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Record W3202969252

PROFIL GANGGUAN KOGNITIF PADA PASIEN STROKE ISKEMIK AKUT DI UNIT STROKE RSUP DR. SARDJITO TAHUN 2016-2017

2018· article· ms· W3202969252 on OpenAlexaboutno aff
Sesilia Sekarbumi Santoso, Sp.S Ismail Setyopranoto, M.Sc Atitya Fithri Khairani

Bibliographic record

Venuenot available
Typearticle
Languagems
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGynecologyStroke (engine)Acute strokeInternal medicinePhysics
DOInot available

Abstract

fetched live from OpenAlex

Salah satu penyebab kematian terbanyak di dunia dan di Indonesia adalah stroke. Prevalensi kematian karena stroke ini semakin meningkat tiap tahunnya. Stroke menimbulkan beberapa efek yang bergantung pada lokasi kerusakan otak dan salah satunya adalah gangguan kognitif, namun sering diabaikan karena disabilitas fisik lebih nampak. Tujuan dari penelitian ini adalah untuk mengetahui gambaran umum kelainan kognitif pada penderita stroke iskemik akut dan mengetahui seberapa besar efek stroke iskemik akut terhadap kemampuan kognitif penderita. Dengan mengetahui bagaimana gambaran tersebut, diharapkan dapat membantu menentukan prognosis kognitif dari stroke iskemik akut. Penelitian dilakukan dengan cara mencari 62 pasien penderita stroke iskemik akut dengan gangguan kognitif ringan yang ada di Unit Stroke RSUP Dr. Sardjito, Yogyakarta, untuk mengisi kuesioner Montreal Cognitive Assessment (MoCA). Seluruh subjek yang telah terdiagnosis memiliki gangguan kognitif berusia 60 tahun atau ke atas, dengan rata-rata usia 69,53 tahun. Rata-rata skor MoCA yang diperoleh cukup rendah, yaitu 15,42. Sebagian besar penderita gangguan kognitif merupakan laki-laki, dan domain yang paling banyak terkena adalah visuospasial dan eksekutif yang persentase terganggunya mencapai 98,38%, terutama pada bagian modified trail making test. Selain itu, seluruh subjek menderita gangguan multidomain dan sekitar 90% mengalami gangguan pada 4 domain atau lebih. One of the most common death causes in the world and in Indonesia is stroke and the prevalence is increasing every year. Stroke can cause some effects that depens on the location of brain damage and one of them is cognitive impairment, but this often neglected because of the more visible physical disability. The purpose of this research is to know the main depiction of cognitive impairment in acute ischemic stroke and to know how much the effects of it, and hopefully this research can help predicting cognitive prognosis of acute ischemic stroke. This research was conducted by looking for 62 acute ischemic stroke patients with mild cognitive impairment in Stroke Unit of Sardjito Hospital, Yogyakarta, to follow the procedure for Montreal Cognitive Assessment (MoCA). All of the subjects must be 60 years old or above, and in this research, the average is 69,53 years. The average of MoCA score is 15,42, which is low enough. Most of the subjects with cognitive impairment are men, and the most affected domain is visuospatial and executive with 98,38 abnormal results, especially in modified trail making test. Besides, all of the subjects have multidomain impairment and around 90% of subjects have 4 or more domain impairment.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0410.010

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 head0.336
Teacher spread0.287 · 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
Published2018
Admission routes1
Has abstractyes

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