Severity of emergency department presentations due to acute drug toxicity in Europe: a longitudinal analysis over a 6-year period (2014-2019) stratified by sex.

OBJECTIVE: To investigate whether the severity of acute recreation drug toxicity presentations to emergency departments (EDs) in Europe has changed in recent years and to uncover potential sex differences. DESIGN: We analysed presentations to 36 EDs in 24 European countries relating to acute recreational drug toxicity, with separate analysis for presentations involving lone use of cannabis, cocaine, and heroin. As severity markers, we calculated rates of hospitalization, admission to ICU, intubation, and death by annual quarters between 2014 and 2019. Trends on severity over time were estimated by logistic regression. Differences between men and women were assessed by interaction. Sensitivity analysis was performed including only EDs that provided data for all 24 quarters. Analyses of intoxications taken altogether were adjusted by age and sex, while of lone intoxications being also adjusted by ethanol co-ingestion. RESULTS: There were 43 633 presentations (median age = 31 years, interquartile range = 25-40 years, men = 76.5%) resulting in 10 344 hospitalizations (23.9%), 2568 ICU admissions (5.9%), 1391 intubations (3.2%), and 171 deaths (0.39%). Hospitalization, ICU admission and death did not differ by sex, but intubation was more frequent in men (3.4% vs. 2.3%, P < 0.001). No significant changes in the severity of drug intoxications over time were found when considered altogether, neither for lone cannabis (n = 4264) nor cocaine (n = 3562). Conversely, significant increases in hospitalization [odds ratios (OR) = 1.023, 95% confidence interval (CI) = 1.004-1.041], ICU admission (OR = 1.080, 95% CI = 1.042-1.118) and in intubation (OR = 1.049, 95% CI = 1.001-1.099) were detected for lone heroin presentations (n = 1997). Sensitivity analysis (32 245 presentations, 14 EDs, 9 countries) confirmed the overall absence of changes in severity markers (except for death rate, which significantly decreased by quarter: OR = 0.968, 95% CI = 0.943-0.994). Additionally, it suggested an increased risk over time of intubation for cocaine (OR = 1.068, 95% CI = 1.009-1.130) and confirmed the increased risk of ICU admission for heroin (OR = 1.058, 95% CI = 1.013-1.105). Changes in severity over time did not differ according to sex in the main analysis of the whole cohort, while a significantly higher decrease in risk of death in men was found in the sensitivity analysis (OR = 0.894, 95% CI = 0.825-969 vs. OR = 0.949, 95% CI = 0.860-1.048; P interaction = 0.042). CONCLUSIONS: The severity of presentations to European EDs remained mainly unchanged during 2014-2019, but the risk of death may have decreased. Conversely, intubation in lone cocaine and ICU admission in lone heroin intoxications have increased. Although men and women exhibited a similar pattern over the period for the majority of comparisons, our data suggest that women exhibited a smaller decrease of the overall risk of death.

Grayscale Image Statistical Attributes Effectively Distinguish the Severity of Lung Abnormalities in CT Scan Slices of COVID-19 Patients.

Grayscale statistical attributes analysed for 513 extract images taken from pulmonary computed tomography (CT) scan slices of 57 individuals (49 confirmed COVID-19 positive; eight confirmed COVID-19 negative) are able to accurately predict a visual score (VS from 0 to 4) used by a clinician to assess the severity of lung abnormalities in the patients. Some of these attributes can be used graphically to distinguish useful but overlapping distributions for the VS classes. Using machine and deep learning (ML/DL) algorithms with twelve grayscale image attributes as inputs enables the VS classes to be accurately distinguished. A convolutional neural network achieves this with better than 96% accuracy (only 18 images misclassified out of 513) on a supervised learning basis. Analysis of confusion matrices enables the VS prediction performance of ML/DL algorithms to be explored in detail. Those matrices demonstrate that the best performing ML/DL algorithms successfully distinguish between VS classes 0 and 1, which clinicians cannot readily do with the naked eye. Just five image grayscale attributes can also be used to generate an algorithmically defined scoring system (AS) that can also graphically distinguish the degree of pulmonary impacts in the dataset evaluated. The AS classification illustrated involves less overlap between its classes than the VS system and could be exploited as an automated expert system. The best-performing ML/DL models are able to predict the AS classes with better than 99% accuracy using twelve grayscale attributes as inputs. The decision tree and random forest algorithms accomplish that distinction with just one classification error in the 513 images tested.

