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Record W3103998348 · doi:10.1186/s40981-020-00395-8

Pericardial disease as a rare complication of pediatric appendicitis: a systematic literature search

2020· article· en· W3103998348 on OpenAlexafffund
Bibek Saha, Kazuyoshi Aoyama, Maria-Alexandra Petre, Marina Englesakis, James Robertson, Mark Levine

Bibliographic record

VenueJA Clinical Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicPericarditis and Cardiac Tamponade
Canadian institutionsUniversity Health NetworkMontreal Children's HospitalInstitute for Clinical Evaluative SciencesHospital for Sick Children
FundersHospital for Sick Children
KeywordsMedicinePericardial effusionAppendicitisCardiac tamponadeComplicationCochrane LibrarySurgeryRare diseaseTamponadePericarditisGeneral surgeryDiseaseRadiologyInternal medicineRandomized controlled trial

Abstract

fetched live from OpenAlex

BACKGROUND: Classic symptoms of acute appendicitis are well known but are uncommon and often misinterpreted in pediatric patients, potentially delaying diagnosis and resulting in rare sequelae. METHODS: We conducted a comprehensive systematic literature search of case reports detailing pericardial disease as a rare complication of pediatric appendicitis through MEDLINE, Embase, and Cochrane Databases. Inclusion criteria was that the patient must be < 18 years old and present with both pericardial disease and appendicitis. RESULTS: Our search yielded 7 cases with an average age of 10.3 ± 3.9 years old. The cases involved cardiac tamponade, pericarditis, and/or pericardial effusion. Five cases were diagnosed with appendicitis before complicated by pericardial disease. Most cases had an infectious component, but a majority had negative pericardial fluid cultures. Pleural effusion and abdominal abscesses were other common complications of pediatric appendicitis. CONCLUSION: Awareness of this uncommon relationship may have prognostic value as this may facilitate appropriate management of pericardial effusions, tamponade, and/or appendicitis.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.048
GPT teacher head0.374
Teacher spread0.325 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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