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Record W1970793366 · doi:10.5539/gjhs.v4n5p140

Incidence of Birth Asphyxia as Seen in Central Hospital and GN Children’s Clinic both in Warri Niger Delta of Nigeria: An Eight Year Retrospective Review

2012· article· en· W1970793366 on OpenAlexvenueno aff
Gilbert I.M. Ugwu, Heydarali Abedi, Eunice N. Ugwu

Bibliographic record

VenueGlobal Journal of Health Science · 2012
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsnot available
Fundersnot available
KeywordsAsphyxiaMedicineIncidence (geometry)Niger deltaSoutheastern NigeriaAsphyxia NeonatorumPediatricsObstetricsNeonatal sepsisSepsisSurgeryDelta

Abstract

fetched live from OpenAlex

BACKGROUND: Birth asphyxia is one of the commonest causes of neonatal morbidity and mortality in developing countries. Together with prematurity and neonatal sepsis, they account for over 80% of neonatal deaths. AIM: To determine the incidence and mortality rate of birth asphyxia in Warri Niger Delta of Nigeria. MATERIALS AND METHOD: Recovery of case notes of all the newborn babies seen from January 2000 to December 2007 at Central Hospital Warri and GN children's Clinic, Warri, was undertaken. They were analyzed and those with birth asphyxia were further analyzed, noting the causes, severity of asphyxia, sex of the babies, management given. RESULTS: A total of 864 out of 26,000 neonates seen within this period had birth asphyxia. 525 (28/1000 live births) had mild asphyxia while 32% were severely asphyxiated. 61.5% of the asphyxiated were born at maternities, churches or delivered by traditional birth attendants or at home. Prolonged labour was the commonest cause of asphyxia and asphyxia was more in neonates from unbooked patients. CONCLUSION: The incidence of bith asphyxia in Warri is 28/1000. Majority of patients are from prolonged labour and delivery at unrecognized centres. Health education will dratically reduce the burden of asphyxia neanatorum as unsubtanciated religous beliefs have done a great havoc.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.326
Teacher spread0.315 · 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.

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

Citations38
Published2012
Admission routes1
Has abstractyes

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