Enhanced pyrophosphate detection: Utilizing oPD-derived carbon dots and Fe3+ interactions in a paper strip biosensor.

The development of portable, cost-effective, and straightforward DNA biosensors holds immense importance in various fields, including healthcare, environmental monitoring, and food safety. This study contributes to the objective by introducing an innovative approach for synthesizing carbon dots (Cdots) with high quantum yield (QY) and remarkable selectivity for Fe3+ ions. Utilizing o-phenylenediamine as a precursor, the study achieved a straightforward and environmentally friendly synthesis method, enabling the efficient detachment of metal ions from the Cdot surface upon introducing pyrophosphate (PPi). The presence of surface hydroxyl and amino groups facilitated specific Fe3+ recognition. Employing D-optimal response surface methodology, the study optimized Cdot synthesis parameters, identifying temperature and heating time as critical factors influencing QY. Statistical analysis confirmed the model's reliability, predicting maximum QY of 48.8 % with minimal deviation from experimental results. Characterization studies revealed the amorphous nature of Cdots through HR-TEM, XRD, and FTIR analysis. Furthermore, the proposed LAMP/PPi biosensing technique demonstrated higher sensitivity, specificity, and repeatability, with negligible interference from common anions and efficacy across varying pH levels. The limit of detection (LOD) of 0.079 (±0.01) µM and the detection range of 0.1 µM-2 mM underscore the biosensor's practical utility. This study highlights a promising direction for developing paper-based LAMP/PPi biosensors with potential diagnostics and environmental monitoring applications. Significantly, the biosensing technique is applicable to any DNA amplification method generating pyrophosphate (PPi) as a by-product.

Advancements in Battery Monitoring: Harnessing Fiber Grating Sensors for Enhanced Performance and Reliability.

Batteries play a crucial role as energy storage devices across various industries. However, achieving high performance often comes at the cost of safety. Continuous monitoring is essential to ensure the safety and reliability of batteries. This paper investigates the advancements in battery monitoring technology, focusing on fiber Bragg gratings (FBGs). By examining the factors contributing to battery degradation and the principles of FBGs, this study discusses key aspects of FBG sensing, including mounting locations, monitoring targets, and their correlation with optical signals. While current FBG battery sensing can achieve high measurement accuracies for temperature (0.1 °C), strain (0.1 µÎµ), pressure (0.14 bar), and refractive index (6 × 10-5 RIU), with corresponding sensitivities of 40 pm/°C, 2.2 pm/µÎµ, -0.3 pm/bar, and -18 nm/RIU, respectively, accurately assessing battery health in real time remains a challenge. Traditional methods struggle to provide real-time and precise evaluations by analyzing the microstructure of battery materials or physical phenomena during chemical reactions. Therefore, by summarizing the current state of FBG battery sensing research, it is evident that monitoring battery material properties (e.g., refractive index and gas properties) through FBGs offers a promising solution for real-time and accurate battery health assessment. This paper also delves into the obstacles of battery monitoring, such as standardizing the FBG encapsulation process, decoupling multiple parameters, and controlling costs. Ultimately, the paper highlights the potential of FBG monitoring technology in driving advancements in battery development.

A Data Compression Method for Wellbore Stability Monitoring Based on Deep Autoencoder.

The compression method for wellbore trajectory data is crucial for monitoring wellbore stability. However, classical methods like methods based on Huffman coding, compressed sensing, and Differential Pulse Code Modulation (DPCM) suffer from low real-time performance, low compression ratios, and large errors between the reconstructed data and the source data. To address these issues, a new compression method is proposed, leveraging a deep autoencoder for the first time to significantly improve the compression ratio. Additionally, the method reduces error by compressing and transmitting residual data from the feature extraction process using quantization coding and Huffman coding. Furthermore, a mean filter based on the optimal standard deviation threshold is applied to further minimize error. Experimental results show that the proposed method achieves an average compression ratio of 4.05 for inclination and azimuth data; compared to the DPCM method, it is improved by 118.54%. Meanwhile, the average mean square error of the proposed method is 76.88, which is decreased by 82.46% when compared to the DPCM method. Ablation studies confirm the effectiveness of the proposed improvements. These findings highlight the efficacy of the proposed method in enhancing wellbore stability monitoring performance.

