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Prior studies report a greater incidence of second primary malignancy (SPM) among patients with myeloproliferative neoplasms, although the true risk in primary myelofibrosis (PMF) has not been elucidated. We utilized the Surveillance, Epidemiology, and End Results database to evaluate the risk of SPM in PMF patients and analyzed the effects of sociodemographic factors on the risk of SPM. Out of 5273 patients, 385 patients (7.30%) developed SPM. SPM occurred at SIR of 1.95 (95% CI 1.76-2.15) and AER of 149.01 per 10,000 population. A significantly higher incidence of melanoma (SIR 1.76, 95% CI 1.01-2.86), lymphoma (SIR 3.38, 95% CI 2.28-4.83), and leukemia (SIR 27.19, 95% CI 23.09-31.81) was observed. The risk was significantly higher in patients ≤60 years, males, chemotherapy recipients, within 5 years of PMF diagnosis, and for PMF diagnosed after 2009.

Background:\ud Mortality remains unacceptably high in patients with heart failure and reduced left ventricular ejection fraction (LVEF) despite advances in therapeutics. We hypothesised that a novel artificial intelligence approach could better assess multiple and higher-dimension interactions of comorbidities, and define clusters of β-blocker efficacy in patients with sinus rhythm and atrial fibrillation.\ud Methods:\ud Neural network-based variational autoencoders and hierarchical clustering were applied to pooled individual patient data from nine double-blind, randomised, placebo-controlled trials of β blockers. All-cause mortality during median 1·3 years of follow-up was assessed by intention to treat, stratified by electrocardiographic heart rhythm. The number of clusters and dimensions was determined objectively, with results validated using a leave-one-trial-out approach. This study was prospectively registered with ClinicalTrials.gov (NCT00832442) and the PROSPERO database of systematic reviews (CRD42014010012).\ud Findings:\ud 15 659 patients with heart failure and LVEF of less than 50% were included, with median age 65 years (IQR 56–72) and LVEF 27% (IQR 21–33). 3708 (24%) patients were women. In sinus rhythm (n=12 822), most clusters demonstrated a consistent overall mortality benefit from β blockers, with odds ratios (ORs) ranging from 0·54 to 0·74. One cluster in sinus rhythm of older patients with less severe symptoms showed no significant efficacy (OR 0·86, 95% CI 0·67–1·10; p=0·22). In atrial fibrillation (n=2837), four of five clusters were consistent with the overall neutral effect of β blockers versus placebo (OR 0·92, 0·77–1·10; p=0·37). One cluster of younger atrial fibrillation patients at lower mortality risk but similar LVEF to average had a statistically significant reduction in mortality with β blockers (OR 0·57, 0·35–0·93; p=0·023). The robustness and consistency of clustering was confirmed for all models (p

Background Machine learning (ML) is increasingly used in research for subtype definition and risk prediction, particularly in cardiovascular diseases. No existing ML models are routinely used for cardiovascular disease management, and their phase of clinical utility is unknown, partly due to a lack of clear criteria. We evaluated ML for subtype definition and risk prediction in heart failure (HF), acute coronary syndromes (ACS) and atrial fibrillation (AF). Methods For ML studies of subtype definition and risk prediction, we conducted a systematic review in HF, ACS and AF, using PubMed, MEDLINE and Web of Science from January 2000 until December 2019. By adapting published criteria for diagnostic and prognostic studies, we developed a seven-domain, ML-specific checklist. Results Of 5918 studies identified, 97 were included. Across studies for subtype definition (n = 40) and risk prediction (n = 57), there was variation in data source, population size (median 606 and median 6769), clinical setting (outpatient, inpatient, different departments), number of covariates (median 19 and median 48) and ML methods. All studies were single disease, most were North American (n = 61/97) and only 14 studies combined definition and risk prediction. Subtype definition and risk prediction studies respectively had limitations in development (e.g. 15.0% and 78.9% of studies related to patient benefit; 15.0% and 15.8% had low patient selection bias), validation (12.5% and 5.3% externally validated) and impact (32.5% and 91.2% improved outcome prediction; no effectiveness or cost-effectiveness evaluations). Conclusions Studies of ML in HF, ACS and AF are limited by number and type of included covariates, ML methods, population size, country, clinical setting and focus on single diseases, not overlap or multimorbidity. Clinical utility and implementation rely on improvements in development, validation and impact, facilitated by simple checklists. We provide clear steps prior to safe implementation of machine learning in clinical practice for cardiovascular diseases and other disease areas.

