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Record W2803452170 · doi:10.1002/pbc.27225

Pediatric superior vena cava syndrome: An evidence‐based systematic review of the literature

2018· review· en· W2803452170 on OpenAlexaff
Fadi Nossair, Peter Schoettler, Joanne P. Starr, Anthony K.C. Chan, Ivan I. Kirov, Bosco Paes, Arash Mahajerin

Bibliographic record

VenuePediatric Blood & Cancer · 2018
Typereview
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsMcMaster UniversityThrombosis and Atherosclerosis Research Institute
FundersUniversity of California, Irvine
KeywordsMedicineSuperior vena cava syndromeThrombosisPresentation (obstetrics)Intensive care medicinePediatricsSuperior vena cavaInternal medicineSurgery

Abstract

fetched live from OpenAlex

Superior vena cava syndrome (SVCS) results in vascular, respiratory, and neurologic compromise. A systematic search was conducted to determine the prevalence of pediatric SVCS subtypes and identify clinical characteristics/treatment strategies that may influence overall outcomes. Data from 101 case reports/case series (142 patients) were analyzed. Morbidity (30%), mortality (18%), and acute complications (55%) were assessed as outcomes. Thrombosis was present in 36%, with multi-modal anticoagulation showing improved outcome by >50% (P = 0.004). Infant age (P = 0.04), lack of collaterals (P = 0.007), acute complications (P = 0.005), and clinical presentation may have prognostic utility that could influence clinical decisions and surveillance practices in pediatric SVCS.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0100.010
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.079
GPT teacher head0.409
Teacher spread0.330 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations49
Published2018
Admission routes1
Has abstractyes

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