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Record W3082143828 · doi:10.32734/scripta.v2i1.3373

Hubungan Stroke Iskemik dengan Gangguan Fungsi Kognitif di RS Universitas Sumatera Utara

2020· article· en· W3082143828 on OpenAlexaboutno aff
Salsa Shafira Ramadhani, Haflin Soraya Hutagalung

Bibliographic record

VenueSCRIPTA SCORE Scientific Medical Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitive impairmentMedicineStroke (engine)CognitionPhysical therapyGerontologyPsychiatry

Abstract

fetched live from OpenAlex

Background: Stroke is a major health problem worldwide, especially in Asia, which has more than 60% of the world’s population. Besides causing a health problem, stroke is also an economic and social burden in low and middle-income countries. Stroke may cause cognitive impairment, thus cognitive assessment in stroke survivors is important in addition to determine the treatment aimed at improving cognitive function following a stroke. Objectives: This study aims to determine the association between gender, age, and duration of education and cognitive impairment of post-stroke patients at Rumah Sakit Universitas Sumatera Utara. Methods: This study is an analytical research study using a cross-sectional design with a total of 24 respondents selected by consecutive sampling. Data collection was done by using medical records and interviewing the MoCA-Ina questionnaire to respondents. Results: On the analysis of chi-square obtained, gender value p = 0.673 indicating there is no association between gender and cognitive impairment, age (p = 0.035) and duration of education (p = 0.013) indicating there is an association between age as well as the duration of education and cognitive impairment of post-ischemic stroke patients. Conclusion: There is an association between age as well as the duration of education and cognitive impairment, whereas gender does not show association with cognitive impairment in post-ischemic stroke patients. Keywords: cognitive function, ischemic stroke, MoCA-Ina, post ischemic stroke Latar Belakang: Stroke merupakan masalah kesehatan utama di dunia terutama di Benua Asia dengan penduduk lebih dari 60% populasi dunia. Selain menimbulkan masalah kesehatan stroke juga menjadi beban ekonomi dan sosial di negara yang berpendapatan rendah dan menengah. Stroke dapat menyebabkan gangguan fungsi kognitif sehingga pemeriksaan fungsi kognitif pada pasien stroke merupakan hal yang penting untuk dapat menentukan penanganan selanjutnya yang bertujuan memperbaiki fungsi kognitif. Tujuan: Penelitian ini bertujuan untuk menganalisis hubungan jenis kelamin, usia dan lama pendidikan dengan gangguan fungsi kognitif pada pasien pasca stroke iskemik di Rumah Sakit Universitas Sumatera Utara. Metode: Penelitian ini merupakan penelitian analitik menggunakan desain penelitian potong lintang dengan sampel penelitian pasien pasca stroke iskemik di poliklinik saraf di Rumah Sakit Universitas Sumatera Utara dipilih dengan metode consecutive sampling sebanyak 24 responden. Pengambilan data dilakukan dengan menggunakan rekam medik serta wawancara menggunakan kuisioner MoCA-Ina kepada responden. Hasil: Pada analisis uji chi square didapatkan jenis kelamin (p = 0,673) tidak berhubungan dengan gangguan fungsi kognitif pada pasien pasca stroke, sedangkan usia (p = 0,035) dan lama pendidikan (p = 0,013) menunjukkan hubungan dengan gangguan fungsi kognitif pada pasien pasca stroke iskemik. Kesimpulan: Terdapat hubungan antara usia dan lama pendidikan dengan gangguan fungsi kognitif, sedangkan jenis kelamin tidak menunjukkan adanya hubungan dengan gangguan fungsi kognitif pada pasien pasca stroke iskemik. Kata kunci: fungsi kognitif, MoCA-Ina, pasca stroke iskemik, stroke iskemik

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)0.000
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 score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.052
GPT teacher head0.285
Teacher spread0.233 · 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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Citations5
Published2020
Admission routes1
Has abstractyes

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