Importance: There is little evidence to support selection of heart rate control therapy in patients with permanent atrial fibrillation, in particular those with coexisting heart failure. Objective: To compare low-dose digoxin with bisoprolol (a β-blocker). Design, Setting, and Participants: Randomized, open-label, blinded end-point clinical trial including 160 patients aged 60 years or older with permanent atrial fibrillation (defined as no plan to restore sinus rhythm) and dyspnea classified as New York Heart Association class II or higher. Patients were recruited from 3 hospitals and primary care practices in England from 2016 through 2018; last follow-up occurred in October 2019. Interventions: Digoxin (n = 80; dose range, 62.5-250 μg/d; mean dose, 161 μg/d) or bisoprolol (n = 80; dose range, 1.25-15 mg/d; mean dose, 3.2 mg/d). Main Outcomes and Measures: The primary end point was patient-reported quality of life using the 36-Item Short Form Health Survey physical component summary score (SF-36 PCS) at 6 months (higher scores are better; range, 0-100), with a minimal clinically important difference of 0.5 SD. There were 17 secondary end points (including resting heart rate, modified European Heart Rhythm Association [EHRA] symptom classification, and N-terminal pro-brain natriuretic peptide [NT-proBNP] level) at 6 months, 20 end points at 12 months, and adverse event (AE) reporting. Results: Among 160 patients (mean age, 76 [SD, 8] years; 74 [46%] women; mean baseline heart rate, 100/min [SD, 18/min]), 145 (91%) completed the trial and 150 (94%) were included in the analysis for the primary outcome. There was no significant difference in the primary outcome of normalized SF-36 PCS at 6 months (mean, 31.9 [SD, 11.7] for digoxin vs 29.7 [11.4] for bisoprolol; adjusted mean difference, 1.4 [95% CI, −1.1 to 3.8]; P = .28). Of the 17 secondary outcomes at 6 months, there were no significant between-group differences for 16 outcomes, including resting heart rate (a mean of 76.9/min [SD, 12.1/min] with digoxin vs a mean of 74.8/min [SD, 11.6/min] with bisoprolol; difference, 1.5/min [95% CI, −2.0 to 5.1/min]; P = .40). The modified EHRA class was significantly different between groups at 6 months; 53% of patients in the digoxin group reported a 2-class improvement vs 9% of patients in the bisoprolol group (adjusted odds ratio, 10.3 [95% CI, 4.0 to 26.6]; P Conclusions and Relevance: Among patients with permanent atrial fibrillation and symptoms of heart failure treated with low-dose digoxin or bisoprolol, there was no statistically significant difference in quality of life at 6 months. These findings support potentially basing decisions about treatment on other end points.