Grayscale Image Statistical Attributes Effectively Distinguish the Severity of Lung Abnormalities in CT Scan Slices of COVID-19 Patients

Grayscale statistical attributes analysed for 513 extract images taken from pulmonary computed tomography (CT) scan slices of 57 individuals (49 confirmed COVID-19 positive;eight confirmed COVID-19 negative) are able to accurately predict a visual score (VS from 0 to 4) used by a clinician to assess the severity of lung abnormalities in the patients. Some of these attributes can be used graphically to distinguish useful but overlapping distributions for the VS classes. Using machine and deep learning (ML/DL) algorithms with twelve grayscale image attributes as inputs enables the VS classes to be accurately distinguished. A convolutional neural network achieves this with better than 96% accuracy (only 18 images misclassified out of 513) on a supervised learning basis. Analysis of confusion matrices enables the VS prediction performance of ML/DL algorithms to be explored in detail. Those matrices demonstrate that the best performing ML/DL algorithms successfully distinguish between VS classes 0 and 1, which clinicians cannot readily do with the naked eye. Just five image grayscale attributes can also be used to generate an algorithmically defined scoring system (AS) that can also graphically distinguish the degree of pulmonary impacts in the dataset evaluated. The AS classification illustrated involves less overlap between its classes than the VS system and could be exploited as an automated expert system. The best-performing ML/DL models are able to predict the AS classes with better than 99% accuracy using twelve grayscale attributes as inputs. The decision tree and random forest algorithms accomplish that distinction with just one classification error in the 513 images tested.

Evidence on Internal Audit Quality from Transitioning to Remote Audits because of COVID-19

As in-person audits were banned by governments and by company policies due to the COVID-19 pandemic, internal auditors had to transition to remote audits to perform their work. Based on survey responses of internal auditors who have conducted both remote and in-person audits, we find that internal auditors perceive no difference in the efficiency and effectiveness of and stakeholders' reliance on results from remote and in-person audits when considering all responses. However, we also find that perceived efficiency and effectiveness increase the more experience internal auditors have with remote audits. Supplemental analyses show that support from the auditee, but not management or the audit committee, is a central determinant of perceived remote audit success. It is important for internal auditors to consider this later finding in the design of remote audits as it indicates the importance of building support with the auditee to have a successful remote auditing experience.

JAK-STAT inhibition reduces endothelial prothrombotic activation and leukocyte-endothelial proadhesive interactions.

BACKGROUND: Vascular activation is characterized by increased proinflammatory, pro thrombotic, and proadhesive signaling. Several chronic and acute conditions, including Bcr-abl-negative myeloproliferative neoplasms (MPNs), graft-vs-host disease, and COVID-19 have been noted to have increased activation of the janus kinase (JAK)-signal transducer and downstream activator of transcription (STAT) pathways. Two notable inhibitors of the JAK-STAT pathway are ruxolitinib (JAK1/2 inhibitor) and fedratinib (JAK2 inhibitor), which are currently used to treat MPN patients. However, in some conditions, it has been noted that JAK inhibitors can increase the risk of thromboembolic complications. OBJECTIVES: We sought to define the anti-inflammatory and antithrombotic effects of JAK-STAT inhibitors in vascular endothelial cells. METHODS: We assessed endothelial activation in the presence or absence of ruxolitinib or fedratinib by using immunoblots, immunofluorescence, qRT-PCR, and function coagulation assays. Finally, we used endothelialized microfluidics perfused with blood from normal and JAK2V617F+ individuals to evaluate whether ruxolitinib and fedratinib changed cell adhesion. RESULTS: We found that both ruxolitinib and fedratinib reduced endothelial cell phospho-STAT1 and STAT3 signaling and attenuated nuclear phospho-NK-κB and phospho-c-Jun localization. JAK-STAT inhibition also limited secretion of proadhesive and procoagulant P-selectin and von Willebrand factor and proinflammatory IL-6. Likewise, we found that JAK-STAT inhibition reduced endothelial tissue factor and urokinase plasminogen activator expression and activity. CONCLUSIONS: By using endothelialized microfluidics perfused with whole blood samples, we demonstrated that endothelial treatment with JAK-STAT inhibitors prevented rolling of both healthy control and JAK2V617F MPN leukocytes. Together, these findings demonstrate that JAK-STAT inhibitors reduce the upregulation of critical prothrombotic pathways and prevent increased leukocyte-endothelial adhesion.

