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Record W3104502560 · doi:10.52964/amja.0831

Approach to dyspnoea in pregnancy in the COVID-19 era

2020· article· en· W3104502560 on OpenAlexaff
Anita Banerjee, L. Arrandale, Srividhya Sankaran, Guy Glover, Catherine Nelson‐Piercy

Bibliographic record

VenueAcute Medicine Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineExacerbationPregnancyCoronavirus disease 2019 (COVID-19)Hypoxia (environmental)PandemicMedical diagnosisIntensive care medicineAsthma exacerbationsIntubationCompromiseSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)AsthmaPediatricsInternal medicineDiseaseSurgeryInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

IMPORTANCE: Dyspnoea and hypoxia in pregnant women during the COVID-19 pandemic may be due to causes other than SARS Co-V-2 infection which should not be ignored. Shared decision-making regarding early delivery is paramount. OBJECTIVE: To highlight and discuss the differential diagnoses of dyspnoea and hypoxia in pregnant women and to discuss the risks versus benefit of delivery for maternal compromise. DESIGN, SETTING AND PARTICIPANTS: Case series of two pregnant women who presented with dyspnoea and hypoxia during the COVID-19 pandemic. RESULTS: Two pregnant women presented with dyspnoea and hypoxia. The first case had COVID-19 infection in the 3rd trimester. The second case had an exacerbation of asthma without concurrent COVID-19. Only the first case required intubation and delivery. Both recovered and were discharged home. Conclusion and relevance: Our two cases highlight the importance of making the correct diagnosis and timely decision-making to consider if delivery for maternal compromise is warranted. Whilst COVID-19 is a current healthcare concern other differential diagnoses must still be considered when pregnant women present with dyspnoea and hypoxia.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.729
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.096
GPT teacher head0.383
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2020
Admission routes1
Has abstractyes

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