Background: Transparent and robust real-world evidence sources are increasingly important for global health, including cardiovascular (CV) diseases. We aimed to identify global real-world data (RWD) sources for heart failure (HF), acute coronary syndrome (ACS), and atrial fibrillation (AF). Methods: We conducted a systematic review of publications with RWD pertaining to HF, ACS, and AF (2010–2018), generating a list of unique data sources. Metadata were extracted based on the source type (e.g., electronic health records, genomics, and clinical data), study design, population size, clinical characteristics, follow-up duration, outcomes, and assessment of data availability for future studies and linkage. Results: Overall, 11,889 publications were retrieved for HF, 10,729 for ACS, and 6,262 for AF. From these, 322 (HF), 287 (ACS), and 220 (AF) data sources were selected for detailed review. The majority of data sources had near complete data on demographic variables (HF: 94%, ACS: 99%, and AF: 100%) and considerable data on comorbidities (HF: 77%, ACS: 93%, and AF: 97%). The least reported data categories were drug codes (HF, ACS, and AF: 10%) and caregiver involvement (HF: 6%, ACS: 1%, and AF: 1%). Only a minority of data sources provided information on access to data for other researchers (11%) or whether data could be linked to other data sources to maximize clinical impact (20%). The list and metadata for the RWD sources are publicly available at www.escardio.org/bigdata. Conclusions: This review has created a comprehensive resource of CV data sources, providing new avenues to improve future real-world research and to achieve better patient outcomes.

Introduction Echocardiography is essential for the management of patients with atrial fibrillation (AF), but current methods are time consuming and lack any evidence of reproducibility. Purpose To compare conventional averaging of consecutive beats with an index beat approach, where systolic and diastolic measurements are taken once after two prior beats with a similar RR interval (not more than 60 ms difference). Methods Transthoracic echocardiography was performed using a standardized and blinded protocol in patients enrolled into the RAte control Therapy Evaluation in permanent AF randomised controlled trial (RATE-AF; NCT02391337). AF was confirmed in all patients with a preceding 12-lead ECG. A minimum of 30-beat loops were recorded. Left ventricular function was determined using the recommended averaging of 5 and 10 beats and using the index beat method, with observers blinded to clinical details. Complete loops were used to calculate the within-beat coefficient of variation (CV) and intraclass correlation coefficient (ICC) for Simpson's biplane left ventricular ejection fraction (LVEF), global longitudinal strain (GLS) and filling pressure (E/e'). Results 160 patients (median age 75 years (IQR 69–82); 46% female) were included, with median heart rate 100 beats/min (IQR 86–112). For LVEF, the index beat had the lowest CV of 32% compared to 51% for 5 consecutive beats and 53% for 10 consecutive beats (p Conclusion Index beat determination of left ventricular function improves reproducibility, saves time and does not compromise validity compared to conventional quantification in patients with heart failure and AF. After independent validation, the index beat method should be adopted into routine clinical practice. Comparison for measurement of E/e' Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Institute of Health Research UK

Introduction Early diagnosis of atrial fibrillation (AF) is essential to reduce complications such as stroke, and improve patient quality of life. Novel screening techniques using smartphone camera photoplethysmography (PPG) can be used for AF detection, but their clinical applicability remains unclear. Purpose To assess the diagnostic accuracy of smartphone PPG compared to conventional ECG for AF detection. Methods We performed a systematic review of MEDLINE, EMBASE, Cochrane library, and other databases (1980-October 2019), including any study or abstract where smartphone finger-tip PPG was compared with a reference ECG (1, 3 or 12-lead). Outcomes were sensitivity (SE), specificity (SP), positive and negative predictive value (PPV; NPV) and overall accuracy. Bivariate hierarchical random effects meta-analysis was performed for studies with confidence intervals for SE and SP, and funnel plots were used to identify publication bias. Study quality was assessed using the established QUADAS-2 tool by two independent graders. Results 1350 publications were screened, of which 17 studies were included in the systematic review (7 full text publications and 10 abstracts), providing 21 comparisons of accuracy for AF detection. Most studies were based in secondary care and small (range n=33 to 1095), with a total of 5469 participants including 1384 with AF. Only 4 studies were multicentre. Smartphone applications used were Cardiio Rhythm, Fibricheck, Preventicus and Heartbeats, with 7 studies not specifying the tool used. Overall SE and SP for AF detection were high, ranging from 76 to 100%, and 85 to 100% respectively. PPV ranged from 54 to 100% and NPV from 77 to 100%, with overall accuracy between 61 and 99%. The meta-analysis included 12 comparisons from 10 studies (n=2714; 936 with AF). The pooled SE was 93% (95% CI 90–96%) and SP 97% (95% CI 95–99%); Figure 1A. QUADAS-2 assessment demonstrated poor quality of studies overall, with a high or unclear risk of bias in at least one domain for all studies. There was clear evidence of publication bias; Figure 1B. Conclusions PPG offers the potential for large scale, non-invasive, patient-led screening of AF. However, current evidence is limited to biased, low quality studies often with unrealistic results for AF detection. These are insufficient to advise clinicians on the true value of current smartphone PPG technology. Figure 1. Meta-analysis & publication bias Funding Acknowledgement Type of funding source: Public grant(s) – EU funding. Main funding source(s): BigData@Heart EU/EFPIA IMI 116074.

