13.9 (95% C.I. 3.5–55.3), NLR 0.09 (95% C.I. 0.03–0.22)]. Sub-group analyses of primary care professionals found greater specificity for GPs than nurses [GPs: sensitivity 0.91 (95% C.I. 0.68–1.00); specificity 0.96 (95% C.I. 0.89–1.00). Nurses: sensitivity 0.88 (95% C.I. 0.63–1.00); specificity 0.85 (95% C.I. 0.83–0.87)]. Conclusions: Automated ECG-interpreting software most accurately excluded AF, although its ability to diagnose this was similar to all healthcare professionals. Within primary care, the specificity of AF diagnosis from ECG was greater for GPs than nurses.

OBJECTIVES: A purpose of the Hypertension in Dementia feasibility study was to explore recruitment of people with dementia and essential hypertension in primary care practices to prepare a withdrawal study of their antihypertensive medication. METHODS: Primary care practices were invited by phone to support the study, which would entail screening their databases to identify people with diagnoses of both dementia and essential hypertension, and sending out letters to these people asking them to indicate their willingness participate in the feasibility withdrawal study. Practice managers or GPs from practices that declined to support the study were asked to give their reasons. RESULTS: All primary care practices in Nottingham and Nottinghamshire were contacted (n=145). Of those, 12 (8%) practices agreed to support the study. Between them they identified and sent out a total of 249 letters to potential participants. Of these 19 (7%) people responded and only 6 (2%) met the eligibility criteria for withdrawing antihypertensive medication. 80/133 (60%) non responding practices gave reasons for why they did not support the study: the most common responses were that 31 (39%) were ‘too busy’, staff changes or short staffed were cited in 11 (14%) and “too time consuming” was cited in 7 (9%). CONCLUSIONS: Recruitment of a sufficiently large and representative population for a larger trial would not be feasible in primary care practices using these methods, due to the high workload in UK primary care.

Background: 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. Methods: 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. Results: 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)). Conclusions: 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.

The optimal management of hypertension in people with dementia is uncertain. This review explores if people with dementia experience greater adverse effects from antihypertensive medications, if cognitive function is protected or worsened by controlling blood pressure (BP) and if there are subgroups of people with dementia for whom antihypertensive therapy is more likely to be harmful. Robust evidence is scant, trials of antihypertensive medications have generally excluded those with dementia. Observational data show changes in risk association over the life course, with high BP being a risk factor for cognitive decline in mid-life, while low BP is predictive in later life. It is therefore possible that excessive BP lowering in older people with dementia might harm cognition. From the existing literature, there is no direct evidence of benefit or harm from treating hypertension in people with dementia. So what practical steps can the clinician take? Assess capacity, establish patient preferences when making treatment decisions, use ambulatory monitoring to thoroughly assess BP, individualise and consider deprescribing where side effects (e.g. hypotension) outweigh the benefits. Future research might include pragmatic randomised trials of targeted deprescribing, which include patient-centred outcome measures to help support decision-making and studies to address mechanistic uncertainties.

Introduction Ischaemic heart disease (IHD) is one of the most common causes of death in the UK and treatment of patients with IHD costs the National Health System (NHS) billions of pounds each year. Allopurinol is a xanthine oxidase inhibitor used to prevent gout that also has several positive effects on the cardiovascular system. The ALL-HEART study aims to determine whether allopurinol improves cardiovascular outcomes in patients with IHD. Methods and Analysis The ALL-HEART study is a multicentre, controlled, prospective, randomised, open-label blinded end point (PROBE) trial of allopurinol (up to 600 mg daily) versus no treatment in a 1:1 ratio, added to usual care, in 5215 patients aged 60 years and over with IHD. Patients are followed up by electronic record linkage and annual questionnaires for an average of 4 years. The primary outcome is the composite of non-fatal myocardial infarction, non-fatal stroke or cardiovascular death. Secondary outcomes include all-cause mortality, quality of life and cost-effectiveness of allopurinol. The study will end when 631 adjudicated primary outcomes have occurred. The study is powered at 80% to detect a 20% reduction in the primary end point for the intervention. Patient recruitment to the ALL-HEART study started in February 2014. Ethics and Dissemination The study received ethical approval from the East of Scotland Research Ethics Service (EoSRES) REC 2 (13/ES/0104). The study is event-driven and results are expected after 2019. Results will be reported in peer-reviewed journals and at scientific meetings. Results will also be disseminated to guideline committees, NHS organisations and patient groups.

