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Record W3041592048 · doi:10.1111/jgs.16728

Recurrence or Relapse of <scp>COVID</scp> ‐19 in Older Patients: A Description of Three Cases

2020· article· en· W3041592048 on OpenAlexaff
Ludovic Lafaie, Thomas Célarier, Luc Goethals, Bruno Pozzetto, Sylvain Grange, Étienne Ojardias, Cédric Annweiler, Elisabeth Botelho‐Nevers

Bibliographic record

VenueJournal of the American Geriatrics Society · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsWestern University
FundersAgence Nationale de la Recherche
KeywordsMedicineCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakBetacoronavirusCoronavirusYoung adultIntensive care medicinePediatricsGerontologyVirologyInternal medicineDiseaseOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: COVID-19 has infected millions of people worldwide, particularly in older adults. The first cases of possible reinfection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were reported in April 2020 among older adults. DESIGN/SETTING: In this brief report, we present three geriatric cases with two episodes of SARS-CoV-2 infection separated by a symptom-free interval. PARTICIPANTS: The participants of this brief report are three cases of hospitalized geriatric women. MEASUREMENTS/RESULTS: We note clinical and biological worsening during the second episode of COVID-19 for all three patients. Also, there is a radiological aggravation. The second episode of COVID-19 was fatal in all three cases. CONCLUSION: This series of three geriatric cases with COVID-19 diagnosed two times apart for several weeks questions the possibility of reinfection with SARS-CoV-2. It raises questions in clinical practice about the value of testing for SARS-CoV-2 infection again in the event of symptomatic reoccurrence. J Am Geriatr Soc 68:2179-2183, 2020.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.377
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 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

Citations74
Published2020
Admission routes1
Has abstractyes

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Same venueJournal of the American Geriatrics SocietySame topicCOVID-19 Clinical Research StudiesFrench-language works237,207