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Estimated Stroke-Free Survival of Folic Acid Therapy for Hypertensive Adults

2019· article· en· W2996875402 on OpenAlexaff
Tiantian Zhang, Teng-Fei Lin, Yang Wang, Binyan Wang, Xianhui Qin, Feng Xie, Yimin Cui, Yong Huo, Xiaobin Wang, Zugui Zhang, Jie Jiang

Bibliographic record

VenueHypertension · 2019
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsMcMaster UniversityHamilton Health Sciences
FundersNational Institute of General Medical Sciences
KeywordsEnalaprilMedicineStroke (engine)Internal medicineBlood pressureMethylenetetrahydrofolate reductaseInterquartile rangeCardiologyEndocrinologyGastroenterologySurgeryAngiotensin-converting enzymeGenotypeBiochemistryBiology

Abstract

fetched live from OpenAlex

The CSPPT (China Stroke Primary Prevention Trial) demonstrated a significant risk reduction of first stroke in hypertensive patients treated with enalapril plus folic acid compared with those with enalapril alone, but the lifetime stroke-free survival associated with the treatment is unknown. By establishing adjusted models for competing risks and an age-based time scale using data from 19 053 participants of the CSPPT, we estimated lifetime incremental stroke-free survival for enalapril-folic acid versus enalapril alone. Compared with enalapril alone, the enalapril plus folic acid treatment projected a mean lifetime stroke-free survival gain of 1.75 months, with an interquartile range from 0.73 to 2.39 months and the maximum gain up to 12.95 months. Subgroup analyses showed greater gain in stroke-free survival in younger, male patients, those with lower baseline folate levels, higher baseline systolic blood pressure, higher baseline total cholesterol and blood glucose, and with MTHFR (methylenetetrahydrofolate reductase) C677T CT or TT genotype. Overall, besides significant benefit in certain subgroups, enalapril plus folic acid treatment for hypertensive patients is associated with a modest gain in lifetime stroke-free survival, compared with enalapril alone.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.054
GPT teacher head0.305
Teacher spread0.251 · 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 designBench or experimental
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

Citations10
Published2019
Admission routes1
Has abstractyes

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