Direct Electron Transfer-Type Oxidoreductases for Biomedical Applications.

Among the various types of enzyme-based biosensors, sensors utilizing enzymes capable of direct electron transfer (DET) are recognized as the most ideal. However, only a limited number of redox enzymes are capable of DET with electrodes, that is, dehydrogenases harboring a subunit or domain that functions specifically to accept electrons from the redox cofactor of the catalytic site and transfer the electrons to the external electron acceptor. Such subunits or domains act as built-in mediators for electron transfer between enzymes and electrodes; consequently, such enzymes enable direct electron transfer to electrodes and are designated as DET-type enzymes. DET-type enzymes fall into several categories, including redox cofactors of catalytic reactions, built-in mediators for DET with electrodes and by their protein hierarchic structures, DET-type oxidoreductases with oligomeric structures harboring electron transfer subunits, and monomeric DET-type oxidoreductases harboring electron transfer domains. In this review, we cover the science of DET-type oxidoreductases and their biomedical applications. First, we introduce the structural biology and current understanding of DET-type enzyme reactions. Next, we describe recent technological developments based on DET-type enzymes for biomedical applications, such as biosensors and biochemical energy harvesting for self-powered medical devices. Finally, after discussing how to further engineer and create DET-type enzymes, we address the future prospects for DET-type enzymes in biomedical engineering.

The correlation of urea and creatinine concentrations in sweat and saliva with plasma during hemodialysis: an observational cohort study.

OBJECTIVES: Urea and creatinine concentrations in plasma are used to guide hemodialysis (HD) in patients with end-stage renal disease (ESRD). To support individualized HD treatment in a home situation, there is a clinical need for a non-invasive and continuous alternative to plasma for biomarker monitoring during and between cycles of HD. In this observational study, we therefore established the correlation of urea and creatinine concentrations between sweat, saliva and plasma in a cohort of ESRD patients on HD. METHODS: Forty HD patients were recruited at the Dialysis Department of the Catharina Hospital Eindhoven. Sweat and salivary urea and creatinine concentrations were analyzed at the start and at the end of one HD cycle and compared to the corresponding plasma concentrations. RESULTS: A decrease of urea concentrations during HD was observed in sweat, from 27.86 mmol/L to 12.60 mmol/L, and saliva, from 24.70 mmol/L to 5.64 mmol/L. Urea concentrations in sweat and saliva strongly correlated with the concentrations in plasma (ρ 0.92 [p<0.001] and 0.94 [p<0.001], respectively). Creatinine concentrations also decreased in sweat from 43.39 µmol/L to 19.69 µmol/L, and saliva, from 59.00 µmol/L to 13.70 µmol/L. However, for creatinine, correlation coefficients were lower than for urea for both sweat and saliva compared to plasma (ρ: 0.58 [p<0.001] and 0.77 [p<0.001], respectively). CONCLUSIONS: The results illustrate a proof of principle of urea measurements in sweat and saliva to monitor HD adequacy in a non-invasive and continuous manner. Biosensors enabling urea monitoring in sweat or saliva could fill in a clinical need to enable at-home HD for more patients and thereby decrease patient burden.

Continuous cardiac monitoring in epilepsy: an implantable loop manual activation algorithm for improving ECG signal acquisition accuracy.