Introduction Echocardiography is essential for the management of patients with atrial fibrillation (AF), but current methods are time consuming and lack any evidence of reproducibility. Purpose To compare conventional averaging of consecutive beats with an index beat approach, where systolic and diastolic measurements are taken once after two prior beats with a similar RR interval (not more than 60 ms difference). Methods Transthoracic echocardiography was performed using a standardized and blinded protocol in patients enrolled into the RAte control Therapy Evaluation in permanent AF randomised controlled trial (RATE-AF; NCT02391337). AF was confirmed in all patients with a preceding 12-lead ECG. A minimum of 30-beat loops were recorded. Left ventricular function was determined using the recommended averaging of 5 and 10 beats and using the index beat method, with observers blinded to clinical details. Complete loops were used to calculate the within-beat coefficient of variation (CV) and intraclass correlation coefficient (ICC) for Simpson’s biplane left ventricular ejection fraction (LVEF), global longitudinal strain (GLS) and filling pressure (E/e’). Results 160 patients (median age 75 years (IQR 69-82); 46% female) were included, with median heart rate 100 beats/min (IQR 86-112). For LVEF, the index beat had the lowest CV of 32% compared to 51% for 5 consecutive beats and 53% for 10 consecutive beats (p Conclusion Index beat determination of left ventricular function improves reproducibility, saves time and does not compromise validity compared to conventional quantification in patients with heart failure and AF. After independent validation, the index beat method should be adopted into routine clinical practice. Conflict of Interest Nothing to declare

Introduction Early diagnosis of atrial fibrillation (AF) is essential to reduce complications such as stroke, and improve patient quality of life. Novel screening techniques using smartphone camera photoplethysmography (PPG) can be used for AF detection, but their clinical applicability remains unclear. Our aim was to assess the diagnostic accuracy of smartphone PPG compared to conventional ECG for AF detection. Methods We performed a systematic review of MEDLINE, EMBASE, Cochrane library, and other databases (1980-October 2019), including any study or abstract where smartphone finger-tip PPG was compared with a reference ECG (1, 3 or 12-lead). Outcomes were sensitivity (SE), specificity (SP), positive and negative predictive value (PPV; NPV) and overall accuracy. Bivariate hierarchical random effects meta-analysis was performed for studies with confidence intervals for SE and SP, and funnel plots were used to identify publication bias. Study quality was assessed using the established QUADAS-2 tool by two independent graders. Results 1350 publications were screened, of which 17 studies were included in the systematic review (7 full text publications and 10 abstracts), providing 21 comparisons of accuracy for AF detection. Most studies were based in secondary care and small (range n=33 to 1095), with a total of 5469 participants including 1384 with AF. Only 4 studies were multi-centre. Smartphone applications used were Cardiio Rhythm, Fibricheck, Preventicus and Heartbeats, with 7 studies not specifying the tool used. Overall SE and SP for AF detection were high, ranging from 76 to 100%, and 85 to 100% respectively. PPV ranged from 54 to 100% and NPV from 77 to 100%, with overall accuracy between 61 and 99%. The meta-analysis included 12 comparisons from 10 studies (n=2714; 936 with AF). The pooled SE was 93% (95% CI 90-96%) and SP 97% (95-99%); Figure A. QUADAS-2 assessment demonstrated poor quality of studies overall, with a high or unclear risk of bias in at least one domain for all studies. There was clear evidence of publication bias; Figure B. Conclusions PPG offers the potential for large scale, non-invasive, patient-led screening of AF. However, current evidence is limited to biased, low quality studies often with unrealistic results for AF detection. These are insufficient to advise clinicians on the true value of current smartphone PPG technology. Conflict of Interest EU grant -BigData@Heart EU/EFPIA IMI 11607

