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Record W3091703337 · doi:10.1186/s12884-020-03267-2

Rate, determinants, and causes of stillbirth in Jordan: Findings from the Jordan Stillbirth and Neonatal Deaths Surveillance (JSANDS) system

2020· article· en· W3091703337 on OpenAlexfundno aff
Khulood Kayed Shattnawi, Yousef Khader, Mohammad S. Alyahya, Nihaya Al-Sheyab, Anwar Batieha

Bibliographic record

VenueBMC Pregnancy and Childbirth · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersInternational Development Research CentreUNICEF
KeywordsMedicineObstetricsPregnancyInfant mortalityReproductive medicineNeonatal deathFetusPediatricsPopulationEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Annually, 2.6 million stillbirths occur around the world, with approximately 98% occurring in low- and middle-income countries. The stillbirth rates in these countries are 10 times higher than the rates in high-income countries. METHODS: An electronic stillbirths and neonatal deaths surveillance system (JSANDS) was established in five large hospitals located in three of the largest cities in Jordan in August 2019. JSANDS was developed as a secure on-line data entry system to collect, organize, analyze, and disseminate data on stillbirths, neonatal deaths, and their contributing conditions. Data on births, stillbirths and their contributing conditions, and other demographic and clinical characteristics in the period between August 2019 - January 2020 were extracted and analyzed. RESULTS: A total of 10,328 births were registered during the reporting period. Of the total births, 102 were born dead (88 antepartum stillbirths and 14 intrapartum stillbirths), with a rate of 9.9 per 1000 total births. The main contributing fetal conditions of antepartum stillbirths were antepartum death of unspecified cause (33.7%), acute antepartum event (hypoxia) (33.7%), congenital malformations and chromosomal abnormalities (13.3%), and disorders related to the length of gestation and fetal growth (10.8%). The main contributing maternal conditions of antepartum stillbirths included complications of the placental cord and membranes (48.7%), maternal complications of pregnancy (23.1%), and maternal medical and surgical conditions (23.1%). Contributing fetal conditions of intrapartum stillbirths included congenital malformations, deformations and chromosomal abnormalities, other specified intrapartum disorders, and intrapartum death of unspecified cause (33.3% each). Contributing maternal conditions of intrapartum stillbirths included complications of the placental cord and membranes. In the multivariate analysis, small for gestational age (SGA) pregnancies were associated with a significant 3-fold increased risk of stillbirth compared to appropriate for gestational age (AGA) pregnancies. CONCLUSIONS: Although the rate of stillbirth is lower than that in other countries in the region, there is an opportunity to prevent such deaths. While the majority of stillbirths occurred during the antepartum period, care should be taken for the early identification of high-risk pregnancies, including the early detection of SGA pregnancies, and ensuring adequate antenatal obstetric interventions.

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)0.004
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.238
Teacher spread0.224 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

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