Ozone air concentration trend attributes assist hours-ahead forecasts from univariate recorded data avoiding exogenous data inputs

Multiple trend attributes extracted from univariate hourly ozone recorded data can be effective in forecasting ozone concentrations at near surface sites for t0 to t + 12 h ahead without recourse to exogeneous variables. The method is evaluated with datasets from three cities less than 100 km apart in central/eastern England, each with more than forty thousand data records for the period 2016 to 2020. The 2020 recorded ozone distribution values are higher in all three cities than for 2016 to 2019 due, at least in part, to COVID-19 lockdowns limiting vehicle emissions. Fifteen attributes extracted from the recorded ozone trend for the past twelve hours are added to each hourly data record. The attributes include seasonal components, some prior-hour values, averages, differences and rates of change. Two multi-linear regression and eight machine-learning (ML) models are used to predict 2019 and 2020 hourly ozone values with the attribute-endowed datasets. The forecasting accuracy of all but one of these models outperforms that of an autoregression model applied to the univariate recorded ozone trends. The support vector machine model achieves the highest ozone forecasting accuracy for hours ahead t0 to t + 12. However, nine of the other models also providing credible and consistent forecasts for the datasets for all three cities. Coefficient analysis of the multi-linear regression models reveals the flexibility with which each of the trend attributes is used in predicting different hours ahead in the t0 to t + 12 range. The attribute-endowed datasets also enable the ML models to assign different relative weights to each attribute for the different hours-ahead being forecasts. This capability introduces additional dimensions that are not available to autoregressive or moving-average models applied to univariate ozone trends.

What the children tell us: the COVID-19 pandemic and how the world should respond.

While the COVID-19 pandemic and associated mitigation measures have had a devastating impact on children and youth (CY), they were rarely consulted or their views incorporated into the approaches to address the pandemic.The main objective of this review is to present the voices and opinions of CY relative to the impact of the first year of the pandemic, on their lives and the lives of their families, and to present their recommendations as a call to action to adults and governments.The origin of this review was an iterative consultation process involving an international collective of Child Health professionals specialising in Child Rights. The recruitment of articles began by soliciting articles written or recommended by members of our international Child Health professional organisation. We then developed search strategies which were conducted in two phases, with the assistance of medical librarians. We limited our search to articles that sought the direct perspectives and experiences of CY in regard to the first year of COVID-19, and published between February 2020 and February 2021.Two phases of searches identified 8131 studies for screening. Following removal of irrelevant literature, 28 studies were included for the final analysis.CY articulate the detrimental impact of the COVID-19 pandemic to their health, education, protection and basic needs, clearly and intelligently. They make specific recommendations to address the issues they elucidate. They state a need for accurate information that is targeted for them. They ask for recognition as stakeholders and social actors in the pandemic response planning and implementation processes.We assert that the recognition of CY as stakeholders in response planning for COVID-19 and other emerging crises such as climate change, must become a statutory requirement for local, national and international policy-makers. Evidence of CY participation should specifically be reported to and tracked by the Committee on the Rights of the Child.

