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Record W3095376501 · doi:10.1016/j.ajoc.2020.100986

Nontraumatic subperiosteal orbital hemorrhage in a laboring patient with gestational immune thrombocytopenic purpura

2020· article· en· W3095376501 on OpenAlexaff
Carl Shen, Siddharth Nath

Bibliographic record

VenueAmerican Journal of Ophthalmology Case Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineThrombocytopenic purpuraDiplopiaComplicationSurgeryPediatricsPopulationVisual acuityInternal medicinePlatelet

Abstract

fetched live from OpenAlex

PURPOSE: To describe a case of nontraumatic subperiosteal orbital hemorrhage (NTSOH) in a laboring patient with gestational immune thrombocytopenic purpura. OBSERVATIONS: A 28-year-old G3P2 laboring patient was urgently evaluated by our ophthalmology unit after she developed sudden onset left eye proptosis, headache, and diplopia in the final hour of pushing. The patient's platelet count was markedly decreased at 45,000 and subsequent work-up established a diagnosis of gestational immune thrombocytopenic purpura. On examination, visual acuity was 20/25 bilaterally and there was a minus two restriction in upgaze in the left eye and a left hypotropia in primary position. Computed tomography demonstrated an elliptical, hyperdense collection at the left orbital roof consistent with NTSOH. The patient was deemed clinically stable through serial examinations and symptoms resolved with conservative management. CONCLUSIONS AND IMPORTANCE: NTSOH is a rare, potentially sight-threatening condition that requires timely ophthalmological evaluation. To our knowledge, this is the first report in the literature of NTSOH in a laboring patient with gestational immune thrombocytopenic purpura. Consideration of the possibility of NTSOH as a complication in this population may allow for appropriate diagnosis, monitoring, and treatment when indicated.

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)0.000
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.278
Teacher spread0.263 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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