BACKGROUND: Single-item urges to smoke measures have been contemplated as important measures of nicotine dependence This study aimed to prospectively determine the relationships between measures of craving to smoke and smoking cessation, and compare their ability to predict cessation with the Heaviness of Smoking Index, an established measure of nicotine dependence. METHODS: We conducted a secondary analysis of data from the randomised controlled PORTSSS trial. Measures of nicotine dependence, ascertained before making a quit attempt, were the HSI, frequency of urges to smoke (FUTS) and strength of urges to smoke (SUTS). Self-reported abstinence at six months after quitting was the primary outcome measure. Multivariate logistic regression and Receiver Operating Characteristic (ROC) analysis were used to assess associations and abilities of the nicotine dependence measures to predict smoking cessation. RESULTS: Of 2,535 participants, 53.5% were female; the median (Interquartile range) age was 38 (28–50) years. Both FUTS and HSI were inversely associated with abstinence six months after quitting; for each point increase in HSI score, participants were 16% less likely to have stopped smoking (OR 0.84, 95% C.I 0.78-0.89, p < 0.0001). Compared to participants with the lowest possible FUTS scores, those with greater scores had generally lower odds of cessation (p across frequency of urges categories=0.0026). SUTS was not associated with smoking cessation. ROC analysis suggested the HSI and FUTS had similar predictive validity for cessation. CONCLUSIONS: Higher FUTS and HSI scores were inversely associated with successful smoking cessation six months after quit attempts began and both had similar validity for predicting cessation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13011-015-0011-8) contains supplementary material, which is available to authorized users.

Background: With a crisis in general practice recruitment, to maintain the current workforce, the Department of Health and Social Care quote a need for 50% of our medical students to choose general practice as a career. There is much variety between medical schools and Nottingham University, alongside most others does not achieve this. Aim: To increase the number of medical students at Nottingham University who would consider a career in general practice. Design and Setting: Innovative, paired careers tutorials embedded into a new 4-week general practice attachment at Nottingham University with student evaluation. Method: 2 paired careers tutorials, giving guided careers advice to 4th year medical students, using the strapline “General Practice can be whatever you want it to be….”. The tutorials promoted portfolio GPs and enabled students to look at their current career choice and how general practice could fit into that. Paired evaluation in week 1 and 4 was completed. Students were asked open-ended questions regarding current career choices and (using a 5 point Likert scale) whether: “General practice is a possible career choice for me”. Due to the new nature of the course, the first, of four cohorts was excluded from the evaluation to ensure standardised teaching and remove potential bias. The data analysed using the Wilcoxon signed rank test. Results: We surveyed 218 students with a response rate of 218(100%). At the end of the module, in the second careers tutorial, 80(36.7%) gave a higher score suggesting they were more likely to choose general practice as a future career, 107(49.1%) had no change in score and only 31(14.2%) provided a lower score. There was a significantly higher median score at the end of the attachment the median (IQR) pre-survey score was 3 (3-4) and the median (IQR) post-survey score was 4(3-5). P=<0.0001. Conclusion: Increasing medical student exposure to general practice with innovative, paired, careers tutorials increased the number of

Introduction: 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. Methods: 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. Results: 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. Conclusion: 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 p