Grayscale image statistics of COVID‐19 patient CT scans characterize lung condition with machine and deep learning

Background Grayscale image attributes of computed tomography (CT) of pulmonary scans contain valuable information relating to patients with respiratory ailments. These attributes are used to evaluate the severity of lung conditions of patients confirmed to be with and without COVID‐19. Method Five hundred thirteen CT images relating to 57 patients (49 with COVID‐19;8 free of COVID‐19) were collected at Namazi Medical Centre (Shiraz, Iran) in 2020 and 2021. Five visual scores (VS: 0, 1, 2, 3, or 4) are clinically assigned to these images with the score increasing with the severity of COVID‐19‐related lung conditions. Eleven deep learning and machine learning techniques (DL/ML) are used to distinguish the VS class based on 12 grayscale image attributes. Results The convolutional neural network achieves 96.49% VS accuracy (18 errors from 513 images) successfully distinguishing VS Classes 0 and 1, outperforming clinicians’ visual inspections. An algorithmic score (AS), involving just five grayscale image attributes, is developed independently of clinicians’ assessments (99.81% AS accuracy;1 error from 513 images). Conclusion Grayscale CT image attributes can be successfully used to distinguish the severity of COVID‐19 lung damage. The AS technique developed provides a suitable basis for an automated system using ML/DL methods and 12 image attributes. Grayscale CT image statistics accurately distinguish the severity of COVID‐19‐related lung conditions Highlights Grayscale image statistics of CT scans can effectively classify lung abnormalities Graphical trends of grayscale statistics distinguish visual assessments COVID‐19 classes Machine/deep learning algorithms predict severity from image grayscale attributes Algorithmic class systems can be established using just five grayscale attributes Confusion matrices provide detailed insight to algorithm prediction capabilities

Validation of a rapid, saliva-based, and ultra-sensitive SARS-CoV-2 screening system for pandemic-scale infection surveillance.

Without any realistic prospect of comprehensive global vaccine coverage and lasting immunity, control of pandemics such as COVID-19 will require implementation of large-scale, rapid identification and isolation of infectious individuals to limit further transmission. Here, we describe an automated, high-throughput integrated screening platform, incorporating saliva-based loop-mediated isothermal amplification (LAMP) technology, that is designed for population-scale sensitive detection of infectious carriers of SARS-CoV-2 RNA. Central to this surveillance system is the "Sentinel" testing instrument, which is capable of reporting results within 25 min of saliva sample collection with a throughput of up to 3840 results per hour. It incorporates continuous flow loading of samples at random intervals to cost-effectively adjust for fluctuations in testing demand. Independent validation of our saliva-based RT-LAMP technology on an automated LAMP instrument coined the "Sentinel", found 98.7% sensitivity, 97.6% specificity, and 98% accuracy against a RT-PCR comparator assay, confirming its suitability for surveillance screening. This Sentinel surveillance system offers a feasible and scalable approach to complement vaccination, to curb the spread of COVID-19 variants, and control future pandemics to save lives.

Same-Day Discharge Post-Transcatheter Aortic Valve Replacement During the COVID-19 Pandemic: The Multicenter PROTECT TAVR Study.

OBJECTIVES: The aim of this study was to determine the safety and efficacy of same-day discharge (SDD) after transcatheter aortic valve replacement (TAVR) during the COVID-19 pandemic. BACKGROUND: The COVID-19 pandemic has placed significant stress on health care systems worldwide. SDD in highly selected TAVR patients can facilitate the provision of essential cardiovascular care while managing competing COVID-19 resource demands. METHODS: Patient selection for SDD was at the discretion of the local multidisciplinary heart team, across 7 international sites. The primary outcome was a composite of cardiovascular death, stroke, myocardial infarction, all-cause readmission, major vascular complications, and new permanent pacemaker (PPM) implantation. RESULTS: From March 2020 to August 2021, 124 of 2,100 patients who underwent elective transfemoral TAVR were selected for SDD. The average age was 78.9 ± 7.8 years, the median Society of Thoracic Surgeons score was 2.4 (IQR: 1.4-4.2), and 32.3% (n = 40) had preexisting PPMs. There were no major vascular complications, strokes, or deaths during the index admission. One patient (0.8%) required PPM implantation for complete heart block and was discharged the same day. No patient required a PPM between discharge home and 30-day follow-up. The composite of cardiovascular death, stroke, myocardial infarction, all-cause readmission, major vascular complications, and new PPM at 30 days occurred in 5.7% patients (n = 6 of 106). CONCLUSIONS: SDD post-TAVR is safe and feasible in selected patients at low risk for adverse clinical events postdischarge. This strategy may have a potential role in highly selected patients even when the COVID-19 pandemic abates.

