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Record W3022141899 · doi:10.14740/cr1074

Coronavirus Disease 2019 With Acute Respiratory Distress Syndrome Mimicking Heart Failure Exacerbation: Time to Rethink

2020· article· en· W3022141899 on OpenAlexvenueno aff
Yasar Sattar, Michael Connerney, Waqas Ullah, Hiba Rauf, Sahil Mamtani, Stephen Luddington, M. Chadi Alraies

Bibliographic record

VenueCardiology Research · 2020
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineExacerbationARDSHeart failureCardiologyInternal medicineAcute decompensated heart failureAcute respiratory distressPulmonary edemaNatriuretic peptideIntensive care medicineCoronavirus disease 2019 (COVID-19)Respiratory failureRespiratory distressLungDiseaseAnesthesiaInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

A 67-year-old man with a prior heart failure presented with fever, cough and dyspnea for 4 days. Physical examination showed bilateral rales on the lung exam, yet no lower extremity edema. The combination of symptoms, elevated inflammatory markers, normal baseline pro-B-type natriuretic peptide, PaO 2 /FiO 2 < 300 and positive swab suggested coronavirus disease 2019 (COVID-19) with acute respiratory distress syndrome (ARDS) rather than heart failure exacerbation. We discuss the challenges in management of ARDS in COVID-19 patients that may initially mimic as acute exacerbation of heart failure. Cardiol Res. 2020;11(3):196-199 doi: https://doi.org/10.14740/cr1074

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0020.001

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 head0.073
GPT teacher head0.391
Teacher spread0.318 · 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 designCase report
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

Citations4
Published2020
Admission routes1
Has abstractyes

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