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Record W3032570197 · doi:10.26355/eurrev_202005_21369

Severe acute dried gangrene in COVID-19 infection: a case report.

2020· article· en· W3032570197 on OpenAlexaff
E. Novara, Eleonora Molinaro, I. Benedetti, R. Bonometti, E.C. Lauritano, Riccardo Boverio

Bibliographic record

VenuePubMed · 2020
Typearticle
Languageen
FieldMedicine
TopicDermatological and COVID-19 studies
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Gangrene2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineVirologySurgeryInternal medicineOutbreakInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

OBJECTIVE: Coronavirus disease 2019 (COVID-19) related coagulopathy may be the first clinical manifestation even in non-vasculopathic patients and is often associated with worse clinical outcomes. CASE PRESENTATION: A 78 years old woman was admitted to the Emergency Unit with respiratory symptoms, confusion and cyanosis at the extremity, in particular at the nose area, hands and feet fingers. A nasal swab for COVID-19 was performed, which resulted positive, and so therapy with doxycycline, hydroxychloroquine and antiviral agents was started. At admission, the patient was hemodynamically unstable requiring circulatory support with liquids and norepinephrine; laboratory tests showed disseminated intravascular coagulation (DIC). During hospitalization, the clinical condition worsened and the cyanosis of the nose, fingers, and toes rapidly increased and became dried gangrene in three days. Subsequently, the neurological state deteriorated into a coma and the patient died. DISCUSSION: In severe cases, COVID-19 could be complicated by acute respiratory disease syndrome, septic shock, and multi-organ failure. This case report shows the quick development of dried gangrene in a non-vasculopathic patient, as a consequence of COVID-19's coagulopathy and DIC. CONCLUSIONS: In our patient, COVID-19 related coagulopathy was associated with poor prognosis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.069
GPT teacher head0.303
Teacher spread0.234 · 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 teacher head, 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

Citations31
Published2020
Admission routes1
Has abstractyes

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