MétaCan
Menu
Back to cohort
Record W2905734040 · doi:10.55919/jk.v9i5.8

GAMBARAN IBU BERSALIN YANG MENGALAMI PRE-EKLAMPSIA BERAT

2021· article· id· W2905734040 on OpenAlexaff
Ria Muji Rahayu, Admin Admin

Bibliographic record

VenueJurnal Kesehatan · 2021
Typearticle
Languageid
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Penyebab langsung kematian ibu adalah perdarahan (30%), eklamsi (25%), partus lama (5%), komplikasi abortus (8%), dan infeksi (12%). Preeklampsi berat adalah suatu komplikasi kehamilanyang ditandai dengan timbulnya hipertensi 160/110 mmHg atau lebih disertai proteinuria pada umurkehamilan 20 minggu atau lebih. Tujuan dari penelitian ini adalah untuk mengetahui gambaran ibubersalin yang mengalami preeklamsi berat di RSUD dr. H. Abdul Moeloek Bandar Lampung tahun2020. Jenis penelitian ini adalah Deskriftif, subjek penelitin yaitu seluruh ibu berrsalin yangmengalami preeklamsi berat, sedangkan objek penelitiannya adalah gambaran ibu bersalin yangmengalami preeklampsia berat. Populasidalam penelitian ini yaitu 258 orang dan seluruh jumlahpopulasi dijadikan sampel penelitian. Alat pengumpulan data dalam penelitian ini berupa formatpengumpulan data, analisis data penelitian ini adalah analisis univariat dengan distribusi frekuensi. Hasil penelitian menunjukkan bahwa ibu bersalin yang mengalami PEB di RSUD AbdoelMoeloek Tahun 2015 mayoritas adalah ibu yang berusia 20-35 tahun 155 ibu (60,1%), paritasmultipara sebanyak 150 ibu (58,1%),ibu yang mempunyai riwayat preeklamsi sebanyak 188 ibu(72,9%), ibu yang tidak mengalami distensi rahim 206 ibu (79,8%). Kesimpulan ibu bersalin yang mengalami preeklamsia berat di RSUD Dr. H Abdoel MoeloekBandar Lampung tahun 2020 mayoritas adalah ibu yang berusia 20-35, paritas multipara, ibu yangmempunyai riwayat preeklamsi, dan ibu yang tidak mengalami distensi rahim. Disarankan kepada ibuhamil untuk rutin memeriksakan kehamilannya setiap bulan sesuai jadwal dan memeriksakan tekanandarahnya agar mendapat pengobatan dan mendeteksi komplikasi sedini mungkin.

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)0.002
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.007

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 head0.020
GPT teacher head0.314
Teacher spread0.294 · 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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJurnal KesehatanSame topicPublic Health and NutritionFrench-language works237,207