Search

Postexercise heart rate recovery (HRR) is an important indicator of cardiac autonomic function and abnormal HRR is associated with adverse outcomes. We hypothesized that deep learning on resting electrocardiogram (ECG) tracings may identify individuals with impaired HRR.We trained a deep learning model (convolutional neural network) to infer HRR based on resting ECG waveforms (HRRAmong 56,793 individuals (mean age 57 years, 51% women), the HRRDeep learning-derived estimates of HRR using resting ECG independently associated with future clinical outcomes, including new-onset DM and all-cause mortality. Inferring postexercise heart rate response from a resting ECG may have potential clinical implications and impact on preventive strategies warrants future study.

BackgroundBetter understanding of global variation in simple tests of cognition and function would aid the delivery and interpretation of multi-national studies of the prevention of dementia and functional decline.MethodsWe aim to describe the variation in simple measures of cognition and function by world region, study, recruitment centre or individual level factors. In six RCTs that measured cognition with the mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), and instrumental activities of daily living (IADL) with the Standardised Assessment of Everyday Global Activities (SAGEA), we estimated average scores by global region with multilevel mixed-effects models. We estimated the proportion of participants with cognitive or functional impairment with previously defined thresholds (MMSE≤24 or MoCA≤25, SAGEA≥7), and with a country-standardised z-score threshold of cognitive or functional score of ≤-1.ResultsIn 91,396 participants (mean age 66.6±7.8 years, 31% females) from seven world regions, all global regions differed significantly in estimated cognitive function (z-score differences 0.11–0.45, pConclusionsAccounting for country-level factors reduced large differences between world regions in estimates of cognitive impairment. Measures of IADL were less variable across world regions, and could be used to better estimate dementia incidence in large studies.Impact statementWe certify that this work is novel. After analysing data from a large cohort of participants with a history of cardiovascular disease or cardiovascular risk factors, who were recruited in six international randomised controlled trials (RCTs) we found that accounting for country-level factors reduced large differences between world regions in estimates of cognitive impairment, while measures of functional impairment were less variable across world regions.Key PointsCognitive and functional test scores in randomized controlled clinical trial cohorts vary widely across world regions.The difference in cognitive test performance was large in comparison to difference in measures of activities of daily living (ADLs). Accounting for country-level factors reduced the differences between world regions in estimates of cognitive impairment.Cognitive test measures were less variable and could be used to better estimate dementia incidence in international studies.Why this study matters?We found that cognitive and functional test scores in RCT cohorts varied widely across world regions. The difference in cognitive test performance was large in comparison to difference in measures of activities of daily living. The impact of differences on the performance of cognitive tests, which were developed in high-income countries, creates challenges for harmonized studies of cognitive decline prevention in different world regions. Future studies using the same test around the world could standardise cognitive score by country, and consider using in addition measures of instrumental and basic activities of daily living, where there is less variation across world regions.

Electronic health record (EHR) datasets are statistically powerful but are subject to ascertainment bias and missingness. Using the Mass General Brigham multi-institutional EHR, we approximated a community-based cohort by sampling patients receiving longitudinal primary care between 2001-2018 (Community Care Cohort Project [C3PO], n = 520,868). We utilized natural language processing (NLP) to recover vital signs from unstructured notes. We assessed the validity of C3PO by deploying established risk models for myocardial infarction/stroke and atrial fibrillation. We then compared C3PO to Convenience Samples including all individuals from the same EHR with complete data, but without a longitudinal primary care requirement. NLP reduced the missingness of vital signs by 31%. NLP-recovered vital signs were highly correlated with values derived from structured fields (Pearson r range 0.95–0.99). Atrial fibrillation and myocardial infarction/stroke incidence were lower and risk models were better calibrated in C3PO as opposed to the Convenience Samples (calibration error range for myocardial infarction/stroke: 0.012–0.030 in C3PO vs. 0.028–0.046 in Convenience Samples; calibration error for atrial fibrillation 0.028 in C3PO vs. 0.036 in Convenience Samples). Sampling patients receiving regular primary care and using NLP to recover missing data may reduce bias and maximize generalizability of EHR research.

To characterize ATP-sensitive channels (KATP channels) benzopyrans with different substituents at position 6 were synthesized as new KATP-activators. Their relaxant potencies were determined in rat aorta and trachea. In aorta, pEC50-values (−log, M) ranged from 7.37 to 5.43; in trachea, pEC50-values were 0.3 to 0.8 log units lower. Functional data were compared with binding data obtained in calf tracheal cells using the cyanoguanidine [ 3 H ] P1075 (N-cyano-N′-1,1-dimethyl[2,3(n)- 3 H ]propyl)-N11-(3-pyridinyl)guanidine) as radioligand. A high correlation (r=0.96) between pEC50- and pKD-values indicated that tracheal relaxation produced by benzopyrans is mediated via KATP channels without signal amplification. The permanently charged trimethylammonium derivative designed as a probe for the membrane site of action completely lost its affinity for KATP channels, but converted to an antagonist for muscarinic acetylcholine receptors (pKB=6.12±0.10), as confirmed in radioligand binding studies (pKD=5.77±0.04). Structure–activity analyses revealed that the 6-substituent influences biological activity by a direct receptor interaction of its own and not indirectly by withdrawing electrons from the benzopyran nucleus. The variance of the biological activity is primarily determined by electrostatic properties, but desolvation energies additionally contribute.

Big data is important to new developments in global clinical science that aim to improve the lives of patients. Technological advances have led to the regular use of structured electronic health-care records with the potential to address key deficits in clinical evidence that could improve patient care. The COVID-19 pandemic has shown this potential in big data and related analytics but has also revealed important limitations. Data verification, data validation, data privacy, and a mandate from the public to conduct research are important challenges to effective use of routine health-care data. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including representation from patients, clinicians, scientists, regulators, journal editors, and industry members. In this Review, we propose the CODE-EHR minimum standards framework to be used by researchers and clinicians to improve the design of studies and enhance transparency of study methods. The CODE-EHR framework aims to develop robust and effective utilisation of health-care data for research purposes.