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Record W3096107413 · doi:10.14740/cr1175

Delays in Presentation in Patients With Acute Myocardial Infarction During the COVID-19 Pandemic

2020· article· en· W3096107413 on OpenAlexvenueno aff
Ali Aldujeli, Anas Hamadeh, Kasparas Briedis, Kristen M. Tecson, Joshua Rutland, Žilvinas Krivickas, Simas Stiklioraitis, Kamilija Briedė, Montazar Aldujeili, Ramūnas Unikas, Diana Žaliaduonytė, Remigijus Žaliūnas, Ravi C. Vallabhan, Peter A. McCullough

Bibliographic record

VenueCardiology Research · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePandemicMyocardial infarctionChest painCoronavirus disease 2019 (COVID-19)Emergency medicineInternal medicineRetrospective cohort studyCardiologyEmergency departmentCoronavirusDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has had a major impact on the behavior of patients, as well as on the delivery of healthcare services. With older and more medically vulnerable people tending to stay at home to avoid contracting the virus, it is unclear how the behavior of people with acute myocardial infarction (AMI) has changed. The aim of this study was to determine if delays in presentation and healthcare service delivery for AMI exist during the COVID-19 pandemic compared to the same period a year prior. METHODS: In this single-center, retrospective study, we evaluated patients admitted with ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation myocardial infarction (NSTEMI) during early months of the COVID-19 pandemic (March 11, 2020 to April 20, 2020) compared to patients admitted with same diagnosis during the same period a year prior. RESULTS: There were 30 and 62 patients who presented with NSTEMI in the pandemic and pre-pandemic eras, respectively. The median pain-to-door time was significantly larger during the pandemic compared to pre-pandemic era (1,885 (880, 5,732) vs. 606 (388, 944) min, P < 0.0001). There was a significant delay in door-to-reperfusion time during the pandemic with a median time of 332 (182, 581) vs. 194 (92, 329) min (P = 0.0371). There were 24 (80%) and 25 (42%) patients who presented after 12 h of pain onset in pandemic and pre-pandemic eras, respectively (P = 0.0006). There were 47 and 60 patients who presented with STEMI during the pandemic timeframe of study and pre-pandemic timeframe, respectively. The median pain-to-door time during the pandemic was significantly larger than that of the pre-pandemic (620 (255, 1,500) vs. 349 (146, 659) min, P = 0.0141). There were 22 (47%) and 14 (24%) patients who presented after 12 h of pain onset in the pandemic and pre-pandemic eras, respectively (P = 0.0127). There was not a significant delay in door-to-reperfusion time (P = 0.9833). There were no differences in in-hospital death, stroke, or length of hospitalization between early and late presenters, as well as between pandemic and pre-pandemic eras. CONCLUSIONS: In conclusion, this study found that patients waited significantly longer during the pandemic to seek medical treatment for AMI compared to before the pandemic, and that pandemic-specific protocols may delay revascularization for NSTEMI patients. These findings resulted in more than a threefold increase from the onset of symptoms to revascularization increasing the risks for future complications such as left ventricular dysfunction and cardiovascular death. Efforts should be made to increase patients' awareness regarding consequences of delayed presentation, and to find a balance between hospital evaluation strategies and goals of minimizing total ischemic time.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.176
GPT teacher head0.463
Teacher spread0.287 · 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".

Quick stats

Citations85
Published2020
Admission routes1
Has abstractyes

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