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Record W4282922101 · doi:10.1161/jaha.121.024735

Underdiagnosis and Undertreatment of Modifiable Cardiovascular Risk Factors Among Survivors of Childhood Cancer

2022· article· en· W4282922101 on OpenAlexaff
Eric J. Chow, Yan Chen, Gregory T. Armstrong, Laura‐Mae Baldwin, Casey Cai, Todd M. Gibson, Melissa M. Hudson, Aaron McDonald, Paul C. Nathan, Jeffrey E. Olgin, Karen L. Syrjala, Emily S. Tonorezos, Kevin C. Oeffinger, Yutaka Yasui

Bibliographic record

VenueJournal of the American Heart Association · 2022
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of TorontoUniversity of Alberta
FundersNational Institute of Biomedical Imaging and BioengineeringNational Cancer Institute
KeywordsMedicineNational Health and Nutrition Examination SurveyOdds ratioDyslipidemiaRisk factorOverweightCancerCross-sectional studyObesityInternal medicinePediatricsEnvironmental healthPopulationPathology

Abstract

fetched live from OpenAlex

Background Determine the prevalence and predictors associated with underdiagnosis and undertreatment of modifiable cardiovascular disease (CVD) risk factors (hypertension, dyslipidemia, glucose intolerance/diabetes) among adult survivors of childhood cancer at high risk of premature CVD. Methods and Results This was a cross‐sectional study of adult‐aged survivors of childhood cancer treated with anthracyclines or chest radiotherapy, recruited across 9 US metropolitan regions. Survivors completed questionnaires and in‐home clinical assessments. The comparator group was a matched sample from the National Health and Nutrition Examination Survey. Multivariable logistic regression estimated the risk (odds ratios) of CVD risk factor underdiagnosis and undertreatment among survivors compared with the National Health and Nutrition Examination Survey. Survivors (n=571; median age, 37.7 years and 28.5 years from cancer diagnosis) were more likely to have a preexisting CVD risk factor than the National Health and Nutrition Examination Survey (n=345; P <0.05 for all factors). While rates of CVD risk factor underdiagnosis were similar (27.1% survivors versus 26.1% National Health and Nutrition Examination Survey; P =0.73), survivors were more likely undertreated (21.0% versus 13.9%, P =0.007; odds ratio, 1.8, 95% CI, 1.2–2.7). Among survivors, the most underdiagnosed and undertreated risk factors were hypertension (18.9%) and dyslipidemia (16.3%), respectively. Men and survivors who were overweight/obese were more likely to be underdiagnosed and undertreated. Those with multiple adverse lifestyle factors were also more likely undertreated (odds ratio, 2.2, 95% CI, 1.1–4.5). Greater health‐related self‐efficacy was associated with reduced undertreatment (odds ratio, 0.5; 95% CI, 0.3–0.8). Conclusions Greater awareness of among primary care providers and cardiologists, combined with improving self‐efficacy among survivors, may mitigate the risk of underdiagnosed and undertreated CVD risk factors among adult‐aged survivors of childhood cancer. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03104543.

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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.275
Teacher spread0.259 · 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

Citations68
Published2022
Admission routes1
Has abstractyes

Explore more

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