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Pediatric Venous Thromboembolism: Redefining Epidemiology.

2009· article· en· W2562549173 on OpenAlexaboutno aff
Bhuvana A. Setty, Sarah H. O’Brien, Bryce A. Kerlin

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiagnosis codeIncidence (geometry)Healthcare Cost and Utilization ProjectEpidemiologyPediatricsDiseasePsychological interventionIntensive care medicineHealth careInternal medicinePopulation

Abstract

fetched live from OpenAlex

Abstract Abstract 5055 Introduction Pediatric venous thromboembolism (VTE) is a multifactorial disease most commonly seen in children with complex medical conditions. The data regarding associated conditions in children is sparse. The most comprehensive source regarding these associations is derived from the Canadian registry of 137 children with VTE collected from 1990-1992. Objective To refine the spectrum of pediatric VTE associated illnesses, utilizing a large, comprehensive claims database. Methods The Healthcare Cost and Utilization Project (HCUP) Kids' Inpatient Database (KID) 2006 was utilized to identify children <18 years old with in-hospital VTE. These children were identified by the presence of at least one of the following ICD-9-CM diagnosis or procedure codes: 325, 452, 453(.0, .2-.42), 453 (.8-.9), 415 (.0-.11), 38 (.05, .07, .09), or 99.10. The remaining diagnostic ICD-9-CM codes were then utilized to assign a preliminary Complex Chronic Condition (CCC) category for each patient, using previously defined criteria. This categorization was further refined by a manual translation of the diagnostic codes by one of the investigators (BAS or BAK). The incidence of in-hospital VTE by geographic region, hospital type, age, gender, ethnicity, and median household income was estimated. Results 4,731 children met the inclusion criteria (1.76/1,000 discharges). The major underlying illnesses were cardiovascular (18%), malignancy (17%), neuromuscular disease (11%), gastrointestinal (8%), hematology/immunology (7%), and metabolic disease (6%). Trauma and surgical interventions were present in 5 % while 5% of VTE was idiopathic. Renal, respiratory, and autoimmune diseases were less commonly associated with VTE (<5%). Interestingly, the incidence of VTE was highest in the Midwest (2.12/1,000 discharges) and lowest in the South (1.60/1,000 discharges). As seen in previous studies, VTE was more commonly seen in infants and adolescents. There was a slight predominance of males with VTE (1.22:1). 4.2% of the VTE were associated with in-hospital death. Conclusion Pediatric VTE is rarely an idiopathic illness. More commonly it is associated with a chronic underlying medical condition. These data refine our understanding of the spectrum of underlying health conditions in children with VTE. This is limited by the inability to take into account the use of various medications and outpatient interventions that may have contributed to the occurrence of the VTE. Future studies should focus on the epidemiology of VTE within each associated disease category. Disclosures No relevant conflicts of interest to declare.

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)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0120.013
Science and technology studies0.0000.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.300
Teacher spread0.266 · 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 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
Published2009
Admission routes1
Has abstractyes

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