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Abstract 4142894: Multimorbidity Trajectories Across the Lifespan in Patients with Congenital Heart Disease

2024· article· en· W4404360069 on OpenAlexaffabout
Chao Li, Aihua Liu, Solomon Bendayan, Liming Guo, Judith Therrien, Archer Y. Yang, Robyn Tamblyn, Yue Li, Ariane Marelli

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicineMultimorbidityHeart diseaseDiseaseCardiologyGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Befitted from advances in medical care, patients with congenital heart disease (CHD) now survive to adulthood but face elevated risks of both cardiac and non-cardiac complications. Understanding the trajectories of comorbidity development over a patient's lifespan is cornerstone to optimize care expected to improve long-term health outcomes. Research Aim: This study aims to investigate the temporal sequences and evolution of comorbidities in CHD patients across their lifespan. We hypothesize that multimorbidity trajectories in CHD patients are linked to CHD lesion severity and age at onset of specific comorbidities. Methods: Using the Quebec CHD database which comprised data in outpatient visits, hospitalization records and vital status from 1983 to 2017, we designed a longitudinal cohort study evaluating the development of 39 comorbidities coded using ICD-9/10. Temporal sequences were mapped using median age of onset. Associations between disease pairs were quantified by hazard ratios from Cox proportional hazard models adjusting for age, sex, genetic syndrome, competing risks of death, and taking into account the time-varying nature of the predictor diseases. Results: The cohort included 9,764 individuals with severe and 127,729 with non-severe CHD lesions. In severe CHD patients, most comorbidities developed between ages 25 and 40. Comorbidity progression began with childhood cardiovascular diseases, followed by systemic diseases such as diabetes, liver and kidney diseases, and advanced to heart failure and dementia in middle adulthood. In addition, mental disorders emerged in early adulthood and were associated with subsequent development of kidney diseases and dementia. Different trajectories were observed in non-severe CHD patients with 2-3 decades later disease onsets and non-differential onsets between cardiovascular and systemic complications (Figure). Conclusions: Distinct multimorbidity trajectories were observed in CHD patients by CHD lesion severity. In patients with severe CHD lesions, early systemic diseases significantly influenced subsequent complications. These findings highlight the need for well-timed surveillance guidelines and interventions to improve health outcomes.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.829

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.298
Teacher spread0.276 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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