Introduction: It remains unclear what percentage of abstracts proceed to manuscript publication and the characteristics that predict successful publication. This study aimed to determine factors associated with successful peer-reviewed publications following oral presentation at the American Society of Hematology (ASH) annual meeting. Methods: All oral abstract presentations (n=621) in the hematological malignancy category from 2016 ASH annual meeting were included in the study. Abstract publication was confirmed by searching for the publicly listed abstract on PubMed by title, first, and last author names, and institutional matching. We recorded time to online publication, US versus foreign journal publication, and journal impact factor by 3.5 years from 2016 ASH annual meeting. Abstracts characteristics that were analyzed also included number of authors, gender of first author, gender of last author, and single vs multi-institution studies. Gender of the first and last author was confirmed by looking at their biography details on their institutional website. Descriptive analysis was performed and an association between presenter's or last author's gender and publication matrix was analyzed using Chi-square tests. Results: Of the 621 abstracts, 350 (56%) were published in full text by three and a half years since the 2016 ASH annual meeting. The abstracts' average time to journal publication was 17.46 months (SD +/- 11.32) (Table 1). Of the published articles, 64% (223/350) were published in U.S. journals; mean impact factor for all publications was 14.46 (SD+/- 11.47).The median number of authors for published and unpublished abstracts were similar. Females presented 37% (228/621) of the abstracts and 35% (123/350) of the journal publications had female first author and 22% (77/350) had female last author. A total of 53.9% (123/228) abstracts presented by a female author were published versus 57.7% (227/393) abstracts presented by a male author (p= Conclusion: More than half of the oral abstracts were successfully published regardless of gender and number of authors. The rate of successful publication is higher for male authors even though there was no correlation between the gender of the first author to journal impact factor or time to publication. Our study highlights gender disparity in senior authorship, however this difference is not as wide in first authorship. Disclosures Jamshed: Takeda, Amgen and Celgene: Honoraria.

