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Record W2909197471 · doi:10.1101/524462

The reconstitution of body mass index in HIV positive subjects under antiretroviral treatment in Kinshasa

2019· preprint· en· W2909197471 on OpenAlexaff
Guyguy Kabundi Tshima, Paul Madishala Mulumba

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMalariaMalnutritionConfoundingWeight lossHuman immunodeficiency virus (HIV)MedicineAntiretroviral therapyBody mass indexAntiretroviral treatmentPediatricsImmunologyInternal medicineDemographyViral load

Abstract

fetched live from OpenAlex

Abstract Objective We aimed to evaluate BMI changes in HIV adults’ subjects in the first year of ART in malaria endemic areas. Methods We used linear regression analysis showing that the change in weight at 12 months (y) in a malaria-endemic area is related to malaria infection at admission and its different episodes as illustrated by equation: y = a + bxi + ε, where x is malaria on admission, i refers to episodes of clinical malaria infection during the year, b is the slope, a is a constant and ε are confounding factors such as tuberculosis or poor eating habits. Results We found a positive value for b (b = 0.697), and this shows that weight loss at 12 months is correlated with the diagnosis of severe malaria at admission. In other words, severe malaria eliminates the weight gained under ART. Conclusions Malaria is the leading cause of weight loss under ART. Important recommendation for future: This study suggests nutritional education based on local foods containing antioxidants to fight the oxidative stress generated by HIV and stimulated by Plasmodium falciparum during febrile episodes. Oxidative stress is blocked by NADPHase which is a metalloenzyme based on selenium. Thus, to prevent a weight loss or the occurrence of the protein-energy malnutrition among people living with HIV, it is necessary to use the nutritional education. Résumé Objectif Nous voulions évaluer les modifications de l’IMC chez les patients VIH adultes au cours de la première année du traitement antirétroviral dans une zone d’endémie palustre Matériel et Méthodes Nous avons utilisé une analyse de régression linéaire montrant que la variation de poids à 12 mois (y) dans une zone d’endémie palustre est liée à l’infection palustre à l’admission et à ses différents épisodes, comme l’illustre l’équation suivante: y = a + bxi + ε, où x est le paludisme à l’admission, i les épisodes de paludisme clinique survenus au cours de l’année, b est la pente, a est une constante et ε sont des facteurs de confusion tels que la tuberculose ou de mauvaises habitudes alimentaires.. Résultats Nous avons trouvé une valeur positive pour b (b = 0,697), ce qui montre que la perte de poids à 12 mois est en corrélation avec le diagnostic de paludisme grave à l’admission. En d’autres termes, le paludisme grave élimine le poids gagné sous traitement antirétroviral. Conclusions Le paludisme est la principale cause de perte de poids sous ARV. Recommandation importante pour l’avenir : Cette étude suggère une éducation nutritionnelle basée sur des aliments locaux contenant des anti-oxydants pour lutter contre le stress oxydatif généré par le VIH et stimulé par le Plasmodium falciparum lors des poussées fébriles. Le stress oxydatif est bloqué par la NADPHase qui est une métalloenzyme à base de sélénium. Ainsi, il est nécessaire d’utiliser l’éducation nutritionnelle pour prévenir la perte du poids sous ARV.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2019
Admission routes1
Has abstractyes

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