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Record W2038600641 · doi:10.1159/000184563

Smoking Habits and Antihypertensive Treatment

2008· article· en· W2038600641 on OpenAlexaff
Siegfried Heyden, Kenneth A. Schneider, George Fodor

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2008
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicinePlaceboInternal medicineDiureticIncidence (geometry)PopulationObservational studyChlorthalidoneCardiologyClinical trialPathology

Abstract

fetched live from OpenAlex

Five hypertension intervention trials (HDFP, MRFIT, Australian National BP Study, IPPPSH, MRC) were analyzed for the effect of smoking on antihypertensive therapy and final outcome in coronary and all-cause mortality. In addition, an observational study of primary screenees for MRFIT was reviewed. Thus, the hypertensive population evaluated in this paper amounts to 135,851 patients. HDFP revealed that smokers had about twice the mortality rates compared to nonsmokers regardless of the treatment group to which they were randomized. The annual incidence of events in the Australian Study among nonsmokers in the placebo group was even lightly lower than in smokers under active therapy. The results of the MRFIT showed that smoking had a particularly deleterious impact on those hypertensives whose cholesterol levels were elevated. In this group, the coronary death rates were 10 times higher than in nonsmokers with lower cholesterol levels. Although the treatment with beta-blockers reduced the coronary event rates in the MRC and in IPPPSH, this beneficial effect was absent in smokers. However, in trials in which diuretic treatment is effective in nonsmokers, it is equally effective in smokers.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.062
GPT teacher head0.305
Teacher spread0.243 · 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 teacher head, not a consensus.

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

Citations4
Published2008
Admission routes1
Has abstractyes

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