BACKGROUND: Remote ischaemic conditioning with transient ischaemia and reperfusion applied to the arm has been shown to reduce myocardial infarct size in patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). We investigated whether remote ischaemic conditioning could reduce the incidence of cardiac death and hospitalisation for heart failure at 12 months. METHODS: We did an international investigator-initiated, prospective, single-blind, randomised controlled trial (CONDI-2/ERIC-PPCI) at 33 centres across the UK, Denmark, Spain, and Serbia. Patients (age >18 years) with suspected STEMI and who were eligible for PPCI were randomly allocated (1:1, stratified by centre with a permuted block method) to receive standard treatment (including a sham simulated remote ischaemic conditioning intervention at UK sites only) or remote ischaemic conditioning treatment (intermittent ischaemia and reperfusion applied to the arm through four cycles of 5-min inflation and 5-min deflation of an automated cuff device) before PPCI. Investigators responsible for data collection and outcome assessment were masked to treatment allocation. The primary combined endpoint was cardiac death or hospitalisation for heart failure at 12 months in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT02342522) and is completed. FINDINGS: Between Nov 6, 2013, and March 31, 2018, 5401 patients were randomly allocated to either the control group (n=2701) or the remote ischaemic conditioning group (n=2700). After exclusion of patients upon hospital arrival or loss to follow-up, 2569 patients in the control group and 2546 in the intervention group were included in the intention-to-treat analysis. At 12 months post-PPCI, the Kaplan-Meier-estimated frequencies of cardiac death or hospitalisation for heart failure (the primary endpoint) were 220 (8·6%) patients in the control group and 239 (9·4%) in the remote ischaemic conditioning group (hazard ratio 1·10 [95% CI 0·91-1·32], p=0·32 for intervention versus control). No important unexpected adverse events or side effects of remote ischaemic conditioning were observed. INTERPRETATION: Remote ischaemic conditioning does not improve clinical outcomes (cardiac death or hospitalisation for heart failure) at 12 months in patients with STEMI undergoing PPCI. FUNDING: British Heart Foundation, University College London Hospitals/University College London Biomedical Research Centre, Danish Innovation Foundation, Novo Nordisk Foundation, TrygFonden. The ERIC-PPCI trial was funded by a British Heart Foundation clinical study grant (grant number CS/14/3/31002) and a University College London Hospitals/University College London Biomedical Research Centre clinical research grant. The CONDI-2 trial was funded by Danish Innovation Foundation grants (grant numbers 11-108354 and 11-115818), Novo Nordisk Foundation (grant number NNF13OC0007447), and TrygFonden (grant number 109624). DJH was supported by the British Heart Foundation (grant number FS/10/039/28270), the National Institute for Health Research (NIHR) Biomedical Research Centre at University College London Hospitals, the Duke-National University Singapore Medical School, the Singapore Ministry of Health’s National Medical Research Council under its Clinician Scientist-Senior Investigator scheme (grant number NMRC/CSA-SI/0011/2017) and its Collaborative Centre Grant scheme (grant number NMRC/CGAug16C006), and the Singapore Ministry of Education Academic Research Fund Tier 2 (grant number MOE2016-T2-2-021). HEB was supported by the Novo Nordisk Foundation (grant numbers NNF14OC0013337, NNF15OC0016674). RKK is supported by the Oxford NIHR Biomedical Centre. The research was also supported by the NIHR infrastructure at Leeds. The views expressed are those of the author(s) and not necessarily those of the National Health Service, the NIHR, or the Department of Health. This article is based on the work of COST Action EU-CARDIOPROTECTION (CA16225) and supported by COST (European Cooperation in Science and Technology). We thank all study personnel for their invaluable assistance. Sí

Background:\ud Moderate and moderately severe renal impairment are common in patients with heart failure and reduced ejection fraction, but whether beta-blockers are effective is unclear, leading to underuse of life-saving therapy.\ud \ud Objectives:\ud This study sought to investigate patient prognosis and the efficacy of beta-blockers according to renal function using estimated glomerular filtration rate (eGFR).\ud \ud Methods:\ud Analysis of 16,740 individual patients with left ventricular ejection fraction

11034 Background: We aimed to determine abstract characteristics associated with successful peer-reviewed publication after presentation at ASCO annual meeting in the women’s malignancy category (breast & gynecologic cancer). Awareness of this could help meeting organizers & attendees understand factors associated with impactful abstracts. Methods: All oral & poster abstracts (OA: n = 53 & PA: n = 527) in Breast (Loco/Regional/Adjuvant & Metastatic) & Gynecologic cancers category (2017 & 2018 meeting) were included. Subsequent publication was confirmed by searching PubMed by title, names of first & last authors for abstracts published by January 2021. Time to online publication, US or foreign journal publication & impact factor (IF) were recorded. We also recorded number of authors, single/ multi-institution studies & gender of first/ last author, which was confirmed by viewing biography details on their institutional websites. Descriptive analysis was performed & association between above factors & publication matrix was analyzed using multiple logistic regression model, Chi-square and t-test. Results: 45/53 OA (85%) & 269/527 PA (51%) were published in peer-reviewed journals. Median number of authors for published PA was 12 vs 11 for unpublished (p = 0.24). Females (F) presented 34% (18/53) OA & 49.3% (260/527) PA. 55% (143/260) PA presented by female authors & 47.1% (126/267) presented by male (M) authors (p = 0.073) were published. No difference in publication between single vs multi-institution studies (p = 0.76) for PA was noted. Average time to journal publication for OA & PA was 15.45 (SD +/- 3.37) & 17.73 (SD +/- 1.27) months (mo) respectively. Mean IF for OA was 27.95 (SD+/- 6.18) while for PA was 10.96 (SD+/- 1.75). For published OA, 33% (15/45) had female first & 29% (13/45) had female last authors. For published PA, 50.2% (135/269) had female first while only 37.5% (101/269) had female last authors. There was no association between gender of last author to IF (p = 0.39), single vs multi-institution study (p = 0.48) or time to publication (p = 0.44) for PA. Conclusions: More than 75% of OA & 50% of PA were successfully published regardless of gender, number of authors or institutions involved. We observe a slight disparity in senior authorship for females and although this was not statistically significant, we are encouraged that the gap is closing in first authorship.[Table: see text]

