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Record W4411683104 · doi:10.1177/21501351251345805

Historical, Cultural, and Structural Barriers for Cardiac Surgery in Sub-Saharan Africa: Lessons Learned From Angola

2025· review· en· W4411683104 on OpenAlexaff
Valdano Manuel, Dominique Vervoort, Frank Edwin, Jeffrey P. Jacobs

Bibliographic record

VenueWorld Journal for Pediatric and Congenital Heart Surgery · 2025
Typereview
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineSubspecialtySpecialtyAutonomyHealth careContext (archaeology)ScarcityAccreditationPublic relationsEconomic growthPolitical scienceMedical educationGeographyFamily medicine

Abstract

fetched live from OpenAlex

Cardiac surgery (CS) in sub-Saharan Africa (SSA) faces unique challenges that go beyond resource scarcity. Historical, cultural, and structural barriers continue to hinder the development of the specialty in SSA, impacting professional accreditation and the organization of healthcare systems. The colonial legacy of the subcontinent has shaped health systems in ways that often sustain external dependency, limiting local autonomy, which is particularly true for a high-resource subspecialty such as CS. Additionally, cultural resistance, the undervaluation of the specialty, and a lack of institutional recognition create a difficult environment for African cardiac surgeons. Based on the recent experience in Angola, this article explores these challenges and highlights the need for context-specific solutions, including strengthening local training, improving hospital governance, and prioritizing CS as a public health necessity. Understanding these obstacles and their potential solutions is crucial to fostering sustainable progress and ensuring equitable access to cardiovascular care in the region and in similar environments.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.492
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.094
GPT teacher head0.356
Teacher spread0.262 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2025
Admission routes1
Has abstractyes

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