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Control of Hypertension in Pregnant Women in Secondary Health Facilities in Nigeria: A Cross-Sectional Study

2023· article· en· W4390540241 on OpenAlexaboutno aff
Jennifer Chukwu, Doris Atibinye Dotimi, Jennifer Ladokun, Esther Dogo, Chinedu Ogbonnia Egwu, Chidinma Chukwu, David Tersoo Audu

Bibliographic record

VenueTexila international journal of public health · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePregnancyEnvironmental healthCross-sectional studyQuarter (Canadian coin)Hypertension in PregnancyObstetricsHealth carePediatricsPreeclampsiaEconomic growth

Abstract

fetched live from OpenAlex

Hypertension is among the non-communicable diseases that complicate pregnancies in women. Diagnosis and control of this condition are important in reducing the risk of maternal and foetal mortality. This study was aimed at determining the prevalence and control of hypertension among pregnant women visiting secondary health care facilities in four Local Government Areas in Lagos (2) and Abuja (Federal Capital Territory) (2), Nigeria. Our findings showed that there was a high prevalence of hypertension in these facilities (50%). Our finding also revealed that the overall level of control was 30.45%, which decreased with time in the course of the management. The control was highest in the first quarter and lowest in the third (last) quarter. The consistent and appropriate use of antihypertensives is important to prevent the complications associated with non-communicable diseases like hypertension during pregnancy. Healthcare providers should therefore advocate early diagnosis and management of hypertension during pregnancy. Keywords: Control, Hypertension, Non-communicable diseases, Pregnancy, Secondary healthcare.

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)0.030
metaresearch head score (Gemma)0.003
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 score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.185
GPT teacher head0.472
Teacher spread0.287 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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