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Record W3182332907 · doi:10.1111/hdi.12964

Elevated serum thyrotropin levels and endothelial dysfunction in a prospective hemodialysis cohort

2021· article· en· W3182332907 on OpenAlexvenueno aff
Amy S. You, Matthew J. Budoff, Irfan Zeb, Naser Ahmadi, Alejandra García Novoa, Ferdinand Flores, Sajad Hamal, April Kinninger, Christopher Dailing, Tracy Nakata, Csaba P. Kövesdy, Danh V. Nguyen, Gregory A. Brent, Kamyar Kalantar‐Zadeh, Connie M. Rhee

Bibliographic record

VenueHemodialysis International · 2021
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsMedicineHemodialysisQuartileInternal medicineEndothelial dysfunctionCardiologyProspective cohort studyPopulationThyroid functionArea under the curveLogistic regressionGastroenterologyEndocrinologySurgeryThyroidConfidence interval

Abstract

fetched live from OpenAlex

INTRODUCTION: Thyroid dysfunction is a highly prevalent yet under-recognized complication in hemodialysis patients. In the general population, hypothyroidism has been associated with endothelial dysfunction due to impaired vasodilator synthesis and activity. Little is known about the association of serum thyrotropin (TSH), the most sensitive and specific single biochemical metric of thyroid function, with endothelial function in hemodialysis patients. METHODS: In a secondary analysis of 99 patients from the Anti-inflammatory and anti-oxidative nutrition in hypoalbuminemic dialysis patients (AIONID) trial, we examined measurements of serum TSH and endothelial function ascertained by fingertip digital thermal monitoring (DTM), a novel method used to measure micro-vascular reactivity, collected within a 90-day period. DTM was used to measure changes in fingertip temperature during and after an ischemic stimulus (blood pressure cuff occlusion) as an indicator of changes in blood flow, and two DTM indices were assessed, namely adjusted (a) Temperature Rebound (TR), defined as the maximum temperature rebound post-cuff deflation, and adjusted (b) Area Under the Temperature Curve (TMP-AUC), defined as area under the curve between the maximum and minimum temperatures. We examined the relationship between serum TSH with impaired TR (separately) and TMP-AUC (both defined as less than the median level of observed values) using multivariable logistic regression. FINDINGS: In unadjusted and case-mix analyses, higher serum TSH levels (defined as the three highest quartiles) were associated with lower (worse) TR (ref: lowest TSH quartile): ORs (95% CI) 2.64 (1.01-6.88) and 2.85 (1.08-7.57), respectively. In unadjusted and case-mix analyses, higher TSH levels were associated with lower (worse) TMP-AUC: ORs (95% CI) 2.64 (1.01-6.88) and 2.79 (1.06-7.38), respectively. DISCUSSION: In HD patients, higher serum TSH levels were associated with worse micro-vascular reactivity measured by DTM. Further studies are needed to determine if thyroid hormone supplementation improves endothelial function in hemodialysis patients with lower levels of thyroid function.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.260
Teacher spread0.247 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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