BACKGROUND: The muscle artifacts, caused by prominent muscle contractions, mimicking cardiac arrhythmias, might compromise the ECG signal quality and the implantable loop recorder memory capacity in patients with epilepsy. We developed an epileptic seizures clinical pattern-based implantable loop recorder manual activation algorithm, presenting its real-world efficacy here. METHODS: One hundred ninety-three patients (18-60 years) with drug-resistant focal epilepsy were consecutively enrolled and underwent a subcutaneous loop recorder implantation. Patients with focal onset-aware seizures and patients with focal impaired awareness seizures /bilateral tonic-clonic seizures without aura were recommended to use the activator once - just after the episode. Patients with focal impaired awareness seizures/bilateral tonic-clonic seizures with aura, the caregivers of patients experiencing status epilepticus, were advised to use the activator twice - during the aura and after the episode/ regaining consciousness. RESULTS: Six thousand four hundred ninety-four ECG traces (4826 - auto-triggered events, 1668 - person-activated events) were recorded and analyzed. The rate of true positive events in the person-activated group was statistically higher than in the autoactivation group (72.5% vs.19.4%, p < 0.0001). Person-activated false-positive events were observed in 30.5% of patients with focal impaired awareness seizures and 27.7% in patients with bilateral tonic-clonic seizures. The highest rate of false-positive events (61.5%) was detected in patients undergoing epileptic status, and the lowest rate (3.8%) - was in patients with focal onset aware seizures. The rate of false-positive events was significantly higher in patients with impaired awareness seizures without aura both in focal impaired awareness (45.5% vs. 19.3%, p < 0.0001) and bilateral tonic-clonic seizure groups (38.8% vs. 5.9%, p < 0.0001). CONCLUSIONS: Arrhythmias with varying clinical outcomes are expected in epilepsy patients and have been monitored continuously. The specified loop recorder external activation algorithm can improve the clinically relevant cardiac arrhythmia detection accuracy in epilepsy patients and the value of future studies.

Evaluation of an algorithm-guided photoplethysmography for atrial fibrillation burden using a smartwatch.

BACKGROUND: Wearable devices based on the PPG algorithm can detect atrial fibrillation (AF) effectively. However, further investigation of its application on long-term, continuous monitoring of AF burden is warranted. METHOD: The performance of a smartwatch with continuous photoplethysmography (PPG) and PPG-based algorithms for AF burden estimation was evaluated in a prospective study enrolling AF patients admitted to Beijing Anzhen Hospital for catheter ablation from September to November 2022. A continuous Electrocardiograph patch (ECG) was used as the reference device to validate algorithm performance for AF detection in 30-s intervals. RESULTS: A total of 578669 non-overlapping 30-s intervals for PPG and ECG each from 245 eligible patients were generated. An interval-level sensitivity of PPG was 96.3% (95% CI 96.2%-96.4%), and specificity was 99.5% (95% CI 99.5%-99.6%) for the estimation of AF burden. AF burden estimation by PPG was highly correlated with AF burden calculated by ECG via Pearson correlation coefficient (R2 = 0.996) with a mean difference of -0.59 (95% limits of agreement, -7.9% to 6.7%). The subgroup study showed the robust performance of the algorithm in different subgroups, including heart rate and different hours of the day. CONCLUSION: Our results showed the smartwatch with an algorithm-based PPG monitor has good accuracy and stability in continuously monitoring AF burden compared with ECG patch monitors, indicating its potential for diagnosing and managing AF.

Improving diagnosis of early complications (<1 week) through continuous vital sign monitoring following oncological gastrointestinal surgical procedures.

BACKGROUND: Patients undergoing major oncological abdominal surgery are prone to postoperative complications, making early recognition crucial. Clinical deterioration is often preceded by changes in vital signs, which are typically measured thrice a day by a nurse. However, intermittent measurements may delay recognizing clinical deterioration. Continuous vital parameter monitoring may lead to earlier recognition and management of complications and reduce nursing workload. OBJECTIVE: To compare vital parameter measurements between ward nurses and a wireless continuous monitoring system (Sensium® wireless patch) and assess whether this patch can detect clinical deterioration earlier in patients with complications in the first postoperative week. METHODS: Vital parameters (heart rate, respiratory rate, and temperature) were collected in patients undergoing an oncological resection of the liver, colorectal, or pancreas. Sensium® patch measurements were compared to nurses' measurements to assess the percentages of discordant measurements. In patients with complications in the first postoperative week, time discrepancies between nurses and Sensium® patch measurements were identified in cases of clinical deterioration (respiratory rate ≥15/min, heart rate ≥100/min, and temperature ≥38°C). RESULTS: Among 227 patients, 22% of the patients experienced complications. Nurse and Sensium® measurements were discrepant in 586/2272 measurements (26%). In 506/586 discrepancies (86%), this was due to the respiratory rate (difference ≥4/min). Compared to nurses, the Sensium® patch detected an elevated respiratory rate 14 h earlier and heart rate 2 h earlier within complications in the first postoperative week. For temperature, no difference was observed. CONCLUSION: Continuous monitoring with the Sensium® wireless patch holds promise for earlier recognition of complications in patients who underwent major oncological abdominal surgery.

