Summary Background Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations to primary care with symptoms. We aimed to test an artificial intelligence (AI) algorithm applied to a single-lead ECG, recorded during ECG-enabled stethoscope examination, to validate a potential point-of-care screening tool for LVEF of 40% or lower. Methods We conducted an observational, prospective, multicentre study of a convolutional neural network (known as AI-ECG) that was previously validated for the detection of reduced LVEF using 12-lead ECG as input. We used AI-ECG retrained to interpret single-lead ECG input alone. Patients (aged ≥18 years) attending for transthoracic echocardiogram in London (UK) were recruited. All participants had 15 s of supine, single-lead ECG recorded at the four standard anatomical positions for cardiac auscultation, plus one handheld position, using an ECG-enabled stethoscope. Transthoracic echocardiogram-derived percentage LVEF was used as ground truth. The primary outcome was performance of AI-ECG at classifying reduced LVEF (LVEF ≤40%), measured using metrics including the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity, with two-sided 95% CIs. The primary outcome was reported for each position individually and with an optimal combination of AI-ECG outputs (interval range 0–1) from two positions using a rule-based approach and several classification models. This study is registered with ClinicalTrials.gov , NCT04601415 . Findings Between Feb 6 and May 27, 2021, we recruited 1050 patients (mean age 62 years [SD 17·4], 535 [51%] male, 432 [41%] non-White). 945 (90%) had an ejection fraction of at least 40%, and 105 (10%) had an ejection fraction of 40% or lower. Across all positions, ECGs were most frequently of adequate quality for AI-ECG interpretation at the pulmonary position (979 [93·3%] of 1050). Quality was lowest for the aortic position (846 [80·6%]). AI-ECG performed best at the pulmonary valve position (p=0·02), with an AUROC of 0·85 (95% CI 0·81–0·89), sensitivity of 84·8% (76·2–91·3), and specificity of 69·5% (66·4–72·6). Diagnostic odds ratios did not differ by age, sex, or non-White ethnicity. Taking the optimal combination of two positions (pulmonary and handheld positions), the rule-based approach resulted in an AUROC of 0·85 (0·81–0·89), sensitivity of 82·7% (72·7–90·2), and specificity of 79·9% (77·0–82·6). Using AI-ECG outputs from these two positions, a weighted logistic regression with l2 regularisation resulted in an AUROC of 0·91 (0·88–0·95), sensitivity of 91·9% (78·1–98·3), and specificity of 80·2% (75·5–84·3). Interpretation A deep learning system applied to single-lead ECGs acquired during a routine examination with an ECG...

ObjectiveThe reduction in circulating low-density lipoprotein cholesterol (LDL-c) is the primary aim of lipid-lowering therapies as a method of atherosclerotic cardiovascular disease risk reduction. Inclisiran is a new and potent lipid-lowering drug that is shown to be effective in reducing LDL-c in randomised controlled trials, however, real-world data of its use are not yet known. We sought to analyse the early effects of this drug in a tertiary centre lipid and cardiovascular risk clinic.MethodsWe performed a retrospective analysis of the first 80 patients who received a single dose of inclisiran at our lipid clinic between 1 December 2021 and 1 September 2022. Data were collected using electronic healthcare records. Baseline blood tests were taken prior to start of treatment and were repeated at 2 months follow-up. Data on adverse events were also recorded.ResultsAt 2 months after treatment initiation, mean baseline LDL-c fell from 3.5±1.1 mmol/L by 48.6% to 1.8±1.0 mmol/L and total cholesterol from 5.7±1.3 mmol/L by 33.3% to 3.8±1.1 mmol/L (both p<0.0001). Mean high-density lipoprotein-c rose by 7.7% to 1.4±0.4 mmol/L (p=0.02) and median triglycerides fell by 31.3% to 1.1 mmol/L (IQR 0.9–2) (p=0.001). Adverse events (injection site reaction, fatigue and headache) were recorded in three patients and all had self-resolved by time of follow-up.ConclusionInclisiran use in line with National Institute for Health and Care Excellence guidelines led to significant lowering of LDL-c at 2 months, with efficacy similar to that reported in trials with good tolerability.

Small intestinal bacterial overgrowth is a small bowel disorder characterised by excessive amounts of bacteria populating the small intestine leading to symptoms of abdominal pain, bloating and change in bowel habit. This creates some degree of diagnostic uncertainty due to the overlap of these symptoms with numerous other gastrointestinal conditions. Quantitative culture of jejunal aspirates is the gold standard diagnostic test but has largely been replaced by glucose and lactulose breath tests due to their relative ease and accessibility. The approach to treatment centres around reducing bacterial numbers through antibiotic therapy and managing any predisposing factors. Further research is required in order to define the optimum antibiotic choice and duration of therapy as well as the potential diagnostic utility of home breath testing and capsule-based technology.

Background: Patients with AF and likelihood of bleeding can undergo left atrial appendage occlusion (LAAO) as an alternative method of stroke prophylaxis. Short-term anti-thrombotic drugs are used post-procedure to offset the risk of device-related thrombus, evidence for this practice is limited. Objectives: To investigate optimal post-implant antithrombotic strategy in high bleeding-risk patients. Methods: Patients with AF and high-risk for both stroke and bleeding undergoing LAAO were advised their peri-operative drug therapy by a multi-disciplinary physician panel. Those deemed to be at higher risk of bleeding from anti-thrombotic drugs were assigned to minimal treatment with no antithrombotics or aspirin-alone. The remaining patients received standard care (STG)with a 12week course of dual-antiplatelets or anticoagulation post-implant. We compared mortality, device-related thrombus, ischemic stroke and bleeding events during the 90 days post-implant and long-term. Event-free survival was assessed using Kaplan-Meier survival analysis, with logrank testing for statistical significance. Results: 75 pts underwent LAAO of whom 63pts(84%) had a prior serious bleeding event. The 42pts on minimal treatment were older(74.3±7.7vs71.2±7.2) with higher HASBLED score (3.6±0.9vs3.3±1.2) than the 33pts having standard care. There were no device-related thrombi or strokes in either group at 90 days post-procedure; STG had more bleeding events (5/33vs0/42,p=0.01) with associated deaths (3/33vs0/42,p=0.05). During long-term follow up (median 2.2yrs), all patients transitioned onto no antithrombotic drugs (43pts(61%)) or a single-antiplatelet (29pts(39%)). There was no evidence of early minimal treatment adversely affecting long-term outcomes. Conclusions: Short-term anti-thrombotic drugs may not be needed after LAAO implant in patients with high bleeding risk and could be harmful. Larger, prospective studies would be warranted to test these findings.

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