Local Integrated Air Quality Predictions from Meteorology (2015 to 2020) with Machine and Deep Learning Assisted by Data Mining

Overall air quality local indices can usefully be established by combining normalised values of common individual pollutant values. This reveals distinctive seasonal trends that are strongly influenced by local meteorological conditions. A newly compiled dataset for 2015 to 2020 covering Dallas County (USA), combining six pollutants into a combined local area benchmark (CLAB), is assessed in terms of eleven meteorological variables. It is possible to distinguish the effects of lock-down induced impacts in the CLAB index and some of its component pollutants during 2020. Nine machine learning and three deep learning algorithms are compared in their abilities to predict CLAB from the meteorological variables on supervised and unseen bases. Prediction results for 2019 and 2020 are distinctive for annual and quarterly timeframes. In-depth prediction outlier analysis using a transparent data-matching algorithm provides insight to the few data records for which CLAB is not accurately predicted from ground-level meteorological data.

Same Day Discharge during the COVID-19 Pandemic in Highly Selected Transcatheter Aortic Valve Replacement Patients.

Background: Transcatheter aortic valve replacement (TAVR) with a standardized clinical pathway allows most patients to achieve safe next-day discharge. This approach has been successfully implemented across global centers as part of the Benchmark Program. Considering restricted hospital resources resulting from the COVID-19 pandemic, a modified same day discharge (SDD) clinical pathway was implemented for selected TAVR patients at a single Benchmark site. Methods: All patients accepted for TAVR were assessed for the SDD clinical pathway. Eligibility criteria included adequate social support and accessibility to the TAVR program post-discharge. Patients with preexisting conduction disease were excluded. The clinical pathway comprised of mobilization, bloodwork and electrocardiogram 4 hours post-TAVR and discharge ≥8 hours following groin hemostasis. Results: From June to December 2020, 142 patients underwent TAVR at a single community Benchmark site. Of those, 29 highly selected patients were successfully discharged the same day using the SDD clinical pathway. There were no vascular access complications, permanent pacemaker (PPM) implantation, or mortality in the SDD group during index admission or at 30-day follow-up. When compared to a standard therapy group, there was no statistically significant difference in 30-day cardiovascular readmission. Conclusions: This study demonstrates the safety and feasibility of same day discharge post-TAVR in a highly selected cohort of patients, with no observable difference in safety outcomes when compared to patients who were discharged according to standard institutional practice.Abbreviations: AS: aortic stenosis; ACT: Activated clotting time; AV: atrioventricular; AVB: atrioventricular block; BBB: bundle branch block; CAIC: Canadian Society for Cardiovascular Angiography; CCL: cardiac catheterization laboratory; CT: Computed topography; CV: cardiovascular; IQR: Interquartile Range; IVCD: intraventricular conduction delay; LBBB: left bundle branch block; LOS: length of stay; NDD: next day discharge; PPM: permanent pacemaker; RBBB: right bundle branch block; SCAI: Society for Cardiovascular Angiography and Intervention; SD: standard deviation; SDD: same day discharge; ST: standard therapy; STS PROM: society of thoracic surgeons predicted risk of mortality; TAVR: transcatheter aortic valve replacement; TF: transfemoral; THV: transcatheter heart valve; TTE: transthoracic echocardiogram; VARC: Valve Academic Research Consortium.

Setting a benchmark for resource utilization and quality of care in patients undergoing transcatheter aortic valve implantation in Europe-Rationale and design of the international BENCHMARK registry.