Workload associated with manual assessment of vital signs as compared with continuous wireless monitoring.

BACKGROUND: Vital sign monitoring is considered an essential aspect of clinical care in hospitals. In general wards, this relies on intermittent manual assessments performed by clinical staff at intervals of up to 12 h. In recent years, continuous monitoring of vital signs has been introduced to the clinic, with improved patient outcomes being one of several potential benefits. The aim of this study was to determine the workload difference between continuous monitoring and manual monitoring of vital signs as part of the National Early Warning Score (NEWS). METHODS: Three wireless sensors continuously monitored blood pressure, heart rate, respiratory rate, and peripheral oxygen saturation in 20 patients admitted to the general hospital ward. The duration needed for equipment set-up and maintenance for continuous monitoring in a 24-h period was recorded and compared with the time spent on manual assessments and documentation of vital signs performed by clinical staff according to the NEWS. RESULTS: The time used for continuous monitoring was 6.0 (IQR 3.2; 7.2) min per patient per day vs. 14 (9.7; 32) min per patient per day for the NEWS. Median difference in duration for monitoring of vital signs was 9.9 (95% CI 5.6; 21) min per patient per day between NEWS and continuous monitoring (p < .001). Time used for continuous monitoring in isolated patients was 6.6 (4.6; 12) min per patient per day as compared with 22 (9.7; 94) min per patient per day for NEWS. CONCLUSION: The use of continuous monitoring was associated with a significant reduction in workload in terms of time for monitoring as compared with manual assessment of vital signs.

Advances in microneedles for transdermal diagnostics and sensing applications.

Microneedles, the miniaturized needles, which can pierce the skin with minimal invasiveness open up new possibilities for constructing personalized Point-of-Care (POC) diagnostic platforms. Recent advances in microneedle-based POC diagnostic systems, especially their successful implementation with wearable technologies, enable biochemical detection and physiological recordings in a user-friendly manner. This review presents an overview of the current advances in microneedle-based sensor devices, with emphasis on the biological basis of transdermal sensing, fabrication, and application of different types of microneedles, and a summary of microneedle devices based on various sensing strategies. It concludes with the challenges and future prospects of this swiftly growing field. The aim is to present a critical and thorough analysis of the state-of-the-art development of transdermal diagnostics and sensing devices based on microneedles, and to bridge the gap between microneedle technology and pragmatic applications.

Excessive Oxygen Administration in High-Risk Patients Admitted to Medical and Surgical Wards Monitored by Wireless Pulse Oximeter.

The monitoring of oxygen therapy when patients are admitted to medical and surgical wards could be important because exposure to excessive oxygen administration (EOA) may have fatal consequences. We aimed to investigate the association between EOA, monitored by wireless pulse oximeter, and nonfatal serious adverse events (SAEs) and mortality within 30 days. We included patients in the Capital Region of Copenhagen between 2017 and 2018. Patients were hospitalized due to acute exacerbation of chronic obstructive pulmonary disease (AECOPD) or after major elective abdominal cancer surgery, and all were treated with oxygen supply. Patients were divided into groups by their exposure to EOA: no exposure, exposure for 1-59 min or exposure over 60 min. The primary outcome was SAEs or mortality within 30 days. We retrieved data from 567 patients for a total of 43,833 h, of whom, 63% were not exposed to EOA, 26% had EOA for 1-59 min and 11% had EOA for ≥60 min. Nonfatal SAEs or mortality within 30 days developed in 24%, 12% and 22%, respectively, and the adjusted odds ratio for this was 0.98 (95% CI, 0.96-1.01) for every 10 min. increase in EOA, without any subgroup effects. In conclusion, we did not observe higher frequencies of nonfatal SAEs or mortality within 30 days in patients exposed to excessive oxygen administration.

