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Record W4295023811 · doi:10.30574/ijsra.2022.7.1.0182

Hematological, cholesterolemic and clinical profile in exposed to outdoor air pollution linked to the incineration of biomedical waste in Benin

2022· article· en· W4295023811 on OpenAlexfundno aff
Denise Assiba DAVOU, Alban Zohoun, Hervé Agbomakou GBEGNIDE, Martin Pépin Aïna, Edgard‐Marius Ouendo

Bibliographic record

VenueInternational Journal of Science and Research Archive · 2022
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsIncinerationMedicineHematocritHemoglobinToxicologyAnimal scienceInternal medicineWaste managementBiology

Abstract

fetched live from OpenAlex

Introduction: Incineration is one of the treatment methods for biomedical waste (BMW). It is a source of toxic air pollutant emission. The study aimed to compare the haematological, cholesterolemic and clinical profile of subjects exposed to this pollution to controls. Methods: This was a comparative cross-sectional study on 154 exposed subjects selected within 500 meters of the incineration sites of solid biomedical waste and controls, among new blood donors, matched on age, sex, level of education, cooking mode. The hematological parameters and cholesterolemia were obtained by standardized procedure on automata. The proportions of subjects were compared with a chi-square test. The dispersion analysis of the biological parameters was made by the non-parametric Wilcoxon test at the 5% threshold. Results: The two groups were comparable for matching. The frequency of respiratory symptoms ranged from 20.1 - 79.2% in exposed versus 4.5 - 54.5% in controls. The frequency of neurological symptoms ranged from 26.6 - 76.6% in exposed versus 1.9 - 51.9% in controls. Hemoglobin (p=0.001), hematocrit (p=0.051) were low in the exposed and white blood cells (p=0.003) and platelets (p<0.001) high. Total cholesterol (p<0.001) was twice as high and HDL six times lower in the exposed (p<0.001). Conclusion: The exposed presented a more altered hematological and cholesterolemic profile with more frequent symptoms. It is essential to improve the management practice of BMW in our hospitals through the use of innovative, less polluting technologies

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.077
GPT teacher head0.432
Teacher spread0.355 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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