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Secondary Prevention of Stroke in Saskatchewan, Canada: Hypertension Control

2012· article· en· W1956267027 on OpenAlexaffabout
Janelle Ann Bartsch, Gary Teare, Anne Neufeld, Nedeene Hudema, Nazeem Muhajarine

Bibliographic record

VenueInternational Journal of Stroke · 2012
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsSaskatchewan PolytechnicSaskatchewan Health Quality CouncilUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineStroke (engine)Logistic regressionBlood pressureSecondary preventionEmergency medicineRisk factorMedical recordHealth carePhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In the province of Saskatchewan, Canada, stroke is the third leading cause of death as well as the major cause of adult disability. Once a person suffers a stroke or transient ischemic attack (TIA), they are at high risk for having a secondary stroke. Hypertension (elevated blood pressure) is the single most important modifiable risk factor for both first and recurrent stroke, and is thus an important risk factor to be controlled. According to the Canadian Stroke Strategy (CSS) Best Practice Recommendations, blood pressure lowering treatment should be initiated before discharge from hospital for all stroke/TIA patients. The purpose of this study was to examine the quality of medically driven secondary stroke prevention care in Saskatchewan as applied to hypertension control. AIMS: The objectives of the study were to: (1) develop methodology and calculate a secondary stroke process of care measure using available data in Saskatchewan, based on an appropriate hypertension therapy indicator recommendation from the CSS Performance Measurement Manual; (2) examine variation in secondary stroke prevention hypertensive care among the Saskatchewan Regional Health Authorities; and (3) investigate factors associated with receiving evidence-based hypertensive secondary stroke prevention. METHODS: This multi-year cross-sectional study was an analysis of deidentified health data derived from linkage of administrative health data. A select indicator from the CSS Performance Measurement Manual that measures adherence to a CSS Best Practice Guidelines concerning use of antihypertensive medications for secondary stroke prevention was calculated. Logistic regression was used to quantify the association of patient demographic and socioeconomic characteristics and geographic location of care with receipt of guideline-recommended hypertensive secondary stroke prevention. The target population was all Saskatchewan residents who were hospitalized in Saskatchewan for a stroke or TIA between April 1, 2001 and March 31, 2008. RESULTS: The results of this study indicate that the management of hypertension for secondary stroke prevention is sub-optimal in Saskatchewan. Although there was some improvement over the time period, approximately 40% of patients were not taking antihypertensives at 90 days after discharge from acute care. The correlates, urban/non-urban, previous use of antihypertensive drugs and effect of age modified by sex, were found to be significantly associated with receiving hypertensive secondary stroke prevention, suggesting there are modifiable factors that contribute to variations in this form of secondary stroke care quality in Saskatchewan. CONCLUSIONS: The results of this study suggest that there is a need for province-wide improvement to secondary stroke prevention in Saskatchewan, Canada.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.048
Threshold uncertainty score0.350

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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

Citations6
Published2012
Admission routes2
Has abstractyes

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