Adverse Events Following Immunization With mRNA and Viral Vector Vaccines in Individuals With Previous Severe Acute Respiratory Syndrome Coronavirus 2 Infection From the Canadian National Vaccine Safety Network.

BACKGROUND: Adults previously infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop short-term immunity and may have increased reactogenicity to coronavirus disease 2019 (COVID-19) vaccines. This prospective, multicenter, active-surveillance cohort study examined the short-term safety of COVID-19 vaccines in adults with a prior history of SARS-CoV-2. METHODS: Canadian adults vaccinated between 22 December 2020 and 27 November 2021 were sent an electronic questionnaire 7 days post-dose 1, dose 2, and dose 3 vaccination. The main outcome was health events occurring in the first 7 days after each vaccination that prevented daily activities, resulted in work absenteeism, or required a medical consultation, including hospitalization. RESULTS: Among 684 998 vaccinated individuals, 2.6% (18 127/684 998) reported a prior history of SARS-CoV-2 infection a median of 4 (interquartile range: 2-6) months previously. After dose 1, individuals with moderate (bedridden) to severe (hospitalized) COVID-19 who received BNT162b2, mRNA-1273, or ChAdox1-S vaccines had higher odds of a health event preventing daily activities, resulting in work absenteeism or requiring medical consultation (adjusted odds ratio [95% confidence interval]: 3.96 [3.67-4.28] for BNT162b2, 5.01 [4.57-5.50] for mRNA-1273, and 1.84 [1.54-2.20] for ChAdox1-S compared with no infection). Following dose 2 and 3, the greater risk associated with previous infection was also present but was attenuated compared with dose 1. For all doses, the association was lower or absent after mild or asymptomatic infection. CONCLUSIONS: Adults with moderate or severe previous SARS-CoV-2 infection were more likely to have a health event sufficient to impact routine activities or require medical assessment in the week following each vaccine dose.

A hybrid automated event adjudication system for clinical trials.

INTRODUCTION: In clinical trials, event adjudication is a process to review and confirm the accuracy of outcomes reported by site investigators. Despite efforts to automate the communication between a clinical-data-and-coordination center and an event adjudication committee, the review and confirmation of outcomes, as the core function of the process, still fully rely on human labor. To address this issue, we present an automated event adjudication system and its application in two randomized controlled trials. METHODS: Centrally executed by a clinical-data-and-coordination center, the automated event adjudication system automatedly assessed and classified outcomes in a clinical data management system. By checking clinically predefined criteria, the automated event adjudication system either confirmed or unconfirmed an outcome and automatedly updated its status in the database. It also served as a management tool to assist staff to oversee the process of event adjudication. The system has been applied in: (1) the Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) trial and (2) the New Approach riVaroxaban Inhibition of Factor Xa in a Global trial versus Aspirin to prevenT Embolism in Embolic Stroke of Undetermined Source (NAVIGATE ESUS) trial. The automated event adjudication system first screened outcomes reported on a case report form and confirmed those with data matched to preset definitions. For selected primary efficacy, secondary, and safety outcomes, the unconfirmed cases were referred to a human event adjudication committee for a final decision. In the New Approach riVaroxaban Inhibition of Factor Xa in a Global trial versus Aspirin to prevenT Embolism in Embolic Stroke of Undetermined Source (NAVIGATE ESUS) trial, human adjudicators were given priority to review cases, while the automated event adjudication system took the lead in the Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) trial. RESULTS: Outcomes that were adjudicated in a hybrid model are discussed here. The COMPASS automated event adjudication system adjudicated 3283 primary efficacy outcomes and confirmed 1652 (50.3%): 132 (21.1%) strokes, 522 (53%) myocardial infarctions, and 998 (59.7%) causes of deaths. The NAVIGATE ESUS one adjudicated 737 cases of selected outcomes and confirmed 383 (52%): 219 (51.5%) strokes, 34 (42.5%) myocardial infarctions, 73 (54.9%) causes of deaths, and 57 (57.6%) major bleedings. After one deducts the time needed for migrating the system to a new study, the automated event adjudication system helped to reduce the time required for human review from approximately 1303 to 716.5 h for the Cardiovascular Outcomes for People Using Anticoagulation Strategies trial and from 387 to 196 h for the New Approach riVaroxaban Inhibition of Factor Xa in a Global trial versus Aspirin to prevenT Embolism in Embolic Stroke of Undetermined Source trial. CONCLUSION: The automated event adjudication system in combination with human adjudicators provides a streamlined and efficient approach to event adjudication in clinical trials. To immediately apply automated event adjudication, one can first consider the automated event adjudication system and involve human assistance for cases unconfirmed by the former.