Point Sensor Networks Struggle to Detect and Quantify Short Controlled Releases at Oil and Gas Sites.

This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38 and 86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between the release rate and the reported emission rate estimate was observed. The average, aggregated across all PSN solutions during releases, shows 5% of the mixing ratio readings at downwind sensors were greater than the site's baseline plus two standard deviations. Four of seven total PSN solutions tested during this field campaign provided site-level emission rate estimates with the site average relative error ranging from -100% to 24% for solution D, -100% to -43% for solution E, -25% for solution F (solution F was only at one site), and -99% to 430% for solution G, with an overall average of -29% across all sites and solutions. Of all the individual site-level emission rate estimates, only 11% were within ±2.5 kg/h of the study team's best estimate of site-level emissions at the time of the releases.

Real-Time Monitoring of Odour Emissions at the Fenceline of a Waste Treatment Plant by Instrumental Odour Monitoring Systems: Focus on Training Methods.

Waste treatment plants (WTPs) often generate odours that may cause nuisance to citizens living nearby. In general, people are becoming more sensitive to environmental issues, and particularly to odour pollution. Instrumental Odour Monitoring Systems (IOMSs) represent an emerging tool for continuous odour measurement and real-time identification of odour peaks, which can provide useful information about the process operation and indicate the occurrence of anomalous conditions likely to cause odour events in the surrounding territories. This paper describes the implementation of two IOMSs at the fenceline of a WTP, focusing on the definition of a specific experimental protocol and data processing procedure for dealing with the interferences of humidity and temperature affecting sensors' responses. Different approaches for data processing were compared and the optimal one was selected based on field performance testing. The humidity compensation model developed proved to be effective, bringing the IOMS classification accuracy above 95%. Also, the adoption of a class-specific regression model compared to a global regression model resulted in an odour quantification capability comparable with those of the reference method (i.e., dynamic olfactometry). Lastly, the validated models were used to process the monitoring data over a period of about one year.

Advancements in Polymer-Assisted Layer-by-Layer Fabrication of Wearable Sensors for Health Monitoring.

Recent advancements in polymer-assisted layer-by-layer (LbL) fabrication have revolutionized the development of wearable sensors for health monitoring. LbL self-assembly has emerged as a powerful and versatile technique for creating conformal, flexible, and multi-functional films on various substrates, making it particularly suitable for fabricating wearable sensors. The incorporation of polymers, both natural and synthetic, has played a crucial role in enhancing the performance, stability, and biocompatibility of these sensors. This review provides a comprehensive overview of the principles of LbL self-assembly, the role of polymers in sensor fabrication, and the various types of LbL-fabricated wearable sensors for physical, chemical, and biological sensing. The applications of these sensors in continuous health monitoring, disease diagnosis, and management are discussed in detail, highlighting their potential to revolutionize personalized healthcare. Despite significant progress, challenges related to long-term stability, biocompatibility, data acquisition, and large-scale manufacturing are still to be addressed, providing insights into future research directions. With continued advancements in polymer-assisted LbL fabrication and related fields, wearable sensors are poised to improve the quality of life for individuals worldwide.

Performance Assessment for the Validation of Wireless Communication Engines in an Innovative Wearable Monitoring Platform.

In today's health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to flush collected data towards an external gateway. This paper presents a quantitative analysis aimed at validating both the wireless synchronization task (implemented with a custom protocol) and the data transmission task (implemented with the BLE protocol) in a prototype wearable monitoring platform. We evaluated seven frequencies for exchanging synchronization packets (10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 60 Hz, 70 Hz) as well as two different BLE configurations (with and without the implementation of a dynamic adaptation of the BLE Connection Interval parameter). Additionally, we tested BLE data transmission performance in five different use case scenarios. As a result, we achieved the optimal performance in the synchronization task (1.18 ticks as median synchronization delay with a Min-Max range of 1.60 ticks and an Interquartile range (IQR) of 0.42 ticks) when exploiting a synchronization frequency of 40 Hz and the dynamic adaptation of the Connection Interval. Moreover, BLE data transmission proved to be significantly more efficient with shorter distances between the communicating nodes, growing worse by 30.5% beyond 8 m. In summary, this study suggests the best-performing network configurations to enhance the synchronization task of the prototype platform under analysis, as well as quantitative details on the best placement of data collectors.

