Dynamic Relationship among Intraday Realized Volatility, Volume and Number of Trades

In this paper, the vector autoregressive model is fitted to find out the causal relationship among realized volatility, the number of transactions and volume with the intraday time intervals of 10, 20 and 30 min. To understand the impact of shock to the market on specific variables, a multivariate Impulse Response Function analysis is also introduced to visualize the causal relationship among the variables. From the analysis of a stock listed on the Stock Exchange of Hong Kong, we find that realized volatility reacts positively to the lagged average trade size. However, the realized volatility forms a negative relationship with the first few lagged number of trades. As a result, the intraday causal relationship among realized volatility, volume and the number of trades is quite different from that obtained on a daily basis. The findings of this paper can enhance the understanding of how the number of trades and the average trade size per transaction affect the risk evolution of financial securities and thus improve the risk management of day trading strategies. © 2010 Springer Science+Business Media, LLC

The hip in children with cerebral palsy: Predicting the outcome of soft tissue surgery

This study reviewed 56 hips in 37 children with cerebral palsy who had undergone an adductor tenotomy alone or in combination with an anterior obturator neurectomy. The mean review period was 5.3 years. At latest review, 25 of 30 (83%) hips with a preoperative migration percentage of less than 40% were reduced, but 20 of 26 (77%) hips with a preoperative migration percentage of 40% or more were subluxated or dislocated. Surgery was unsuccessful for 13 of 15 hips with an acetabular index of more than 27°. Percutaneous adductor tenotomy alone was as effective as the combination of an open procedure with an anterior obturator neurectomy. The age at the time of surgery did not have a significant effect on the outcome. The preoperative migration percentage was the only significant predictor of outcome in this group of children

Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study

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-enabled stethoscope can detect LVEF of 40% or lower. These findings highlight the potential for inexpensive, non-invasive, workflow-adapted, point-of-care screening, for earlier diagnosis and prognostically beneficial treatment. FUNDING: NHS Accelerated Access Collaborative, NHSX, and the National Institute for Health Research

Revascularisation or medical therapy in elderly patients with acute anginal syndromes (RINCAL) a randomised trial

Aims: To determine whether an intervention-guided strategy is superior to optimal medical therapy (OMT) for treating non-ST-elevation myocardial infarction (NSTEMI) in the elderly. Methods and results: Patients (≥80 years, chest pain, ischaemic ECG, and elevated troponin) were randomised 1:1 to an invasive strategy plus OMT versus OMT alone. The combined primary endpoint was all-cause mortality and non-fatal myocardial re-infarction at 1 year. We enrolled 251 patients (n=125 invasive vs. n=126 conservative) from May 2014 to September 2018. Almost half were female. The trial was terminated prematurely due to slow recruitment. A Kaplan-Meier estimate of event-free survival revealed no difference in the primary combined endpoint (invasive 18.5% [23/124] vs. conservative 22.2% [28/126]; p=0.39) or in all-cause mortality alone (invasive 10.5% [13/124] vs. conservative 11.1% [14/126]; p=0.88). There was less angina at 3 months (p<0.001) in the intervention arm. Non-fatal reinfarction (invasive 9.7% [12/124] vs. conservative 14.3% [18/126]; p=0.22) and unplanned revascularisation (invasive 1.6% [2/124] vs. conservative 6.4% [8/126]; p=0.10) were non-significantly more frequent after OMT alone. Conclusion: The trial was underpowered to provide a definitive conclusion regarding the primary endpoint. An intervention-guided strategy did, however, result in less angina, reinfarction and unplanned revascularisation but did not improve survival