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Record W3020920823 · doi:10.3389/fneur.2020.00278

Prognostic Factors for Cognitive Recovery Beyond Early Poststroke Cognitive Impairment (PSCI): A Prospective Cohort Study of Spontaneous Intracerebral Hemorrhage

2020· article· en· W3020920823 on OpenAlexaboutno aff
Li Gong, Yongzhe Gu, Qiuyue Yu, Haichao Wang, Xiaoping Zhu, Qiong Dong, Rong Xu, Yanxin Zhao, Xueyuan Liu

Bibliographic record

VenueFrontiers in Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
FundersShanghai Municipal Health and Family Planning CommissionTongji UniversityScience and Technology Commission of Shanghai MunicipalityNational Natural Science Foundation of China
KeywordsMontreal Cognitive AssessmentMedicineIntracerebral hemorrhageCognitionLogistic regressionProspective cohort studyInternal medicineStroke (engine)DementiaCohortCardiologyCognitive impairmentPsychiatrySubarachnoid hemorrhageDisease

Abstract

fetched live from OpenAlex

Background: Post-stroke cognitive impairment (PSCI) has been increasingly recognized in patients, but some stroke survivors appear to show cognitive improvement beyond the acute stage. The risk factors associated with cognitive recovery after spontaneous intracerebral hemorrhage (ICH) onset have not yet been sufficiently investigated in prospective studies. Objective: We aimed to identify the trajectory of post-ICH cognitive impairment and the association of potential prognostic factors with follow-up cognitive recovery beyond early PSCI. Methods: In this stroke center-based cohort study, 141 consecutive dementia-free patients with spontaneous ICH were included and underwent Montreal Cognitive Assessment (MoCA) evaluation for cognitive function at baseline (within 2 weeks of ICH onset) and the shortened MoCA (short-MoCA) at a 6-month follow-up. To explore the prognostic factors associated with trajectory of cognition after an ICH onset, we adjusted for demographic and vascular risk factors,using multivariate logistic regression analysis. Results: Of the 141 ICH patients, approximately three quarters (106/141) were diagnosed with early PSCI (MoCA score<26) within 2 weeks of ICH onset. The multiple logistic regression indicated independent positive associations between risk of early PSCI and dominant-hemisphere hemorrhage (OR: 8.845 [3.347-23.371]; P < 0.001), mean corpuscular volume (MCV) (OR: 1.079 [1.002-1.162]; P = 0.043), admission systolic blood pressure (sBP) (OR: 1.021 [1.005-1.038]; P = 0.012). Furthermore, 36% (33/90) of ICH survivors who had early PSCI exhibited cognitive recovery at the 6-month follow-up. After examing potential predictors through multiple linear regression based on stepwise, there were independent negative associations between cognitive recovery and dominant hemisphere hemorrhage (OR: 6.955. [1.604-30.162]; P < 0.01), lobar ICH (OR: 8.363 [1.479-47.290]; P = 0.016), years of education ≤ 9 (OR: 5.145 [1.254-21.105]; P = 0.023), and MCV (OR: 1.660 [1.171-2.354]; P = 0.004). Baseline cognitive performance in the domains of visuospatial/executive function, attention, orientation, and language showed positive correlations with cognitive improvement (P < 0.05). Conclusion: In this cohort study of dementia-free survivors of ICH, our results show that one in three early PSCI survivors exhibit cognitive recovery, in relation to dominant-hemisphere hematoma, lobar ICH, educational history, and MCV levels. Future clinical trials including ICH survivors with cognitive dysfunction should assess these factors.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.255
Teacher spread0.243 · 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.

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

Citations39
Published2020
Admission routes1
Has abstractyes

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