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Record W2529196474

PERBEDAAN STATUS KOGNITIF BERDASARKAN MONTREAL COGNITIVE ASSESSMENT PADA PASIEN PASCA STROKE ISKEMIK DAN STROKE HEMORAGIK DI RSUD DR. ZAINOEL ABIDIN BANDA ACEH

2014· article· ms· W2529196474 on OpenAlexaboutno aff
Mutia Aprilia Ningsih

Bibliographic record

VenueElectronic theses and dissertations (Syiah Kuala University) · 2014
Typearticle
Languagems
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)Gynecology
DOInot available

Abstract

fetched live from OpenAlex

ABSTRAKStroke merupakan salah satu gangguan serebrovaskular yang dapat diklasifikasikan menjadi stroke iskemik dan stroke hemoragik. Stroke dapat menyebabkan komplikasi kelainan neurologis berupa gangguan motorik maupun sensorik dimana salah satunya adalah gangguan fungsi kognitif. Penelitian ini bertujuan untuk mengetahui apakah terdapat perbedaan status kognitif pada pasien pasca stroke iskemik dan stroke hemoragik. Penelitian ini merupakan penelitian analitik observasional dengan desain cross sectional. Teknik pengambilan sampel dilakukan dengan metode consecutive sampling. Status kognitif dinilai dengan menggunakan kuesioner Montreal Cognitive Assessment versi bahasa Indonesia (MoCA-INA). Tempat dilakukannya penelitian adalah di poliklinik saraf, ruang geulima I, instalasi rehabilitasi medik dan instalasi rekam medik RSUD dr. Zainoel Abidin Banda Aceh. Data dianalisis dengan menggunakan independent sample t-test dan Mann Whitney U-test. Didapatkan bahwa seluruh sampel yang berjumlah 66 orang (100%) yang terdiri dari 33 orang (50%) stroke iskemik dan 33 orang (50%) stroke hemoragik mengalami gangguan kognitif. Didapatkan tidak terdapat perbedaan yang bermakna status kognitif pada pasien pasca stroke iskemik dan stroke hemoragik (p = 0,96), baik berdasarkan lokasi lesi hemisfer dextra (p = 0,368), maupun berdasarkan lokasi lesi hemisfer sinistra (p = 0,160). Disimpulkan bahwa terdapat gangguan kognitif pada pasien pasca stroke iskemik dan stroke hemoragik namun tidak terdapat perbedaan status kognitif berdasarkan Montreal Cognitive Assessment pada pasien pasca stroke iskemik dan stroke hemoragik di RSUD dr. Zainoel Abidin Banda Aceh.Kata kunci: stroke iskemik, stroke hemoragik, Montreal Cognitive Assessment, MoCA-INA, status kognitif.ABSTRACTStroke is one of cerebrovascular disease that can be classified as ischemic stroke and hemorrhagic stroke. Stroke can cause many complication of neurology disorder like motoric and sensoric disorder, and one of it is cognitive impairment. The purpose of this study was to find out if there was the difference in cognitive status between ischemic stroke and hemorrhagic stroke. This study was and observational analitic in cross sectional design. Sampling technique was consecutive sampling methode. Cognitive status was examined by using a questionnaire of Montreal Cognitive Assessment in Indonesian version (MoCA-INA). The place of this study was in Polyclinic of Neurology, Geulima I unit, Instalation of Medical Rehabilitation, and Instalation of Medical Record RSUD dr. Zainoel Abidin Banda Aceh. Data were analyzed by using independent sample t-test and Mann Whitney U-test. Obtained that the entire of samples which amount to 66 samples (100%), in which 33 ischemic stroke (50%) and 33 hemorrhagic stroke (50%) suffered from cognitive impairment. This study also found that there was no significant difference in cognitive status of ischemic stroke and hemorrhagic stroke (p = 0,96), both in by the location of the lesion in dextra hemisphere (p = 0,368), and by the location of the lesion in sinistra hemisphere (p = 0,160). We can conclude that there was cognitive impairment both in ischemic stroke and hemorrhagic stroke however, there was no difference in cognitive status based on Montreal Cognitive Assessment of patients after ischemic stroke and hemorrhagic stroke in RSUD dr. Zainoel Abidin Banda Aceh.Keywords: ischemic stroke, hemorrhagic stroke, Montreal Cognitive Assessment, MoCA-INA, cognitive status.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.264
Teacher spread0.255 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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