Data monitoring committees in pediatric randomized controlled trials registered in ClinicalTrials.gov.

BACKGROUND: Data monitoring committees advise on clinical trial conduct through appraisal of emerging data to ensure participant safety and scientific integrity. While consideration of their use is recommended for trials performed with vulnerable populations, previous research has shown that data monitoring committees are reported infrequently in publications of pediatric randomized controlled trials. We aimed to assess the frequency of reported data monitoring committee adoption in ClinicalTrials.gov registry records and to examine the influence of key trial characteristics. METHODS: We conducted a cross-sectional data analysis of all randomized controlled trials performed exclusively in a pediatric population and registered in ClinicalTrials.gov between 2008 and 2021. We used the Access to Aggregate Content of ClinicalTrials.gov database to retrieve publicly available information on trial characteristics and data on safety results. Abstracted data included reported trial design and conduct parameters, population and intervention characteristics, reasons for prematurely halting, serious adverse events, and mortality outcomes. We performed descriptive analyses on the collected data and explored the influence of clinical, methodological, and operational trial characteristics on the reported adoption of data monitoring committees. RESULTS: We identified 13,928 pediatric randomized controlled trial records, of which 39.7% reported adopting a data monitoring committee, 49.0% reported not adopting a data monitoring committee, and 11.3% did not answer on this item. While the number of registered pediatric trials has been increasing since 2008, we found no clear time trend in the reported adoption of data monitoring committees. Data monitoring committees were more common in multicenter trials (50.6% vs 36.9% for single-center), multinational trials (60.2% vs 38.7% for single-country), National Institutes of Health-funded (60.3% vs 40.1% for industry-funded or 37.5% for other funders), and placebo-controlled (47.6% vs 37.5% for other types of control groups). Data monitoring committees were also more common among trials enrolling younger participants, trials employing blinding techniques, and larger trials. Data monitoring committees were more common in trials with at least one serious adverse event (52.6% vs 38.4% for those without) as well as for trials with reported deaths (70.3% vs 38.9% for trials without reported deaths). In all, 4.9% were listed as halted prematurely, most often due to low accrual rates. Trials with a data monitoring committee were more often halted for reasons related to scientific data than trials without a data monitoring committee (15.7% vs 7.3%). CONCLUSION: According to registry records, the use of data monitoring committees in pediatric randomized controlled trials was more frequent than previously reported in reviews of published trial reports. The use of data monitoring committees varied across key clinical and trial characteristics based on which their use is recommended. Data monitoring committees may still be underutilized in pediatric trials, and reporting of this item could be improved.

Recent Progress in Lithium-Ion Battery Safety Monitoring Based on Fiber Bragg Grating Sensors.

Lithium-ion batteries are widely used in a variety of fields due to their high energy density, high power density, long service life, and environmental friendliness. However, safety accidents with lithium-ion batteries occur frequently. The real-time safety monitoring of lithium-ion batteries is particularly important during their use. The fiber Bragg grating (FBG) sensors have some additional advantages over conventional electrochemical sensors, such as low invasiveness, electromagnetic anti-interference, and insulating properties. This paper reviews lithium-ion battery safety monitoring based on FBG sensors. The principles and sensing performance of FBG sensors are described. The single-parameter monitoring and dual-parameter monitoring of lithium-ion batteries based on FBG sensors are reviewed. The current application state of the monitored data in lithium-ion batteries is summarized. We also present a brief overview of the recent developments in FBG sensors used in lithium-ion batteries. Finally, we discuss future trends in lithium-ion battery safety monitoring based on FBG sensors.

A Cell-Phone Medication Error eHealth App for Managing Safety in Chronically Ill Young Patients at Home: A Prospective Study.