The drug fluorouracil (5-FU) is a widely used antimetabolite chemotherapy in the treatment of colorectal cancer. The gene uridine monophosphate synthetase (UMPS) is thought to be primarily responsible for conversion of 5-FU to active anticancer metabolites in tumor cells. Mutation or aberrant expression of UMPS may contribute to 5-FU resistance during treatment. We undertook a characterization of UMPS mRNA isoform expression and sequence variation in 5-FU-resistant cell lines and drug-naive or -exposed primary and metastatic tumors. We observed reciprocal differential expression of two UMPS isoforms in a colorectal cancer cell line with acquired 5-FU resistance relative to the 5-FU-sensitive cell line from which it was derived. A novel isoform arising as a consequence of exon skipping was increased in abundance in resistant cells. The underlying mechanism responsible for this shift in isoform expression was determined to be a heterozygous splice site mutation acquired in the resistant cell line. We developed sequencing and expression assays to specifically detect alternative UMPS isoforms and used these to determine that UMPS was recurrently disrupted by mutations and aberrant splicing in additional 5-FU-resistant colorectal cancer cell lines and colorectal tumors. The observed mutations, aberrant splicing and downregulation of UMPS represent novel mechanisms for acquired 5-FU resistance in colorectal cancer.

Background: Competency in electrocardiogram (ECG) interpretation is central to undergraduate and postgraduate clinical training. Studies have demonstrated ECGs are interpreted sub-optimally. Our study compares the effectiveness of two learning strategies to improve competence and confidence. Method: A 1-month prospective randomized study compared the strategies in two cohorts: undergraduate third year medical students and postgraduate foundation year one (FY1) doctors. Both had blinded randomization to one of these learning strategies: focused teaching program (FTP) and self-directed learning (SDL). All volunteers completed a confidence questionnaire before and after allocation learning strategy and an ECG recognition multiple choice question (MCQ) paper at the end of the learning period. Results: The FTP group of undergraduates demonstrated a significant difference in successfully interpreting “ventricular tachycardia” (P = 0.046) and “narrow complex tachycardia” (P = 0.009) than the SDL group. Participant confidence increased in both learning strategies. FTP confidence demonstrated a greater improvement than SDL for both cohorts. Conclusion: A dedicated teaching program can improve trainee confidence and competence in ECG interpretation. A larger benefit is observed in undergraduates and those undertaking a FTP. Cardiol Res. 2014;5(2):51-57 doi: http://dx.doi.org/10.14740/cr333e

