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Identifying Patients for Intensive Blood Pressure Treatment Based on Cognitive Benefit

2023· article· en· W4377091948 on OpenAlexaff
Lama Ghazi, Jincheng Shen, Jian Ying, Catherine G. Derington, Jordana B. Cohen, Zachary A. Marcum, Jennifer S. Herrick, Jordan B. King, Alfred K. Cheung, Jeff D. Williamson, Nicholas M. Pajewski, Nick Bryan, Mark A. Supiano, Joshua A. Sonnen, William S. Weintraub, Tom Greene, Adam P. Bress

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Institute of General Medical SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Institute on Aging
KeywordsMedicineHazard ratioBlood pressureDementiaInternal medicineSprintPost-hoc analysisRandomized controlled trialCognitive declineStroke (engine)Clinical trialPhysical therapyCardiologyConfidence intervalDisease

Abstract

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Importance: Intensive vs standard treatment to lower systolic blood pressure (SBP) reduces risk of mild cognitive impairment (MCI) or dementia; however, the magnitude of cognitive benefit likely varies among patients. Objective: To estimate the magnitude of cognitive benefit of intensive vs standard systolic BP (SBP) treatment. Design, Setting, and Participants: In this ad hoc secondary analysis of the Systolic Blood Pressure Intervention Trial (SPRINT), 9361 randomized clinical trial participants 50 years or older with high cardiovascular risk but without a history of diabetes, stroke, or dementia were followed up. The SPRINT trial was conducted between November 1, 2010, and August 31, 2016, and the present analysis was completed on October 31, 2022. Intervention: Systolic blood pressure treatment to an intensive (<120 mm Hg) vs standard (<140 mm Hg) target. Main Outcomes and Measures: The primary outcome was a composite of adjudicated probable dementia or amnestic MCI. Results: A total of 7918 SPRINT participants were included in the analysis; 3989 were in the intensive treatment group (mean [SD] age, 67.9 [9.2] years; 2570 [64.4%] men; 1212 [30.4%] non-Hispanic Black) and 3929 were in the standard treatment group (mean [SD] age, 67.9 [9.4] years; 2570 [65.4%] men; 1249 [31.8%] non-Hispanic Black). Over a median follow-up of 4.13 (IQR, 3.50-5.88) years, there were 765 and 828 primary outcome events in the intensive treatment group and standard treatment group, respectively. Older age (hazard ratio [HR] per 1 SD, 1.87 [95% CI, 1.78-1.96]), Medicare enrollment (HR per 1 SD, 1.42 [95% CI, 1.35-1.49]), and higher baseline serum creatinine level (HR per 1 SD, 1.24 [95% CI, 1.19-1.29]) were associated with higher risk of the primary outcome, while better baseline cognitive functioning (HR per 1 SD, 0.43 [95% CI, 0.41-0.44]) and active employment status (HR per 1 SD, 0.44 [95% CI, 0.42-0.46]) were associated with lower risk of the primary outcome. Risk of the primary outcome by treatment goal was estimated accurately based on similar projected and observed absolute risk differences (C statistic = 0.79). Higher baseline risk for the primary outcome was associated with greater benefit (ie, larger absolute reduction of probable dementia or amnestic MCI) of intensive vs standard treatment across the full range of estimated baseline risk. Conclusions and Relevance: In this secondary analysis of the SPRINT trial, participants with higher baseline projected risk of probable dementia or amnestic MCI gained greater absolute cognitive benefit from intensive vs standard SBP treatment in a monotonic fashion. Trial Registration: ClinicalTrials.gov Identifier: NCT01206062.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.055
GPT teacher head0.366
Teacher spread0.311 · 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

Citations26
Published2023
Admission routes1
Has abstractyes

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