Introduction: Whereas ample information describes medication errors (MEs) in children or in mixed pediatric and adult populations discharged with acute or chronic diseases from hospital to community settings, little is known about MEs in children and adolescents with chronic diseases discharged home, a major concern. To promote home medication safety, we trained parents of children discharged with chronic diseases to record ME with a tailored cell-phone eHealth app. Methods: In a 1-year prospective study, we used the app to monitor ME in patients with chronic diseases discharged home from a tertiary hospital in Rome, Italy. Univariate and multivariate analyses detected the ME incidence rate ratio (IRR). Results: Of the 310 parents enrolled, 194 used the app. The 41 MEs involved all drug management phases. The ME IRR was 0.46 errors per child. Children <1 year had the highest ME risk (1.69 vs. 0.35, p = 0.002). Children discharged from the cardiology unit had a statistically higher ME IRR than others (3.66, 95% confidence interval: 1.01-13.23%). Conclusions: The highest ME risk at home involves children with chronic diseases <1 year old. A significant ME IRR at home concerns children with heart diseases of any age. Parents find a tailored eHealth app for monitoring and reporting ME at home easy to use. At discharge, clinical teams need to identify age-related and disease-residual risks to target additional actions for monitoring ME, thus increasing medication safety at home.

Indirect and Direct 65+ Patient Reporting of Non-Steroidal Anti-Inflammatory Drug-Induced Adverse Drug Reactions as a Source of Information on Polypharmacy and Polypharmacy-Related Risk.

Background and Objectives: Non-steroidal anti-inflammatory drugs (NSAIDs), which have anti-inflammatory and analgesic properties, are commonly used in the treatment of various, particularly frequent, as well as chronic, conditions in older patients. Due to common polypragmasia in these patients and a high risk of adverse drug reactions (ADRs) and drug interactions, pain management poses a therapeutic challenge. This study describes the importance of ADR reports in the identification of polypharmacy and the ensuing interactions. Materials and Methods: Both healthcare professionals (HPs) and non-healthcare professionals (non-HPs) reports collected in the EudraVigilance database of NSAIDs, including most commonly co-reported medications and reported reactions, were analysed and differences between HPs and non-HPs reports were identified. Results: In the analysed period and group, non-HPs reported more reactions but indicated fewer drugs as suspect or concomitant. The outcomes of our analysis indicate more HP engagement and more detailed reports of serious ADRs when compared to non-serious individual case safety reports (ICSRs) by non-HPs, which appeared more detailed. Such reactions as kidney failure and increased risk of bleeding are known adverse reactions to NSAIDs and common symptoms of their interactions, which were described in the available literature. They were much more frequently reported by HPs than by non-HPs. Non-HPs more frequently reported reactions that may have been considered less significant by HPs. Conclusions: The differences between healthcare professionals' (HPs) and non-healthcare professionals' (non-HPs) reports may result from the fact that the reports from patients and their caregivers require a professional medical diagnosis based on symptoms described by the patient or additional diagnostic tests. This means that when appropriately classified, medically verified, and statistically analysed, the data may provide new evidence for the risks of medication use or drug interactions.

[Clinical centralized safety monitoring and evaluation of traditional Chinese medicine formula granules].

Traditional Chinese medicine(TCM) formula granules are highly praised for the advanced, convenient, and modern use of Chinese medicinal materials. The safety of TCM formula granules has long been a concern of regulatory authorities and the medical industry. A multi-center, prospective, open, non-interventional, and centralized monitoring was carried out for the patients treated with TCM formula granules in 252 medical institutions from February 5, 2020 to April 19, 2022. All the case data and the incidence of adverse drug reactions/events were recorded. This study evaluated the safety of TCM formula granules, aiming to provide a reference for the clinically use. A total of 20 547 patients were included in this study. Four adverse events were recorded, including 3 adverse drug reactions with an adverse drug reaction rate of 0.015%, all of which occurred in the digestive system. There was no serious adverse event, and no factors related to adverse drug reactions/events were identified. The incidence of adverse drug reactions/events associated with China Resources Sanjiu Medical & Pharmaceutical Co., Ltd. TCM formula granules was rare, which proved their safety in clinical use. A comprehensive data mining and objective analysis was carried out for the medicines with high frequency in TCM formula granules, the commonly used medicine pairs and combinations, and departmental medication. The drug use characteristics, prescription rules, and departmental use of TCM formula granules were summarized, which can shed light on the prescription compatibility and clinical application.

