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Record W3111792256 · doi:10.22146/bns.v19i1.61892

Korelasi kadar high-sensitivity C-reactive protein dengan gangguan kognitif pada pasien stroke iskemia akut

2020· article· ms· W3111792256 on OpenAlexaboutno aff
Fajar Yulianto Prabowo, Sri Sutarni, Astuti Astuti

Bibliographic record

Venuenot available
Typearticle
Languagems
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineMontreal Cognitive AssessmentCognitive impairmentStroke (engine)Ischemic strokeObservational studyAcute strokeIncidence (geometry)CardiologyIschemiaDisease

Abstract

fetched live from OpenAlex

The incidence of acute cognitive impairment in stroke patients occurred in about 80% of patients and 38-73% of them became impaired permanently. Increased of inflammatory markers as a response to stroke inflamation are associated with poor outcomes in stroke patients. HsCRP level is one of the vascular cognitive impairment predictor in ischemic stroke patients. This study aims to determine the correlation of hsCRP levels in determining the occurrence of cognitive function disorder in patients with acute ischemic stroke at RSUP Sardjito Yogyakarta. The design was prospective cohort observational study with the subject of the first acute ischemic stroke patients. Cognitive impairment was assessed using the Montreal Cognitive Assessment ve rsi Indonesia ( MoCA - Ina ) score at discharge. The hsCRP level was examined at <72h onset. All data was processed with computerized statistical analysis. A total of 30 subjects followed the study with mean age 61.93±11.916 years and hsCRP levels of 3.35±2.23 g/dL. The result of bivariate analysis showed that one factor significantly influence cognitive impairment of ischemic stroke patients, that is hsCRP levels (r = -0.538, p = 0.002). Multivariate analysis showed that hsCRP levels (β = -0.5, p = 0.003) were independent factors affecting cognitive impairment of acute ischemic stroke. Based on this study, there is a correlation between hsCRP levels with acute ischemic stroke cognitive impairment, that is, the higher hsCRP levels, the lower MoCA - Ina values. ABSTRAK Kejadian gangguan kognitif secara akut pada penderita stroke terjadi pada sekitar 80% pasien dan 38-73% di antaranya menjadi menetap. Peningkatan penanda inflamasi sebagai respons inflamasi stroke berhubungan terhadap luaran yang buruk pada pasien stroke. Kadar hsCRP merupakan salah satu yang dapat dijadikan prediktor gangguan kognitif vaskular pada pasien stroke infark. Penelitian ini bertujuan untuk mengetahui korelasi kadar hsCRP dalam menentukan terjadinya gangguan fungsi kognitif pada pasien stroke iskemia akut di RSUP Dr. Sardjito Yogyakarta. Rancangan penelitian ini adalah observasional kohort prospektif dengan subjek pasien serangan stroke iskemia akut pertama. Gangguan kognitif dinilai menggunakan skor Montreal Cognitive Assessment ve rsi Indonesia ( MoCA - Ina ) . Kadar hsCRP diperiksa pada <72 jam sejak serangan stroke. Seluruh data kemudian diolah untuk analisis statistik secara komputerisasi. Sebanyak 30 subjek mengikuti penelitian dengan rerata usia 61,93±11,916 tahun dan kadar hsCRP 3,35±2,23 g/dL. Pada h asil analisis bivariat didapatkan 1 faktor bermakna secara signifikan memengaruhi gangguan kognitif pasien stroke iskemia yaitu kadar hsCRP (r = -0,538, p = 0,002). Setelah dilakukan analisis multivariat didapatkan bahwa kadar hsCRP (β = -0,5, p = 0,003) merupakan faktor independen yang mempengaruhi gangguan kognitif stroke iskemia akut. Berdasarkan penelitian ini, terdapat korelasi kadar hsCRP dengan ganguan kognitif stroke iskemia akut yaitu makin tinggi kadar hsCRP , makin rendah nilai MoCA - Ina

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)0.001
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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