MétaCan
Menu
Back to cohort
Record W4388292280 · doi:10.1177/23969873231211157

Association between blood pressure variability and outcomes after endovascular thrombectomy for acute ischemic stroke: An individual patient data meta-analysis

2023· review· en· W4388292280 on OpenAlexafffund
Lina Palaiodimou, Raed A. Joundi, Aristeidis H. Katsanos, Niaz Ahmed, Joon‐Tae Kim, Nitin Goyal, Ilko Maier, Adam de Havenon, Mohammad Anadani, Marius Matusevicius, Eva Mistry, Pooja Khatri, Adam S Arthur, Amrou Sarraj, Shadi Yaghi, Ashkan Shoamanesh, Luciana Catanese, Marios‐Nikos Psychogios, Konark Malhotra, Alejandro M Spiotta, Sofia Vassilopoulou, Konstantinos Tsioufis, Else Charlotte Sandset, Andrei V. Alexandrov, Nils Petersen, Georgios Tsivgoulis

Bibliographic record

VenueEuropean Stroke Journal · 2023
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeMcMaster UniversityHeart and Stroke Foundation of Canada
KeywordsMedicineModified Rankin ScaleThrombolysisStroke (engine)Internal medicineOdds ratioBlood pressureCardiologyIschemic strokeLogistic regressionMyocardial infarctionIschemia

Abstract

fetched live from OpenAlex

INTRODUCTION: Data on the association between blood pressure variability (BPV) after endovascular thrombectomy (EVT) for acute ischemic stroke (AIS) and outcomes are limited. We sought to identify whether BPV within the first 24 hours post EVT was associated with key stroke outcomes. METHODS: We combined individual patient-data from five studies among AIS-patients who underwent EVT, that provided individual BP measurements after the end of the procedure. BPV was estimated as either systolic-BP (SBP) standard deviation (SD) or coefficient of variation (CV) over 24 h post-EVT. We used a logistic mixed-effects model to estimate the association [expressed as adjusted odds ratios (aOR)] between tertiles of BPV and outcomes of 90-day mortality, 90-day death or disability [modified Rankin Scale-score (mRS) > 2], 90-day functional impairment (⩾1-point increase across all mRS-scores), and symptomatic intracranial hemorrhage (sICH), adjusting for age, sex, stroke severity, co-morbidities, pretreatment with intravenous thrombolysis, successful recanalization, and mean SBP and diastolic-BP levels within the first 24 hours post EVT. RESULTS: There were 2640 AIS-patients included in the analysis. The highest tertile of SBP-SD was associated with higher 90-day mortality (aOR:1.44;95% CI:1.08-1.92), 90-day death or disability (aOR:1.49;95% CI:1.18-1.89), and 90-day functional impairment (adjusted common OR:1.42;95% CI:1.18-1.72), but not with sICH (aOR:1.22;95% CI:0.76-1.98). Similarly, the highest tertile of SBP-CV was associated with higher 90-day mortality (aOR:1.33;95% CI:1.01-1.74), 90-day death or disability (aOR:1.50;95% CI:1.19-1.89), and 90-day functional impairment (adjusted common OR:1.38;95% CI:1.15-1.65), but not with sICH (aOR:1.33;95% CI:0.83-2.14). CONCLUSIONS: BPV after EVT appears to be associated with higher mortality and disability, independently of mean BP levels within the first 24 h post EVT. BPV in the first 24 h may be a novel target to improve outcomes after EVT for AIS.

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)0.022
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.038
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.051
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.112
GPT teacher head0.359
Teacher spread0.247 · 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.

Study designMeta-analysis
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 routes2
Has abstractyes

Explore more

Same venueEuropean Stroke JournalSame topicAcute Ischemic Stroke ManagementFrench-language works237,207