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A paradigm shift is also required in treatment goals and in performance indicators: reply

2009· article· en· W2092385027 on OpenAlexaffabout
Sylvie Perreault

Bibliographic record

VenueJournal of Internal Medicine · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineContext (archaeology)Intensive care medicineParadigm shiftPopulationClinical PracticePhysical therapyEnvironmental health

Abstract

fetched live from OpenAlex

Dear Sir,We totally agree that there is much more that can be performed to improve health through the control of hypertension; and that the requirement for a major paradigm shift in treatment goals and in performance indicators so as to ensure that control of hypertension does indeed improve health. Our population-based study of drug utilization patterns in a Canadian setting suggests an association with a significant benefit linked with a good adherence to antihypertensive medication and chronic heart failure in the context of primary prevention. We are convinced based on our population-based study that the adherence level to medication is a major gap to be fulfilled, giving that, the mean high adherence level to AH agents was around to 98% during the first year and 96% after 1 year of follow-up compared with 60% and 59.7% for the low adherence level, respectively. Thus, we suggest in addition to the requirement for a major shift in treatment goals and in performance indicators that an assessment of medication adherence should be incorporated into routine clinical practice to ensure a health improvement. A better adherence to pharmacological therapy is one of key factors in determining the success of various therapeutic approaches. Consequently, greater attention should also be paid to this aspect to improve patient outcomes. None declared.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.121
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.184
GPT teacher head0.420
Teacher spread0.236 · 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.

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
Published2009
Admission routes2
Has abstractyes

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