A Participant-Centered Approach to Understanding Risks and Benefits of Participation in Research Informed by the Kidney Precision Medicine Project.

An understanding of the ethical underpinnings of human subjects research that involves some risk to participants without anticipated direct clinical benefit-such as the kidney biopsy procedure as part of the Kidney Precision Medicine Project (KPMP)-requires a critical examination of the risks as well as the diverse set of countervailing potential benefits to participants. This kind of deliberation has been foundational to the development and conduct of the KPMP. Herein, we use illustrative features of this research paradigm to develop a more comprehensive conceptualization of the types of benefits that may be important to research participants, including respecting pluralistic values, supporting the opportunity to act altruistically, and enhancing benefits to a participant's community. This approach may serve as a model to help researchers, ethicists, and regulators to identify opportunities to better respect and support participants in future research that entails some risk to these participants as well as to improve the quality of research for people with kidney disease.

Ensuring seafood safe to spoon: a brief review of biosensors for marine biotoxin monitoring.

With harmful algal blooms, marine food poisoning caused by marine biotoxins frequently occurs and is life-threatening if severe. However, the conventional detection methods of marine toxins have a few limitations: low sensitivity and high-cost. Therefore, it is necessary to establish a fast and sensitive on-site detection method for real seafood sample. Biosensors based on aptamers, antibodies, and cells have been applied in marine toxins monitoring. This review presents the classification and toxic effects of marine toxins, and recent biosensor for marine toxin detection. In addition, we have compared the superiority and limitation of these biosensors. Finally, challenges and opportunities of biosensors in food safety detection were discussed. Considering the excellent results achieved by the aptasensor in the field of detection, it seems ready to be put into practical applications.

Designing optimal food safety monitoring schemes using Bayesian network and integer programming: The case of monitoring dioxins and DL-PCBs.

Efficient food safety monitoring should achieve optimal resource allocation. In this article, a methodology is presented to optimize the use of resources for food safety monitoring aimed at identifying noncompliant samples and estimating background level of hazards in food products. A Bayesian network (BN) model and an optimization model were combined in a single framework. The framework was applied to monitoring dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs) in primary animal-derived food products in the Netherlands. The BN model was built using a national dataset with monitoring results of dioxins and DL-PCBs in animal-derived food products over a 10-year period (2008-2017). These data were used to estimate the probability of detecting suspect samples with dioxins and DL-PCBs levels above preset thresholds, given certain sample conditions. The results of the BN model were then inserted into the optimization model to compute an optimal monitoring scheme. Model estimates showed that the probability of dioxins and DL-PCBs exceeding threshold limits was higher in laying hen eggs and sheep meat than in other animal-derived food (except deer meat). Compared with the monitoring scheme used in the Netherlands in 2018, the optimal monitoring scheme would save around 10,000 EUR per year. This could be obtained by reallocating monitoring resources from products with lower probability of dioxin and DL-PCBs exceeding threshold limits (e.g., pig meat) to products with higher probability (e.g., bovine animal meat), and by shifting sample collection from the last quarter of the year toward the first three quarters of the year.

Safety Monitoring System of CAVs Considering the Trade-Off between Sampling Interval and Data Reliability.

The safety of urban transportation systems is considered a public health issue worldwide, and many researchers have contributed to improving it. Connected automated vehicles (CAVs) and cooperative intelligent transportation systems (C-ITSs) are considered solutions to ensure the safety of urban transportation systems using various sensors and communication devices. However, realizing a data flow framework, including data collection, data transmission, and data processing, in South Korea is challenging, as CAVs produce a massive amount of data every minute, which cannot be transmitted via existing communication networks. Thus, raw data must be sampled and transmitted to the server for further processing. The data acquired must be highly accurate to ensure the safety of the different agents in C-ITS. On the other hand, raw data must be reduced through sampling to ensure transmission using existing communication systems. Thus, in this study, C-ITS architecture and data flow are designed, including messages and protocols for the safety monitoring system of CAVs, and the optimal sampling interval determined for data transmission while considering the trade-off between communication efficiency and accuracy of the safety performance indicators. Three safety performance indicators were introduced: severe deceleration, lateral position variance, and inverse time to collision. A field test was conducted to collect data from various sensors installed in the CAV, determining the optimal sampling interval. In addition, the Kolmogorov-Smirnov test was conducted to ensure statistical consistency between the sampled and raw datasets. The effects of the sampling interval on message delay, data accuracy, and communication efficiency in terms of the data compression ratio were analyzed. Consequently, a sampling interval of 0.2 s is recommended for optimizing the system's overall efficiency.

