MétaCan
Menu
Back to cohort
Record W179557742 · doi:10.1093/pch/19.10.533

Children who ‘grow up’ in hospital: Inpatient stays of six months or longer

2014· article· en· W179557742 on OpenAlexaffabout
Dawn Davies, Dawn Hartfield, Tara Wren

Bibliographic record

VenuePaediatrics & Child Health · 2014
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsStollery Children's HospitalAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsMedicinePediatricsMedical recordRetrospective cohort studyPopulationEmergency medicineSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the clinical course of all infants and children hospitalized for six consecutive months (180 days) or longer at a tertiary/quaternary children's hospital in Western Canada. METHODS: A retrospective review of medical records for all eligible patients from January 1, 2007 to December 31, 2012 at Stollery Children's Hospital (Edmonton, Alberta) was performed. RESULTS: A total of 61 patients experienced 64 eligible hospitalizations. The mean length of stay was 326 days, corresponding to a cumulative 20,892 hospital days (57.2 patient-years). Prevalent procedures resulting in long hospitalization were long-term tracheostomy ± ventilation in 32 (52%) patients, need for organ transplantation in 24 (39%) with completed transplantation in 15 (25%), and ventricular-assist devices (VADs) in seven (11%). Sixteen (26%) patients in the study group died, and 16 (26%) were placed in long-term care or out-of-home care at the end of their long hospitalization. Of children displaced from their family home, 14 (88%) were Aboriginal. CONCLUSION: Infants and children who experience very long hospitalizations have complex illnesses, with substantial risk for mortality and a high rate of displacement from their families after discharge. Aboriginal children appear to be particularly vulnerable to displacement and problem solving for this population must be undertaken, involving a variety of stakeholders.

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)0.001
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 score0.044
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.009
GPT teacher head0.270
Teacher spread0.261 · 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

Citations25
Published2014
Admission routes2
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicCongenital Heart Disease StudiesFrench-language works237,207