MétaCan
Menu
Back to cohort
Record W3189607796

Improving access, quality and safety of caesarean section services in underserved rural Tanzania: The impact of knowledge translation strategies

2021· article· en· W3189607796 on OpenAlexaff
Angelo Nyamtema, Heather Scott, Elias Kweyamba, Janet Bulemela, Allan Shayo, Godfrey Mtey, Omary Kilume, John C. LeBlanc

Bibliographic record

VenueAfrican Journal of Reproductive Health · 2021
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCaesarean sectionTanzaniaMedicineMentorshipPopulationIntervention (counseling)Family medicineNursingHealth careObstetricsPregnancyEnvironmental healthMedical educationSocioeconomicsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This research was designed to study different approaches to improve access to, and quality of caesarean section services in underserved Tanzania and translate evidence into practice. In 2016, 42 associate clinicians from five health centers were trained in teams for three months in comprehensive emergency obstetric and neonatal care and anesthesia followed by post-training supportive supervision and mentorship. From 2016-2019, 2,179 caesarean sections were performed in the intervention and 969 in the control health centers. Catchment population-based caesarean section rates increased significantly in all five intervention health centers and were more than 10% in three facilities. The risk of a woman dying from complications of caesarean section in the intervention health centers was 2.3 per 1,000 caesarean sections (95% CI 0.7 - 5.3). This educational program was adopted by the government and can be used to meet the demand for caesarean section services in other underserved areas in Africa. (Afr J Reprod Health 202 1; 25[3s]: 74-83 ).

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)0.002
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 score0.078
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.065
GPT teacher head0.386
Teacher spread0.321 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAfrican Journal of Reproductive HealthSame topicGlobal Maternal and Child HealthFrench-language works237,207