Application of FBG Sensor to Safety Monitoring of Mine Shaft Lining Structure.

The use of fiber Bragg grating (FBG) sensors is proposed to solve the technical problem of poor sensor stability in the long-term safety monitoring of shaft lining structures. The auxiliary shaft of the Zhuxianzhuang coal mine was considered as the engineering background, and a test system implementing FBG sensors was established to monitor the long-term safety of the shaft lining structure. Indoor simulation testing revealed that the coefficient of determination (r2) between the test curves of the FBG sensor and the resistance strain gauge is greater than 0.99 in both the transverse and vertical strains. Therefore, the FBG sensor and resistance strain gauge test values are similar, and the error is small. The early warning value was obtained by calculation, according to the specific engineering geological conditions and shaft lining structure. The monitoring data obtained for the shaft lining at three test levels over more than three years reveal that the measured vertical strain value is less than the warning value, indicating that the shaft lining structure is currently in a safe state. The analysis of the monitoring data reveals that the vertical strain increment caused by the vertical additional force is approximately 0.0752 µÎµ/d. As the mine drainage progresses, the increasing vertical additional force acting on the shaft lining will compromise the safety of the shaft lining structure. Therefore, the monitoring must be enhanced to facilitate decision-making for safe shaft operation.

Data and Safety Monitoring of COVID-19 Vaccine Clinical Trials.

To speed the development of vaccines against SARS-CoV-2, the United States Federal Government has funded multiple phase 3 trials of candidate vaccines. A single 11-member data and safety monitoring board (DSMB) monitors all government-funded trials to ensure coordinated oversight, promote harmonized designs, and allow shared insights related to safety across trials. DSMB reviews encompass 3 domains: (1) the conduct of trials, including overall and subgroup accrual and data quality and completeness; (2) safety, including individual events of concern and comparisons by randomized group; and (3) interim analyses of efficacy when event-driven milestones are met. Challenges have included the scale and pace of the trials, the frequency of safety events related to the combined enrollment of over 100 000 participants, many of whom are older adults or have comorbid conditions that place them at independent risk of serious health events, and the politicized environment in which the trials have taken place.

[Research on Comprehensive Safety Monitoring System for Elderly Care Based on Artificial Intelligence and Information Fusion].

Nowadays, China has entered into an aging society; how to ensure safety in elderly care has drawn social attention. Through artificial intelligence and multi-information fusion research, combined with the applications of machine learning algorithms, internet of things devices and cloud computing, this paper presents a comprehensive, intelligent safety monitoring system for the elderly in the community and at home. The system collects the daily life data of the elderly through a series of sensors in an all-round, all-time, and non-intrusive manner, and realizes intelligent alarms for high-risk states such as falls, acute illness, abnormal personnel, and gas smoke for the elderly. Through the innovative research of human pose estimation and behavior recognition, and application of multi-sensor information fusion, the system can greatly reduce the occurrence or injury caused by safety incidents in senior care, bringing safe and healthy living environment for the elderly at homes and communities.

One Step Forward: Successful End-of-Treatment Outcomes of Patients With Drug-Resistant Tuberculosis Who Received Concomitant Bedaquiline and Delamanid in Mumbai, India.

