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Record W3112762500 · doi:10.1093/eurjcn/zvaa011

Breaking pandemic chain reactions: telehealth psychosocial support in cardiovascular disease during COVID-19

2021· letter· en· W3112762500 on OpenAlexaff
Géraldine Martorella, Suzanne Fredericks, Julie Sanders, Rochelle Wynne

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2021
Typeletter
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPandemicMedicineContext (archaeology)ExacerbationTelehealthDiseaseIntensive care medicineCoronavirus disease 2019 (COVID-19)PsychosocialHealth careMedical emergencyTelemedicineInfectious disease (medical specialty)Internal medicinePsychiatry

Abstract

fetched live from OpenAlex

This editorial refers to ‘Delivering healthcare remotely to cardiovascular patients during COVID-19: A rapid review of the evidence’, by L. Neubeck et al. doi: 10.1177/1474515120924530 Can one pandemic intensify the existence of another? The outlook for patients with cardiovascular disease (CVD) during COVID-19 is grim. Evidence indicates a relationship exists between COVID-19 and the onset or exacerbation of heart disease; two conditions are categorized as pandemics by the World Health Organization. Pre-diagnosed CVD increases the risk of death from COVID-19 by almost 70% following acute myocardial injury1 and patient behaviours are compounding this risk. Initially, patients were not presenting to the hospital, and activity in cardiology units decreased anywhere from 50% to 80%.2 ‘Time is heart’ and time from symptom onset to first medical contact has in some instances quadrupled3 since late January 2020. In the context of healthcare systems being pushed to their limits in countries with adequate infrastructure and unimaginable outcomes in countries without it, our response to the array of existing and rebound cardiovascular conditions is crucial. As a global society, how do we begin to address or even consider preventing pandemic chain reactions? COVID-19 is characterized by the rapid transmission of the SARS-CoV-2 virus. Symptoms that present at onset include fever, cough, shortness of breath, fatigue, and loss of taste. Long-term outcomes associated with this disease are unclear; however, evidence suggests an increased likelihood for COVID-19 positive patients to experience heart disease; as the trajectory of illness has been shown to significantly affect heart function resulting in myocardial injury (MI). Psychological symptoms related to anxiety, stress, depression, social isolation, and poor sleep quality confound COVID-19 positive patients’ overall risk of heart disease. This is of importance as cardiovascular disease (CVD) is the leading cause of death and disability, worldwide. Thus, the impact of COVID-19 on exacerbating rates of CVD can have potentially devasting international health and economic consequences. Identifying and implementing strategies to reduce the onset of heart disease in patients who have tested positive for the virus or are presenting with psychological symptoms during the COVID-19 pandemic is urgently needed to reduce rates of MI or onset of heart disease.4 The following presents an overview of specific strategies that can be used to mitigate the psychological impact of COVID-19, as well as its long-term effects on the development of CVD. The COVID-19 pandemic has provided an opportunity to reflect on telehealth practice and increase its use judiciously when monitoring needs to be maintained. Most importantly, this crisis has enabled telehealth to become invaluable as it can address isolation, maintain a feeling of social belonging, and decrease anxiety and depression. Telehealth provides a mechanism to support mental health and well-being in association with physical health management.5 Several cognitive and relaxation strategies can be used through telehealth and self-help alternatives that are convenient and cost-effective. For instance, music interventions have been shown to have beneficial effects on the anxiety of persons with CVD as well as on blood pressure, heart, and respiratory rates and sleep, and can be used with or without the presence of a music therapist. Preliminary evidence indicates similar findings in relation to music therapy when delivered to patients diagnosed with COVID-19.6 Recently, mindfulness-based interventions (MBI) have provided additional advantages for patients with CVD with demonstrated effectiveness for improving depression, anxiety, and health-related quality of life.7 Superior benefits have been gained with MBI when contrasted to health education, relaxation training, and supportive psychotherapy; effects are comparable with traditional cognitive behaviour therapy that is demanding and less suitable for self-help formats. MBI have also shown emerging evidence for the reduction of inflammatory immune markers in adult populations, which are known predictors of CVD. It is then not surprising that the American Heart Association (AHA) has released a scientific statement in favour of meditation for cardiovascular risk reduction.8 Since this release, strengthening beneficial evidence continues to emerge in support of MBI for improved psychological and physiological CVD risk factors and outcomes. Importantly, given the context of chronicity related to CVD and the isolation experienced during a pandemic, dyadic psychosocial telehealth interventions provide a contemporary immediate avenue to support patients and their caregivers.9 A brief dyadic MBI has recently shown improvement in health-related quality of life and psychological distress in atrial fibrillation patients.9 Delivery of MBI using telehealth has the capacity to markedly reduce risk in an already vulnerable population. Timely psychosocial interventions require immediate implementation to stem the tide of avoidable COVID-19 consequences. There is Level 1 evidence to support the use of telehealth for patients with CVD.10 Whether the usual barriers to access for patients with CVD such as socioeconomic status, geographical isolation, cultural or linguist diversity, frailty, or chronic comorbid conditions create barriers for patients to access healthcare,10 or a pandemic such as COVID-19, widespread, sustained implementation of telehealth with MBI provides an opportunity to effectively reduce or mitigate psychological impacts of physiological cardiovascular function. Conflict of interest: none declared. The opinions expressed in this article are not necessarily those of the Editors of the European Journal of Cardiovascular Nursing or of the European Society of Cardiology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.002
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0530.038
Insufficient payload (model declined to judge)0.0150.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.362
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations10
Published2021
Admission routes1
Has abstractyes

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