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Record W2084534643 · doi:10.1016/j.jegh.2014.08.003

Anaesthesia, surgery, obstetrics, and emergency care in Guyana

2014· article· en· W2084534643 on OpenAlexaff
H.J. Vansell, Joseph J. Schlesinger, A Harvey, John Paul Rohde, S. Persaud, Kelly McQueen

Bibliographic record

VenueJournal of Epidemiology and Global Health · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsGeorgetown Hospital
Fundersnot available
KeywordsMedicineCaesarean sectionEconomic shortageChristian ministryHealth careRegional anaesthesiaMedical emergencyEmergency medicinePregnancySurgeryGovernment (linguistics)

Abstract

fetched live from OpenAlex

The surgical and anaesthesia needs of low-income countries are mostly unknown due to the lack of data on surgical infrastructure and human resources. The goal of this study is to assess the surgical and anaesthesia capacity in Guyana. A survey tool adapted from the WHO Tool for Situational Analysis to Assess Emergency and Essential Surgical Care was used to survey nine regional and district hospitals within the Ministry of Health system in Guyana. In nine hospitals across Guyana, there were an average of 0.7 obstetricians/gynaecologists, 3.5 non-OB surgeons, and 1 anaesthesiologist per hospital. District and regional hospitals performed an annual total of 1520 and 10,340 surgical cases, respectively. All but 2 district hospitals reported the ability to perform surgery. An average hospital has two operating rooms; 6 out of 9 hospitals reported routine medication shortages, and 4 out of 9 hospitals reported routine water or electricity shortages. Amongst the three regional hospitals, 16.1% of pregnancies resulted in Caesarean section. Surgical capacity varies by hospital type, with district hospitals having the least surgical capacity and surgical volume. District level hospitals routinely do not perform surgery due to lack of basic infrastructure and human resources.

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)0.006
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.010
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 head0.040
GPT teacher head0.381
Teacher spread0.341 · 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 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

Citations14
Published2014
Admission routes1
Has abstractyes

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