BACKGROUND: The Médecins Sans Frontières Clinic in Mumbai, India, has been providing concomitant bedaquiline (BDQ) and delamanid (DLM) in treatment regimen for patients with drug-resistant tuberculosis (DR-TB) and limited therapeutic options, referred from other healthcare institutions, since 2016. The study documents the end-of-treatment outcomes, culture-conversion rates, and serious adverse events (SAEs) during treatment. METHODS: This was a retrospective cohort study based on routinely collected program data. In clinic, treatment regimens are designed based on culture drug sensitivity test patterns and previous drug exposures, and are provided for 20-22 months. BDQ and DLM are extended beyond 24 weeks as off-label use. Patients who initiated DR-TB treatment including BDQ and DLM (concomitantly for at least 4 weeks) during February 2016-February 2018 were included. RESULTS: Of the 70 patients included, the median age was 25 (interquartile range [IQR], 22-32) years and 56% were females. All except 1 were fluoroquinolone resistant. The median duration of exposure to BDQ and DLM was 77 (IQR, 43-96) weeks. Thirty-nine episodes of SAEs were reported among 30 (43%) patients, including 5 instances of QTc prolongation, assessed as possibly related to BDQ and/or DLM. The majority (69%) had culture conversion before 24 weeks of treatment. In 61 (87%), use of BDQ and DLM was extended beyond 24 weeks. Successful end-of-treatment outcomes were reported in 49 (70%) patients. CONCLUSIONS: The successful treatment outcomes of this cohort show that regimens including concomitant BDQ and DLM for longer than 24 weeks are effective and can be safely administered on an ambulatory basis. National TB programs globally should scale up access to life-saving DR-TB regimens with new drugs.

Prospective individual patient data meta-analysis: Evaluating convalescent plasma for COVID-19.

As the world faced the devastation of the COVID-19 pandemic in late 2019 and early 2020, numerous clinical trials were initiated in many locations in an effort to establish the efficacy (or lack thereof) of potential treatments. As the pandemic has been shifting locations rapidly, individual studies have been at risk of failing to meet recruitment targets because of declining numbers of eligible patients with COVID-19 encountered at participating sites. It has become clear that it might take several more COVID-19 surges at the same location to achieve full enrollment and to find answers about what treatments are effective for this disease. This paper proposes an innovative approach for pooling patient-level data from multiple ongoing randomized clinical trials (RCTs) that have not been configured as a network of sites. We present the statistical analysis plan of a prospective individual patient data (IPD) meta-analysis (MA) from ongoing RCTs of convalescent plasma (CP). We employ an adaptive Bayesian approach for continuously monitoring the accumulating pooled data via posterior probabilities for safety, efficacy, and harm. Although we focus on RCTs for CP and address specific challenges related to CP treatment for COVID-19, the proposed framework is generally applicable to pooling data from RCTs for other therapies and disease settings in order to find answers in weeks or months, rather than years.

Effectiveness of a nurse-led telephone follow-up in the therapeutic management of patients receiving oral antineoplastic agents: a randomized, multicenter controlled trial (ETICCO study).

PURPOSE: The use of oral cancer drugs (OAD) has increased over the last two decades. The objective of this study was to measure the impact of a nurse-led telephone follow-up in the therapeutic management of patients treated with an OAD regarding toxicity, medication adherence and quality of life. METHODS: A randomized, multicenter, controlled trial was conducted. All consecutive over 18-year-old patients, treated in medical oncology, radiotherapy, or hematology departments, receiving OAD for any cancer were invited to participate to the study. A total of 183 patients treated for solid or hematological cancers with an OAD were randomly assigned to receive a nurse-led telephone follow-up or standard care for 24 weeks. Data were collected between 2015 and 2018. RESULTS: Nurse telephone follow-up did not improve the global score toxicity in the intervention group. However, telephone calls directed by trained nurses induced a significant decrease in number of patients with grade 3 adverse events throughout the follow-up [OR 0.45 (IC à 95%) (0.23, 0.9)](P = 0.03). There was no significant difference in quality of life and medication adherence between groups at any follow-up time point. CONCLUSIONS: In this first French real-life study, the advice provided by qualified nurses via phone calls improved the management of grade 3 toxicities but failed to demonstrate an improvement of all grades of toxicities. More prospective studies are needed to confirm the impact of telephone calls on the toxicities related to OAD. TRIAL REGISTRATION: Clinical trial registration is NCT02459483. Protection committee SUD-ESTI registration is 2015-A00527-42 on 13 April 2015. National Agency for the Safety of Medicines and Health Products registration is 150619-B on the 27 may 2015.