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P5.041 TB Treatment For HIV Positive Pregnant Women: Challenges to Screening and Diagnosis

2013· article· en· W2038956740 on OpenAlexaff
Elsabé du Plessis, Souradet Y. Shaw, Mary Gichuhi, Joshua Kimani, Lawrence Gelmon, Lisa Avery

Bibliographic record

VenueSexually Transmitted Infections · 2013
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineNevirapineLogistic regressionMarital statusPregnancySocioeconomic statusPediatricsHuman immunodeficiency virus (HIV)ObstetricsFamily medicineDemographyPopulationEnvironmental healthAntiretroviral therapyInternal medicineViral load

Abstract

fetched live from OpenAlex

<h3>Background</h3> According to Kenya’s PMTCT guidelines, all HIV positive women who present for antenatal care should be tested for TB. <h3>Methods</h3> HIV-positive, pregnant women were recruited from two maternity hospitals in Nairobi, Kenya. The results presented here are based on surveys completed at baseline as well as 48 hour follow up. This data was collected from 505 women as part of a study on the use of mobile technology in PMTCT programmes. Questionnaires included questions on socio-economic characteristics, history of current and previous pregnancies, knowledge of PMTCT, TB screening and treatment and the use of Nevirapine. Chi-square tests and multivariable logistic regression were used to assess statistically significant associations between variables of interest and TB screening. <h3>Results</h3> Overall screening for TB in our sample was 10.3% with no significant difference between the two hospitals (11.4% versus 8.4%). Analysis also revealed no significant difference between groups based on sociodemographic status (including age, education, marital status and income) or based on the number of antenatal visits or gestational age at first presentation. <h3>Conclusion</h3> Reportedly, 80% of TB patients are given access to HIV testing and a further 27% of those who test pest positive are placed on ART. TB screening for pregnant women seem to be offered less regularly, however, with only 10% of women screened. In our sample, the lack of significant difference in screening between facility, by sociodemographic characteristics or by when they access services seems to suggest suboptimal TB screening in pregnant women is a systemic issue.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.032
GPT teacher head0.317
Teacher spread0.285 · 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 designOther design
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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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