BACKGROUND: The use of transcatheter aortic valve implantation (TAVI) for treating aortic stenosis (AS) has increased exponentially in recent years. Despite the availability of clinical practice guidelines for the management of valvular heart disease, disparities in quality of care (QoC) for TAVI patients remain widespread across Europe. Tailored QoC measures will help to reduce resource utilization and improve patient outcomes without compromising patient safety. Using a clear set of QoC measures, the BENCHMARK registry aims to document the progress that can be achieved if such tailored QoC measures are implemented. METHODS: The BENCHMARK registry (BENCHMARK) is a non-interventional, multicenter registry in patients with severe symptomatic AS undergoing TAVI with a 1- and 12-months follow-up. BENCHMARK will be conducted at 30 centers across Europe and will enroll a total of 2400 consecutive TAVI patients. Patients suffering from severe symptomatic AS who undergo TAVI with a balloon-expandable transcatheter aortic valve will be included. The registry will comprise four phases: (1) a retrospective baseline evaluation phase; (2) an education phase; (3) an implementation phase; and (4) a prospective effect documentation phase (prospective phase). The registry's primary objectives are to reduce the length of hospital stay and accelerate the post-procedural patient recovery pathway, but without compromising safety. The study started in April 2021 and has an estimated completion date of May 2023. DISCUSSION: BENCHMARK will establish QoC measures to reduce resource utilization, intensive care unit bed occupancy, and overall length of hospitalization with uncompromised patient safety post-TAVI (ClinicalTrials.gov Identifier: NCT04579445).

Smart Surveillance

Introduction Networked technologies that collect data from the environment and transmit those data to others are increasingly being built into our homes, schools, streets, offices, and shopping centres. In this way, both Ring and Alexa become vectors of infection that, like mould spores, each alight in a particular location to spread out and join up with other points of infection. Because of this bottom up sideways growth, smartness spreads to create something bigger than the sum of its smart parts. [...]it may in the future spread to others-if there is any lesson of surveillance technology procurement by police, it is that the same access is soon granted to multiple state agencies for a plethora of purposes. From there, the infection spread onto the computers of students and ultimately thereafter into the private houses and bedrooms of students via the mandatory cameras needed, apparently, to check for the "right kind" of behaviour during examinations. [...]the private space of the household itself becomes infected as the camera is used to assess whether the space and its contents are compliant with the rules set by the algorithms that drive the system. Initiatives like Saudi Arabia's 170km linear city of NEOM, or Nevada's proposed Special Investment Zones, take the most extremely exclusionary form of capitalist life and, using smart technologies, attempt to secure it and its entrepreneurial inhabitants or operators against the tide of social and ecological breakdown, even as that tide is rising thanks to the same capitalist processes.

INTERASPIRE: an International Survey of Coronary Patients; Their Cardiometabolic, Renal and Biomarker Status; and the Quality of Preventive Care Delivered in All WHO Regions : In Partnership with the World Heart Federation, European Society of Cardiology, Asia Pacific Society of Cardiology, InterAmerican Society of Cardiology, and PanAfrican Society of Cardiology.

PURPOSE OF REVIEW: To describe the INTERASPIRE scientific protocol-an international survey of secondary prevention of coronary heart disease (CHD). RECENT FINDINGS: This international survey is being conducted through National Societies of Cardiology in selected countries from each of the six WHO regions and has the following overall aims: (i) describe prevalence of cardiometabolic and renal risk factors together with biomarkers in CHD patients; (ii) describe current risk factor management through lifestyle changes and cardioprotective drug therapies; (iii) provide an objective assessment of clinical implementation of preventive care by comparison with the lifestyle and risk factor targets defined in international and national guidelines; (iv) investigate the reasons for variation in preventive cardiology practice between regions and countries; and (v) promote the principles of best preventive cardiology practice. This international survey will provide a unique picture of CHD patients; their cardiometabolic, renal and biomarker status; lifestyle and therapeutic management; and the quality of preventive care provided in all WHO regions.

The COVID-19 Pandemic and Coronary Angiography for ST-Elevation Myocardial Infarction, Use of Mechanical Support, and Mechanical Complications in Canada: A Canadian Association of Interventional Cardiology National Survey.

