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Record W2789068955 · doi:10.1055/s-0037-1620279

Nonoperative Treatment of Appendicitis during Pregnancy in a Remote Area

2018· article· en· W2789068955 on OpenAlexaboutno aff
Anne-Kathrine Reus Carstens, Lise Bangsgaard Fensby, Luit Penninga

Bibliographic record

VenueAmerican Journal of Perinatology Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePregnancyAppendicitisPerforationAntibioticsSurgeryGeneral surgeryPopulationIntensive care medicineObstetrics

Abstract

fetched live from OpenAlex

Appendicitis is the most common nonobstetric surgical disease during pregnancy. Appendicitis during pregnancy is associated with an increased risk of morbidity and perforation compared with the general population. Furthermore, it may cause preterm birth and fetal loss, and quick surgical intervention is the established treatment option in pregnant women with appendicitis. In Greenland, geographical distances are very large, and weather conditions can be extreme, and surgical care is not always immediately available. Hence, antibiotic treatment is often initiated as a bridge-to-surgery. We report on a pregnant Greenlandic Inuit woman with appendicitis who was treated with intravenous antibiotics. Antibiotic treatment was successful before surgical care became available and the patient was not operated. No complications occurred, and further pregnancy was uneventful. Our case suggests that antibiotic treatment of appendicitis during pregnancy as a bridge-to-surgery may be a sensible treatment option in remote areas, where no surgical care is immediately available. In some cases, antibiotic treatment may turn out to be definitive treatment.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.300
Teacher spread0.286 · 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 designObservational
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

Citations33
Published2018
Admission routes1
Has abstractyes

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