A machine learning algorithm for detecting abnormal patterns in continuous capnography and pulse oximetry monitoring.

Continuous capnography monitors patient ventilation but can be susceptible to artifact, resulting in alarm fatigue. Development of smart algorithms may facilitate accurate detection of abnormal ventilation, allowing intervention before patient deterioration. The objective of this analysis was to use machine learning (ML) to classify combined waveforms of continuous capnography and pulse oximetry as normal or abnormal. We used data collected during the observational, prospective PRODIGY trial, in which patients receiving parenteral opioids underwent continuous capnography and pulse oximetry monitoring while on the general care floor [1]. Abnormal ventilation segments in the data stream were reviewed by nine experts and inter-rater agreement was assessed. Abnormal segments were defined as the time series 60s before and 30s after an abnormal pattern was detected. Normal segments (90s continuous monitoring) were randomly sampled and filtered to discard sequences with missing values. Five ML models were trained on extracted features and optimized towards an Fß score with ß = 2. The results show a high inter-rater agreement (> 87%), allowing 7,858 sequences (2,944 abnormal) to be used for model development. Data were divided into 80% training and 20% test sequences. The XGBoost model had the highest Fß score of 0.94 (with ß = 2), showcasing an impressive recall of 0.98 against a precision of 0.83. This study presents a promising advancement in respiratory monitoring, focusing on reducing false alarms and enhancing accuracy of alarm systems. Our algorithm reliably distinguishes normal from abnormal waveforms. More research is needed to define patterns to distinguish abnormal ventilation from artifacts.

Postoperative circadian patterns in wearable sensor measured heart rate: a prospective observational study.

PURPOSE: This study aimed to describe the 24-hour cycle of wearable sensor-obtained heart rate in patients with deterioration-free recovery and to compare it with patients experiencing postoperative deterioration. METHODS: A prospective observational trial was performed in patients following bariatric or major abdominal cancer surgery. A wireless accelerometer patch (Healthdot) continuously measured postoperative heart rate, both in the hospital and after discharge, for a period of 14 days. The circadian pattern, or diurnal rhythm, in the wearable sensor-obtained heart rate was described using peak, nadir and peak-nadir excursions. RESULTS: The study population consisted of 137 bariatric and 100 major abdominal cancer surgery patients. In the latter group, 39 experienced postoperative deterioration. Both surgery types showed disrupted diurnal rhythm on the first postoperative days. Thereafter, the bariatric group had significantly lower peak heart rates (days 4, 7-12, 14), lower nadir heart rates (days 3-14) and larger peak-nadir excursions (days 2, 4-14). In cancer surgery patients, significantly higher nadir (days 2-5) and peak heart rates (days 2-3) were observed prior to deterioration. CONCLUSIONS: The postoperative diurnal rhythm of heart rate is disturbed by different types of surgery. Both groups showed recovery of diurnal rhythm but in patients following cancer surgery, both peak and nadir heart rates were higher than in the bariatric surgery group. Especially nadir heart rate was identified as a potential prognostic marker for deterioration after cancer surgery.

A Direct Assessment of Noninvasive Continuous Blood Pressure Monitoring in the Emergency Department and Intensive Care Unit.

