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Record W4380739939 · doi:10.1212/wnl.0000000000207479

Associations of Multimorbidity With Stroke Severity, Subtype, Premorbid Disability, and Early Mortality

2023· article· en· W4380739939 on OpenAlexfundno aff
Matthew B. Downer, Linxin Li, Samantha Carter, Sally Beebe, Peter M. Rothwell

Bibliographic record

VenueNeurology · 2023
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchClarendon FundUniversity of OxfordNational Institute for Health and Care ResearchWellcome Trust
KeywordsMedicineComorbidityStroke (engine)Modified Rankin ScaleInternal medicineConfoundingHazard ratioPopulationLogistic regressionOdds ratioProportional hazards modelPhysical therapyIschemic strokeConfidence intervalIschemia

Abstract

fetched live from OpenAlex

<h3>Background and Objectives:</h3> Patients with multimorbidity are under-represented in clinical trials. Inclusion in stroke trials is often limited by exclusion based on pre-morbid disability, concerns about worse post-stroke outcomes in acute treatment trials, and a possibly increased proportion of haemorrhagic vs ischaemic stroke in prevention trials. Multimorbidity is associated with increased mortality after stroke, but it is unclear whether this is driven by increased stroke severity, or is confounded by particular stroke subtypes or premorbid disability. We aimed to determine the independent association of multimorbidity with stroke severity taking account of these main potential confounders. <h3>Methods:</h3> In a population-based incidence study (Oxford Vascular Study; 2002-2017), pre-stroke multimorbidity (Charlson Comorbidity Index-CCI; unweighted/weighted) in all first-in-study strokes was related to post-acute severity (≈24 hours; NIH Stroke Scale-NIHSS), stroke subtype (haemorrhagic vs ischaemic; Trial of Org 10172 in Acute Stroke Treatment-TOAST), and pre-morbid disability (modified Rankin score/mRS≥2) using age/sex-adjusted logistic and linear regression models, and to 90-day mortality using Cox proportional hazard models. <h3>Results:</h3> Among 2492 patients (mean/SD age=74.5/13.9; 1216/48.8% male; 2160/86.7% ischaemic strokes; mean/SD NIHSS=5.7/7.1), 1402/56.2% had at least one CCI comorbidity, and 700/28.1% had multimorbidity. Although multimorbidity was strongly related to pre-morbid mRS≥2 (aOR for per CCI comorbidity=1.42, 1.31-1.54, <i>p</i>&lt;0.001) and comorbidity burden was crudely associated with increased severity of ischaemic stroke (OR per comorbidity: 1.12, 1.01-1.23 for NIHSS 5-9, <i>p</i>=0.027; 1.15, 1.06-1.26, for NIHSS≥10; <i>p</i>=0.001), no association with severity remained after stratification by TOAST subtype (aOR=1.02, 0.90-1.14, <i>p</i>=0.78 for NIHSS 5-9 vs 0-4: 0.99, 0.91-1.07, <i>p</i>=0.75 for NIHSS≥10vs0-4), or within any individual subtype. The proportion of intracerebral haemorrhage versus ischaemic stroke was lower in patients with multimorbidity (aOR per comorbidity=0.80, 0.70-0.92, <i>p</i>&lt;0.001), and multimorbidity was only weakly associated with 90-day mortality after adjustment for age, sex, severity, and pre-morbid disability (aHR per comorbidity=1.09, 1.04-1.14, <i>p</i>&lt;0.001). Results were unchanged using the weighted CCI. <h3>Discussion:</h3> Multimorbidity is common in patients with stroke and is strongly related to pre-morbid disability, but is not independently associated with increased ischaemic stroke severity. Greater inclusion of patients with multimorbidity is unlikely therefore to undermine the effectiveness of interventions in clinical trials, but would increase external validity.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.065
GPT teacher head0.340
Teacher spread0.275 · 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

Citations31
Published2023
Admission routes1
Has abstractyes

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