Background: Screening for atrial fibrillation (AF) using 12-lead-electrocardiograms (ECGs) has been recommended; however, the best method for interpreting ECGs to diagnose AF is not known. We compared accuracy of methods for diagnosing AF from ECGs. Methods: We searched MEDLINE, EMBASE, CINAHL and LILACS until March 24, 2014. 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) and enabled construction of Summary Receiver Operating Characteristic (SROC) plots. Results: 10 studies investigated 16 methods for interpreting ECGs (n = 55,376 participant ECGs). The sensitivity and specificity of automated software (8 studies; 9 methods) were 0.89 (95% C.I. 0.82–0.93) and 0.99 (95% C.I. 0.99–0.99), respectively; PLR 96.6 (95% C.I. 64.2–145.6); NLR 0.11 (95% C.I. 0.07–0.18). Indirect comparisons with software found healthcare professionals (5 studies; 7 methods) had similar sensitivity for diagnosing AF but lower specificity [sensitivity 0.92 (95% C.I. 0.81–0.97), specificity 0.93 (95% C.I. 0.76–0.98), PLR 13.9 (95% C.I. 3.5–55.3), NLR 0.09 (95% C.I. 0.03–0.22)]. Sub-group analyses of primary care professionals found greater specificity for GPs than nurses [GPs: sensitivity 0.91 (95% C.I. 0.68–1.00); specificity 0.96 (95% C.I. 0.89–1.00). Nurses: sensitivity 0.88 (95% C.I. 0.63–1.00); specificity 0.85 (95% C.I. 0.83–0.87)]. Conclusions: Automated ECG-interpreting software most accurately excluded AF, although its ability to diagnose this was similar to all healthcare professionals. Within primary care, the specificity of AF diagnosis from ECG was greater for GPs than nurses.

Background: 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. Methods: 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. Results: 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)). Conclusions: 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.

Background Screening for atrial fibrillation (AF) has been recommended but is yet to be implemented in clinical practice. However, the most effective approaches for screening are not known and it is unclear if screening could feasibly be implemented in primary care. Aims and methods The overall aims were to determine how AF screening might feasibly and effectively be introduced into primary care in the United Kingdom (UK). Objectives were: 1) to determine the range and accuracies of methods for detecting pulse irregularities attributable to AF, 2) to determine the range and accuracies of methods for diagnosing AF using 12-lead electrocardiograms (ECGs) and 3) to investigate the feasibility and opinions of healthcare professionals (HCPs) in primary care about implementing AF screening. Three studies were undertaken: 1) a systematic review and meta-analysis of the diagnostic accuracy of methods for detecting pulse irregularities caused by AF, 2) a systematic review and meta-analysis of the diagnostic accuracy of methods for diagnosing AF using 12-lead ECG and 3) a survey of HCPs in primary care about screening implementation. Results Study 1: Blood pressure monitors (BPMs) and non-12-lead ECGs had the greatest accuracy for detecting pulse irregularities attributable to AF [BPM: sensitivity 0.98 (95% CI 0.92-1.00), specificity 0.92 (95% CI 0.88-0.95), positive likelihood ratio (PLR) 12.1 (95% C.I 8.2-17.8) and negative likelihood ratio (NLR) 0.02 (95% C.I 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% C.I 12-33.7), NLR 0.09 (95% C.I 0.06 to 0.14); there were similar findings for smart-phone applications although these studies were small in size. The sensitivity and specificity of pulse palpation were 0.92 (95% CI 0.85-0.96) and 0.82 (95% CI 0.76-0.88), respectively (PLR 5.2 (95% C.I 3.8-7.2), NLR 0.1 (0.05-0.18)]. Study 2: The sensitivity and specificity of automated software were 0.89 (95% CI 0.82-0