INTRODUCTION: Noninvasive continuous blood pressure monitoring has the potential to improve patient treatment in the hospital setting. Such noninvasive devices can be applied earlier in the treatment process to empower nurses and clinicians to react more quickly to patient deterioration with the added benefit of eliminating the risks associated with invasive monitoring. However, emerging technologies must be capable of reproducing current clinical measures for medical decision making. METHODS: This study aimed to determine the usability and willingness of nurses to implement a noninvasive continuous blood pressure monitoring device. The secondary aim directly compared the systolic blood pressure, diastolic blood pressure, and mean arterial pressure values recorded by the device (VitalStream; CareTaker Medical LLC, Charlottesville, VA) with the "gold standard" brachial cuff and arterial line measures recorded in the emergency department and intensive care unit settings. RESULTS: VitalStream was similarly received by nurses in the emergency department and intensive care setting, but ultimately had greater promotion from emergency nurses. Despite some statistical similarity between measurement methodologies, all direct comparisons were found to not meet the Association for the Advancement of Medical Instrumentation 2008 and Association for the Advancement of Medical Instrumentation / European Society of Hypertension / International Organization for Standardization 2019 consensus statement criteria for acceptable blood pressure measure differences between the VitalStream and "gold standard" clinical measures. In all instances, the standard deviation of the Bland-Altman bias exceeded 8 mm Hg with less than 85% of paired differences falling within 10 mm Hg of the "gold standard." DISCUSSION: Taken together, the tested device requires additional postprocessing for medical decision making in trauma or emergent care.

Wearable Clinic: From Microneedle-Based Sensors to Next-Generation Healthcare Platforms.

The rapid development of wearable biosensing calls for next-generation devices that allow continuous, real-time, and painless monitoring of health status along with responsive medical treatment. Microneedles have exhibited great potential for the direct access of dermal interstitial fluid (ISF) in a minimally invasive manner. Recent studies of microneedle-based devices have evolved from conventional off-line detection to multiplexed, wireless, and integrated sensing. In this review, the classification and fabrication techniques of microneedles are first introduced, and then the representative examples of microneedles for transdermal monitoring with different sensing modalities are summarized. State-of-the-art advances in therapeutic and closed-loop systems are presented to formulate guidelines for the development of next-generation microneedle-based healthcare platforms. The potential challenges and prospects are discussed to pave a new avenue toward pragmatic applications in the real world.

Clinical utility of the 4S-AF scheme in predicting progression of atrial fibrillation: data from the RACE V study.

AIMS: The recent 4S-AF (scheme proposed by the 2020 ESC AF guidelines to address stroke risk, symptom severity, severity of AF burden and substrate of AF to provide a structured phenotyping of AF patients in clinical practice to guide therapy and assess prognosis) scheme has been proposed as a structured scheme to characterize patients with atrial fibrillation (AF). We aimed to assess whether the 4S-AF scheme predicts AF progression in patients with self-terminating AF. METHODS AND RESULTS: We analysed 341 patients with self-terminating AF included in the well-phenotyped Reappraisal of Atrial Fibrillation: Interaction between HyperCoagulability, Electrical remodelling, and Vascular Destabilization in the Progression of AF (RACE V) study. Patients had continuous monitoring with implantable loop recorders or pacemakers. AF progression was defined as progression to persistent or permanent AF or progression of self-terminating AF with >3% burden increase. Progression of AF was observed in 42 patients (12.3%, 5.9% per year). Patients were given a score based on the components of the 4S-AF scheme. Mean age was 65 [interquartile range (IQR) 58-71] years, 149 (44%) were women, 103 (49%) had heart failure, 276 (81%) had hypertension, and 38 (11%) had coronary artery disease. Median CHA2DS2-VASc (the CHA2DS2-VASc score assesses thromboembolic risk. C, congestive heart failure/left ventricular dysfunction; H, hypertension; A2, age ≥ 75 years; D, diabetes mellitus; S2, stroke/transient ischaemic attack/systemic embolism; V, vascular disease; A, age 65-74 years; Sc, sex category (female sex)) score was 2 (IQR 2-3), and median follow-up was 2.1 (1.5-2.6) years. The average score of the 4S-AF scheme was 4.6 ± 1.4. The score points from the 4S-AF scheme did not predict the risk of AF progression [odds ratio (OR) 1.1 95% CI 0.88-1.41, C-statistic 0.53]. However, excluding the symptoms domain, resulting in the 3S-AF (4S-AF scheme without the domain symptom severity, only including stroke risk, severity of AF burden and substrate of AF) scheme, predicted the risk of progression (OR 1.59 95% CI 1.15-2.27, C-statistic 0.62) even after adjusting for sex and age. CONCLUSIONS: In self-terminating AF patients, the 4S-AF scheme does not predict AF progression. The 3S-AF scheme, excluding the symptom domain, may be a more appropriate score to predict AF progression. TRIAL REGISTRATION NUMBERS: Clinicaltrials.gov NCT02726698 for RACE V.

