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Record W4283705923 · doi:10.1155/2022/2466982

Plasma Neurofilament Light Chain Is Associated with Cognitive Impairment after Posterior Circulation Stroke

2022· article· en· W4283705923 on OpenAlexaboutno aff
Lianyan Jiang, Zhi‐Qiang Wang, Rongyu Wang, Mao Li, Yaodan Zhang, Dongdong Yang

Bibliographic record

VenueEvidence-based Complementary and Alternative Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
FundersHealth and Family Planning Commission of Sichuan Province
KeywordsMontreal Cognitive AssessmentMedicineInternal medicineLogistic regressionBiomarkerStroke (engine)Cognitive impairmentCognitionCardiologyDiseasePsychiatry

Abstract

fetched live from OpenAlex

Background. Neurofilament light chain (NfL) is a biomarker for large-caliber axonal degeneration in the subcortex. The purpose of this research was to examine the relationship between plasma neurofilament light chain (pNfL) and cognitive impairment following a posterior circulation stroke. Methods. Patients over the age of 18 with their first-ever acute ischemic stroke (AIS) of the posterior cerebral circulation within 24 h of symptom onset were included from July 1, 2017, to December 31, 2019. Blood samples were collected within 48 h after the stroke. The Montreal Cognitive Assessment (MOCA) (MOCA &lt; 26) was adopted to define poststroke cognitive impairment (PSCI) 90 days after stroke onset. Results. A total of 264 patients were analyzed in this research 101 (38.30%) patients were clinically diagnosed with PSCI. The PNfL concentration was significantly higher in the PSCI group compared with the non-PSCI group ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>p</a:mi> <a:mo>&lt;</a:mo> <a:mn>0.001</a:mn> </a:math> ). The pNfL concentration (OR 1.044; <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>p</c:mi> <c:mo>&lt;</c:mo> <c:mn>0.001</c:mn> </c:math> ) remained to be a significant predictor for PSCI after a multivariable logistic regression analysis, even after adjusting for factors including age, sex, education background (OR 1.044; <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>p</e:mi> <e:mo>&lt;</e:mo> <e:mn>0.001</e:mn> </e:math> ), baseline NIHSS, infarct volume, and TOAST classification (OR 1.035; <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mi>p</g:mi> <g:mo>&lt;</g:mo> <g:mn>0.001</g:mn> </g:math> ). The diagnostic efficacy of pNfL concentration for PSCI was then explored with a ROC analysis. The optimum pNfL concentration threshold was 38.12 pg/ml, with a sensitivity of 78.20%, a specificity of 66.9%, and an AUC of 0.782 ( <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:mi>p</i:mi> <i:mo>&lt;</i:mo> <i:mn>0.001</i:mn> </i:math> ). Conclusion. This research showed that pNfL concentration, independent of established conventional risk factors, could predict the cognitive impairment in 90 days following posterior circulation stroke.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.049
GPT teacher head0.310
Teacher spread0.260 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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