BACKGROUND: Single-item urges to smoke measures have been contemplated as important measures of nicotine dependence This study aimed to prospectively determine the relationships between measures of craving to smoke and smoking cessation, and compare their ability to predict cessation with the Heaviness of Smoking Index, an established measure of nicotine dependence. METHODS: We conducted a secondary analysis of data from the randomised controlled PORTSSS trial. Measures of nicotine dependence, ascertained before making a quit attempt, were the HSI, frequency of urges to smoke (FUTS) and strength of urges to smoke (SUTS). Self-reported abstinence at six months after quitting was the primary outcome measure. Multivariate logistic regression and Receiver Operating Characteristic (ROC) analysis were used to assess associations and abilities of the nicotine dependence measures to predict smoking cessation. RESULTS: Of 2,535 participants, 53.5% were female; the median (Interquartile range) age was 38 (28–50) years. Both FUTS and HSI were inversely associated with abstinence six months after quitting; for each point increase in HSI score, participants were 16% less likely to have stopped smoking (OR 0.84, 95% C.I 0.78-0.89, p < 0.0001). Compared to participants with the lowest possible FUTS scores, those with greater scores had generally lower odds of cessation (p across frequency of urges categories=0.0026). SUTS was not associated with smoking cessation. ROC analysis suggested the HSI and FUTS had similar predictive validity for cessation. CONCLUSIONS: Higher FUTS and HSI scores were inversely associated with successful smoking cessation six months after quit attempts began and both had similar validity for predicting cessation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13011-015-0011-8) contains supplementary material, which is available to authorized users.

BACKGROUND: Smoking during pregnancy causes many adverse pregnancy and birth outcomes. Nicotine replacement therapy (NRT) is effective for cessation outside pregnancy but efficacy and safety in pregnancy are unknown. We hypothesised that NRT would increase smoking cessation in pregnancy without adversely affecting infants. OBJECTIVES: To compare (1) at delivery, the clinical effectiveness and cost-effectiveness for achieving biochemically validated smoking cessation of NRT patches with placebo patches in pregnancy and (2) in infants at 2 years of age, the effects of maternal NRT patch use with placebo patch use in pregnancy on behaviour, development and disability. DESIGN: Randomised, placebo-controlled, parallel-group trial and economic evaluation with follow-up at 4 weeks after randomisation, delivery and until infants were 2 years old. Randomisation was stratified by centre and a computer-generated sequence was used to allocate participants using a 1 : 1 ratio. Participants, site pharmacies and all study staff were blind to treatment allocation. SETTING: Seven antenatal hospitals in the Midlands and north-west England. PARTICIPANTS: Women between 12 and 24 weeks' gestation who smoked ≥ 10 cigarettes a day before and ≥ 5 during pregnancy, with an exhaled carbon monoxide (CO) reading of ≥ 8 parts per million (p.p.m.). INTERVENTIONS: NRT patches (15 mg per 16 hours) or matched placebo as an 8-week course issued in two equal batches. A second batch was dispensed at 4 weeks to those abstinent from smoking. MAIN OUTCOME MEASURES: PARTICIPANTS: self-reported, prolonged abstinence from smoking between a quit date and childbirth, validated at delivery by CO measurement and/or salivary cotinine (COT) (primary outcome). Infants, at 2 years: absence of impairment, defined as no disability or problems with behaviour and development. Economic: cost per 'quitter'. RESULTS: One thousand and fifty women enrolled (521 NRT, 529 placebo). There were 1010 live singleton births and 12

BACKGROUND: The SNAP (Smoking and Nicotine in Pregnancy) trial compared nicotine replacement therapy (NRT) patches with placebo in pregnant smokers; although NRT doubled cessation rates in the first 4 weeks, by delivery no differences in maternal smoking or birth outcomes were noted. As a result, NRT used in standard doses during pregnancy is considered ineffective for smoking cessation. Subsequent effects of NRT on the children of treated mothers are unknown because no trials have investigated the effect of gestational NRT use beyond birth. To assess whether NRT use in pregnancy might cause harm to infants, we aimed to compare effects of NRT and placebo on infant development 2 years after delivery. METHODS: 1050 pregnant smokers aged 16-45 years, at 12-24 weeks' gestation, and smoking at least five cigarettes per day were recruited from seven hospitals in England between May 1, 2007, and Feb 26, 2010, and followed up until their infants were 2 years old. Participants were randomly assigned (1:1) to receive up to 8-weeks treatment with NRT (15 mg/16 h transdermal patches) or identically packaged and visually matched placebo patches (all patches manufactured by and purchased at market rate from United Pharmaceuticals, Amman, Jordan), issued as two 4-week supplies (521 for NRT group, 529 for placebo group) [Corrected]. Randomisation was stratified by site with participants, health-care professionals, and research staff masked to treatment allocation. The primary results for participants and infants at delivery were published in 2012; we present results from the trial cohort 2 years after birth. After delivery, questionnaires were posted to participants and, if there was no response, to family physicians. The primary outcome at 2 years was infants' survival without developmental impairment (ie, no disability or problems with behaviour or development). Treatment groups were compared on an intention-to-treat basis. The trial is registered with Controlled-Trials.com, numb