The influence of atrial high-rate episodes on stroke and cardiovascular death: an update.

Atrial high-rate episodes (AHRE) are atrial tachyarrhythmias detected by continuous rhythm monitoring by pacemakers, defibrillators, or implantable cardiac monitors. Atrial high-rate episodes occur in 10-30% of elderly patients without atrial fibrillation. However, it remains unclear whether the presence of these arrhythmias has therapeutic consequences. The presence of AHRE increases the risk of stroke compared with patients without AHRE. Oral anticoagulation would have the potential to reduce the risk of stroke in patients with AHRE but is also associated with a rate of major bleeding of ∼2%/year. The stroke rate in patients with AHRE appears to be lower than the stroke rate in patients with atrial fibrillation. Wearables like smart-watches will increase the absolute number of patients in whom atrial arrhythmias are detected. It remains unclear whether anticoagulation is effective and, equally important, safe in patients with AHRE. Two randomized clinical trials, NOAH-AFNET6 and ARTESiA, are expected to report soon. They will provide much-needed information on the efficacy and safety of oral anticoagulation in patients with AHRE.

Assessing Detection Efficiencies for Continuous Methane Emission Monitoring Systems at Oil and Gas Production Sites.

Continuous monitoring systems, consisting of multiple fixed sensors, are increasingly being deployed at oil and gas production sites to detect methane emissions. While these monitoring systems operate continuously, their efficiency in detecting emissions will depend on meteorological conditions, sensor detection limits, the number of sensors deployed, and sensor placement strategies. This work demonstrates an approach to assess the effectiveness of continuous sensor networks in detecting infinite-duration and fixed-duration emission events. The case studies examine a single idealized source and a group of nine different sources at varying heights and locations on a single pad. Using site-specific meteorological data and dispersion modeling, the emission detection performance is characterized. For these case studies, infinite-duration emission events are detected within 1 h to multiple days, depending on the number of sensors deployed. The percentage of fixed-duration emission events that are detected ranged from less than 10% to more than 90%, depending on the number of sources, emission release height, emission event duration, and the number of sensors deployed. While these results are specific to these case studies, the analysis framework described in this work can be broadly applied in the evaluation of continuous emission monitoring network designs.

Toward Multiscale Measurement-Informed Methane Inventories: Reconciling Bottom-Up Site-Level Inventories with Top-Down Measurements Using Continuous Monitoring Systems.

Government policies and corporate strategies aimed at reducing methane emissions from the oil and gas sector increasingly rely on measurement-informed, site-level emission inventories, as conventional bottom-up inventories poorly capture temporal variability and the heavy-tailed nature of methane emissions. This work is based on an 11-month methane measurement campaign at oil and gas production sites. We find that operator-level top-down methane measurements are lower during the end-of-project phase than during the baseline phase. However, gaps persist between end-of-project top-down measurements and bottom-up site-level inventories, which we reconcile with high-frequency data from continuous monitoring systems (CMS). Specifically, we use CMS to (i) validate specific snapshot measurements and determine how they relate to the temporal emission profile of a given site and (ii) create a measurement-informed, site-level inventory that can be validated with top-down measurements to update conventional bottom-up inventories. This work presents a real-world demonstration of how to reconcile CMS rate estimates and top-down snapshot measurements jointly with bottom-up inventories at the site level. More broadly, it demonstrates the importance of multiscale measurements when creating measurement-informed, site-level emission inventories, which is a critical aspect of recent regulatory requirements in the Inflation Reduction Act, voluntary methane initiatives such as the Oil and Gas Methane Partnership 2.0, and corporate strategies.