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Record W3175264687 · doi:10.1161/hyp.68.suppl_1.134

Abstract 134: Association Between Kidney Size, Function and Blood Pressure in Young Adults Born Extremely Preterm

2016· article· en· W3175264687 on OpenAlexaff
Katryn Paquette, Thuy Mai Luu, Anik Cloutier, Marie‐Amélie Lukaszewski, Mariane Bertagnolli, Ramy El-Jalbout, Anne‐Laure Lapeyraque, Anne Monique Nuyt

Bibliographic record

VenueHypertension · 2016
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineBlood pressureRenal functionInternal medicineAnthropometryPopulationNephronYoung adultAmbulatory blood pressureKidney diseaseEndocrinologyCardiology

Abstract

fetched live from OpenAlex

Background: Children born extremely preterm (EPT; ≤29 weeks) have higher blood pressure (BP), lower nephron mass, and increased risk in later life of renal and cardiovascular dysfunction. Whether nephron mass and renal function impact BP in EPT subjects is unknown. We correlated BP with renal size and function in young adults born EPT vs term (T). Methods: Anthropometric measurements, serum and urine chemistry, renal ultrasound, and 24 hour ambulatory BP were obtained in 40 EPT and 40 T born young adults matched for age, sex, race, and socioeconomic status. Comparisons were made using paired T and Wilcoxon signed ranked tests and correlations using Pearson correlation. Results: Study population characteristics are in Table 1. Young adults born EPT had higher systolic BP (SBP) and diastolic BP (DBP), and smaller kidneys (Table 2). Awake SBP and DBP loads in the hypertensive range inversely correlated with kidney size only in EPT participants. Conclusion: Young adults born EPT have higher BP and smaller kidneys vs T controls. EPT young adults with smaller kidneys have a greater BP load in the hypertensive range.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.238
Teacher spread0.217 · 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
Published2016
Admission routes1
Has abstractyes

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