Introduction The Electrocardiogram (ECG) is the most commonly used diagnostic test in modern medicine. 1 Competency in ECG interpretation is central to undergraduate and postgraduate clinical training and minimising potential adverse consequences on patient care. Several studies have demonstrated postgraduates interpret ECG’s sub-optimally. 2,3 Our study compares the effectiveness of two cost neutral learning strategies to improve competence and confidence in this core clinical skill. Method A prospective randomised study was carried out over a one-month period comparing the learning strategies in two cohorts: undergraduate 3 rd year medical students and postgraduate foundation year one (FY1) doctors.Both had blinded randomisation to one of these strategies; focused teaching program (FTP) and self-directed learning (SDL). All volunteers completed a confidence questionnaire on ECG interpretation before and after completing the intervention. Additionally, all undertook an ECG recognition multiple choice question (MCQ) paper at the end of the learning period to assess competence. Results A total of 21 FY1’s and 25 3rd year medical students participated. The undergraduates in the FTP group demonstrated a significant difference in successfully interpreting ‘Ventricular Tachycardia’ (p = 0.046) and ‘Narrow Complex Tachycardia’ (p = 0.009) than the SDL group. Overall, participant confidence increased in both groups in each cohort. The FTP group demonstrated a greater improvement in confidence compared to SDL in both cohorts. Conclusion A dedicated teaching program can improve trainee confidence and competence in ECG interpretation. A larger benefit is observed in those undertaking a focused teaching program. ECG interpretation can be improved at any training level, especially undergraduates with a dedicated teaching program. References Rubinstein J, Dhole A, Ferenchick G. Puzzle based teaching versus traditional instruction in electrocardiogram interpretation for medical students – a pilot study. BMC Medical Education 2009; 9(4):1–7 Sur D, Kaye L, Mikus M, Goad J, Morena A. Accuracy of electrocardiogram reading by family practice residents. Fam Med 2000; 32(5): 315–9 Jensen MSA, Thomasen JL, Jensen SE, Lauritzen T, Engberg M. Electrocardiogram interpretation in general practice. Family Practice 2005; 22:109–113

ObjectivesTimely diagnosis of atrial fibrillation (AF) is essential to reduce complications from this increasingly common condition. We sought to assess the diagnostic accuracy of smartphone camera photoplethysmography (PPG) compared with conventional electrocardiogram (ECG) for AF detection.MethodsThis is a systematic review of MEDLINE, EMBASE and Cochrane (1980–December 2020), including any study or abstract, where smartphone PPG was compared with a reference ECG (1, 3 or 12-lead). Random effects meta-analysis was performed to pool sensitivity/specificity and identify publication bias, with study quality assessed using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2) risk of bias tool.Results28 studies were included (10 full-text publications and 18 abstracts), providing 31 comparisons of smartphone PPG versus ECG for AF detection. 11 404 participants were included (2950 in AF), with most studies being small and based in secondary care. Sensitivity and specificity for AF detection were high, ranging from 81% to 100%, and from 85% to 100%, respectively. 20 comparisons from 17 studies were meta-analysed, including 6891 participants (2299 with AF); the pooled sensitivity was 94% (95% CI 92% to 95%) and specificity 97% (96%–98%), with substantial heterogeneity (pConclusionPPG provides a non-invasive, patient-led screening tool for AF. However, current evidence is limited to small, biased, low-quality studies with unrealistically high sensitivity and specificity. Further studies are needed, preferably independent from manufacturers, in order to advise clinicians on the true value of PPG technology for AF detection.

Additional file 1. Search terms and search strategy.

Additional file 6 Web Table 3. Subtype classification studies in other disease areas.

Additional file 2 Figure S1. PRISMA flow diagram.

Additional file 5. Methods and Results for scoping review.

Additional file 9. PRISMA checklist.

Additional file 7 Web Table 4. Risk prediction studies in other disease areas.

Additional file 9. PRISMA checklist.

Additional file 8 Web Table 5. Proposed methods for development and validation of ML.

Additional file 4 Web Table 2. Data extraction for included studies.

Additional file 4 Web Table 2. Data extraction for included studies.

Additional file 2 Figure S1. PRISMA flow diagram.

Additional file 6 Web Table 3. Subtype classification studies in other disease areas.

Additional file 1. Search terms and search strategy.

Additional file 3 Web Table 1. AI-TREE checklist.

Additional file 5. Methods and Results for scoping review.

Additional file 8 Web Table 5. Proposed methods for development and validation of ML.

Additional file 3 Web Table 1. AI-TREE checklist.