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Record W1530955728 · doi:10.3968/4349

Potential Reno-Protective Effects of Telmisartan in Kurd Non-Diabetic Hypertensive Patients in Hawler City

2013· article· en· W1530955728 on OpenAlexvenueno aff
Muslih Abdulkarim Ibrahim

Bibliographic record

VenueAdvances in natural science/Advances in natural sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTelmisartanMedicineBlood pressureAlbuminuriaCreatinineInternal medicineValsartanCardiologyAngiotensin II receptor type 1Renal functionAngiotensin receptorUrologyAngiotensin II

Abstract

fetched live from OpenAlex

Angiotensin II (AII) type I (AT1) receptor blockers are a well known group of drug that indicated principally for the treatment of hypertension as well as for the protection of kidney function in diabetic patients. Telmisartan is a highly selective angiotensin receptor blocker, and the favourable tolerability profile of telmisartan combined with its long elimination half- life ensure the drug provides pronounced reductions in blood pressure (BP) across the entire 24-hour dosage interval. There is relatively very little data and information available to reveal renoprotective activity of telmisartan in nondiabetic low grade albuminuric Kurd hypertensive patients. Our study explores the effect of telmisartan on mean arterial blood pressure and it also sheds more light on its crucial role in lowering albumin: creatinine ratio in Kurd patients. The results of our study demonstrate that telmisartan reduces mean arterial blood pressure significantly, furthermore the study had explained a significant reduction in albuminuria at the second month of treatment which is regarded as a positive sign of renoprotection.

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)0.000
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.272
Teacher spread0.266 · 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
Published2013
Admission routes1
Has abstractyes

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