Introduction: 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. Methods: 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. Results: 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. Conclusion: 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 p

Introduction: The Heaviness of Smoking Index (HSI) is validated to measure nicotine dependence in nonpregnant smokers, and in these smokers, mean salivary and serum cotinine levels are related by a ratio of 1.25. However, as nicotine metabolism increases during gestation, these findings may differ in pregnancy. We investigated the validity of HSI in pregnancy by comparing this with 3 biochemical measures; and in a search for a less-invasive cotinine measure in pregnancy, we also explored the relationship between mean blood and salivary cotinine levels. Methods: Cross-sectional analyses using baseline data from the Smoking, Nicotine, and Pregnancy Trial. Participants were 16–46 years old, 12–24 weeks gestation, smoked more than 5 cigarettes per day and had exhaled carbon monoxide (CO) readings of at least 8 ppm. Linear regression was used to examine correlations between HSI and blood cotinine, and salivary cotinine and exhaled CO. Correlation between blood and salivary cotinine was investigated using linear regression through the origin. Results: HSI scores were associated with blood cotinine (R2 = 0.20, n = 662, p < .001), salivary cotinine (R2 = 0.11, n = 967, p < .001), and exhaled CO (R2 = 0.13, n = 1,050, p < .001). Salivary and blood cotinine levels, taken simultaneously, were highly correlated (R2 = 0.91, n = 628, p < .001) and the saliva:blood level ratio was 1.01 (95% CI 0.99–1.04). Conclusions: Correlations between HSI and biochemical measures in pregnancy were comparable with those obtained outside pregnancy, suggesting that HSI has similar validity in pregnant smokers. Salivary and blood cotinine levels are roughly equivalent in pregnant smokers.

Background: Screening for atrial fibrillation (AF) using 12-lead-electrocardiograms (ECGs) has been recommended; however, the best method for interpreting ECGs to diagnose AF is not known. We compared accuracy of methods for diagnosing AF from ECGs. Methods: We searched MEDLINE, EMBASE, CINAHL and LILACS until March 24, 2014. 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) and enabled construction of Summary Receiver Operating Characteristic (SROC) plots. Results: 10 studies investigated 16 methods for interpreting ECGs (n = 55,376 participant ECGs). The sensitivity and specificity of automated software (8 studies; 9 methods) were 0.89 (95% C.I. 0.82–0.93) and 0.99 (95% C.I. 0.99–0.99), respectively; PLR 96.6 (95% C.I. 64.2–145.6); NLR 0.11 (95% C.I. 0.07–0.18). Indirect comparisons with software found healthcare professionals (5 studies; 7 methods) had similar sensitivity for diagnosing AF but lower specificity [sensitivity 0.92 (95% C.I. 0.81–0.97), specificity 0.93 (95% C.I. 0.76–0.98), PLR 13.9 (95% C.I. 3.5–55.3), NLR 0.09 (95% C.I. 0.03–0.22)]. Sub-group analyses of primary care professionals found greater specificity for GPs than nurses [GPs: sensitivity 0.91 (95% C.I. 0.68–1.00); specificity 0.96 (95% C.I. 0.89–1.00). Nurses: sensitivity 0.88 (95% C.I. 0.63–1.00); specificity 0.85 (95% C.I. 0.83–0.87)]. Conclusions: Automated ECG-interpreting software most accurately excluded AF, although its ability to diagnose this was similar to all healthcare professionals. Within primary care, the specificity of AF diagnosis from ECG was greater for GPs than nurses.