BACKGROUND: As a result of the COVID-19 pandemic first wave, reductions in ST-elevation myocardial infarction (STEMI) invasive care, ranging from 23% to 76%, have been reported from various countries. Whether this change had any impact on coronary angiography (CA) volume or on mechanical support device use for STEMI and post-STEMI mechanical complications in Canada is unknown. METHODS: We administered a Canada-wide survey to all cardiac catheterization laboratory directors, seeking the volume of CA use for STEMI performed during the period from March 1 2020 to May 31, 2020 (pandemic period), and during 2 control periods (March 1, 2019 to May 31, 2019 and March 1, 2018 to May 31, 2018). The number of left ventricular support devices used, as well as the number of ventricular septal defects and papillary muscle rupture cases diagnosed, was also recorded. We also assessed whether the number of COVID-19 cases recorded in each province was associated with STEMI-related CA volume. RESULTS: A total of 41 of 42 Canadian catheterization laboratories (98%) provided data. There was a modest but statistically significant 16% reduction (incidence rate ratio [IRR] 0.84; 95% confidence interval 0.80-0.87) in CA for STEMI during the first wave of the pandemic, compared to control periods. IRR was not associated with provincial COVID-19 caseload. We observed a 26% reduction (IRR 0.74; 95% confidence interval 0.61-0.89) in the use of intra-aortic balloon pump use for STEMI. Use of an Impella pump and mechanical complications from STEMI were exceedingly rare. CONCLUSIONS: We observed a modest 16% decrease in use of CA for STEMI during the pandemic first wave in Canada, lower than the level reported in other countries. Provincial COVID-19 caseload did not influence this reduction.

INTRODUCTION: Après la première vague de la pandémie de COVID-19, de nombreux pays ont déclaré une réduction de 23 % à 76 % des soins invasifs de l'infarctus du myocarde avec élévation du segment ST (STEMI). On ignore si ce changement a entraîné des répercussions sur le volume d'angiographies coronariennes (AC) ou sur l'utilisation des dispositifs d'assistance mécanique lors de STEMI et des complications mécaniques post-STEMI au Canada. MÉTHODES: Nous avons réalisé un sondage pancanadien auprès de tous les directeurs de laboratoire de cathétérisme cardiaque pour obtenir le volume d'utilisation des AC lors des STEMI réalisées durant la période du 1er mars 2020 au 31 mai 2020 (période de pandémie) et durant 2 périodes témoins (1er mars 2019 au 31 mai 2019 et 1er mars 2018 au 31 mai 2018). Le nombre de dispositifs d'assistance ventriculaire gauche utilisés et le nombre de cas de communications interventriculaires et de ruptures du muscle papillaire diagnostiqués ont également été enregistrés. Nous avons aussi évalué si le nombre de cas de COVID-19 enregistrés dans chaque province était associé au volume d'AC liées aux STEMI. RÉSULTATS: Au total, 41 des 42 laboratoires canadiens de cathétérisme (98 %) ont fourni des données. Lors de la comparaison de la première vague de la pandémie aux périodes témoins, nous avons noté une réduction modeste, mais significative, sur le plan statistique de 16 % (ratio du taux d'incidence [RTI] 0,84; intervalle de confiance à 95 % 0,80-0,87) des AC lors de STEMI. Le RTI n'était pas associé au nombre provincial de cas de COVID-19. Nous avons observé une réduction de 26 % (RTI 0,74; intervalle de confiance à 95 % 0,61-0,89) de l'utilisation de pompes à ballonnet intra-aortique lors de STEMI. L'utilisation d'une pompe Impella et les complications mécaniques après les STEMI étaient extrêmement rares. CONCLUSIONS: Nous avons observé une diminution modeste de 16 % de l'utilisation des AC lors de STEMI durant la première vague de la pandémie au Canada, soit une diminution plus faible que ce que les autres pays ont signalé. Le nombre provincial de cas de COVID-19 n'a pas influencé cette réduction.

The Impact of Covid-19 on Women's Experiences of and Through Football in Buenos Aires.

This research report explores the impact of Covid-19 on women's football in Buenos Aires. The suspension of all forms of football in Argentina as part of the country's hard lockdown measures threatens to undo significant gains made in women's football in recent years. By focussing on the experiences of key actors in a feminist Civil Society Organization (CSO) and a newly professional women's team, respectively, we examine what the pandemic has meant for women's football and for women football players at different levels of the game. We also consider the potential impact of the current situation on the future of women's football in Argentina, representative of wider social advances for women in the country.

Correction: Management of Cardiovascular Disease Patients With Confirmed or Suspected COVID-19 in Limited Resource Settings.

[This corrects the article DOI: 10.5334/gh.823.].