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Record W2911437389 · doi:10.1111/chd.12747

Education as important predictor for successful employment in adults with congenital heart disease worldwide

2019· article· en· W2911437389 on OpenAlexaff
Maayke A. Sluman, Silke Apers, Judith K. Sluiter, Karen Nieuwenhuijsen, Philip Moons, Koen Luyckx, Adrienne H. Kovacs, Corina Thomet, Werner Budts, Junko Enomoto, Hsiao‐Ling Yang, Jamie L. Jackson, Paul Khairy, Stephen C. Cook, Raghavan Subramanyan, Luis Alday, Katrine Eriksen, Mikael Dellborg, Malin Berghammer, Eva Mattsson, Andrew S. Mackie, Samuel Menahem, Maryanne Caruana, Kathy Gosney, Alexandra Soufi, Susan M. Fernandes, Kamila S. White, Edward Callus, Shelby Kutty, Berto J. Bouma, Barbara J.M. Mulder

Bibliographic record

VenueCongenital Heart Disease · 2019
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversity of Alberta HospitalUniversity of AlbertaUniversité de MontréalMontreal Heart InstituteUniversity Health Network
FundersResearch Committee, Aristotle University of Thessaloniki
KeywordsMedicineHeart diseaseDiseaseIntensive care medicineCardiologyInternal medicinePediatrics

Abstract

fetched live from OpenAlex

BACKGROUND: Conflicting results have been reported regarding employment status and work ability in adults with congenital heart disease (CHD). Since this is an important determinant for quality of life, we assessed this in a large international adult CHD cohort. METHODS: Data from 4028 adults with CHD (53% women) from 15 different countries were collected by a uniform survey in the cross-sectional APPROACH International Study. Predictors for employment and work limitations were studied using general linear mixed models. RESULTS: Median age was 32 years (IQR 25-42) and 94% of patients had at least a high school degree. Overall employment rate was 69%, but varied substantially among countries. Higher education (OR 1.99-3.69) and having a partner (OR 1.72) were associated with more employment; female sex (OR 0.66, worse NYHA functional class (OR 0.67-0.13), and a history of congestive heart failure (OR 0.74) were associated with less employment. Limitations at work were reported in 34% and were associated with female sex (OR 1.36), increasing age (OR 1.03 per year), more severe CHD (OR 1.31-2.10), and a history of congestive heart failure (OR 1.57) or mental disorders (OR 2.26). Only a university degree was associated with fewer limitations at work (OR 0.62). CONCLUSIONS: There are genuine differences in the impact of CHD on employment status in different countries. Although the majority of adult CHD patients are employed, limitations at work are common. Education appears to be the main predictor for successful employment and should therefore be encouraged in patients with CHD.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.279
Teacher spread0.270 · 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.

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

Citations45
Published2019
Admission routes1
Has abstractyes

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