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Record W4220735121 · doi:10.1371/journal.pone.0264843

Effects of undernutrition on opportunistic infections among adults living with HIV on ART in Northwest Ethiopia: Using inverse-probability weighting

2022· article· en· W4220735121 on OpenAlexaff
Animut Alebel, Daniel Demant, Pammla Petrucka, David Sibbritt

Bibliographic record

VenuePLoS ONE · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineMalnutritionChecklistPopulationDemographyInverse probability weightingConfidence intervalCohortCohort studyGerontologyPediatricsEnvironmental healthInternal medicinePropensity score matchingPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Opportunistic infections (OIs) are the leading causes of hospitalization, morbidity, and mortality (accounting for 94.1% of all deaths) in people living with human immunodeficiency virus (PLHIV). Despite evidence suggested that undernutrition significantly increases the risk of OIs in PLHIV, to our knowledge, no study has examined the actual effects of undernutrition on OIs in this population, particularly in low-income countries. Thus, this study examined the effects of undernutrition on OIs in adults living with HIV receiving antiretroviral therapy (ART). METHODS: We conducted a retrospective cohort study among 841adults living with HIV receiving ART between June 2014 and June 2020 at Debre Markos Comprehensive Specialized Hospital, Northwest Ethiopia. Study participants were selected using a simple random sampling technique. Data from participants' medical records were extracted using a project-specific data extraction checklist. The Kaplan Meier survival curve estimated the OIs free survival time. The effects of undernutrition on time to develop OIs was estimated using inverse-probability weighting. Finally, regression coefficients with 95% confidence intervals (95% CIs) were reported, with a statistical significance of p < 0.05. RESULTS: Of 841 study participants, 262 (31.2%) developed OIs, and the overall incidence rate was 16.7 (95% CI: 14.8, 18.8) per 100 person-years. The incWidence of OIs in undernourished participants (21/100 person-years, 95% CI: 17.8, 27.4) was higher than well-nourished participants (15.0/100 person-years, 95% CI: 12.9, 17.4). When everyone in the population of interest is well-nourished, average time to develop OIs is estimated as 26.5 (coefficient: 26.5, 95% CI: 20.6, 32.4, p < 0.001) months. When everyone in the population of interest is undernourished, average time to develop OIs is estimated as 17.7 (95% CI: 12.8, 22.6) months. However, when everyone is undernourished, average time to develop OIs decreases by 8.8 (coefficient: -8.8, 95% CI: -16.6, -1.0, p = 0.026) months. Lastly, exposure to undernourishment (intervention) (ratio of average treatment effects to well-nourished potential outcome means in this study was a 32.5% reduction in OIs among adults living with HIV on ART. CONCLUSION: We found that undernutrition significantly shortened time to develop OIs in adults living with HIV. This implies that the occurrence of OIs in this vulnerable population can be improved through different cost-effective nutritional interventions, such as routine nutritional assessments and education.

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)0.019
metaresearch head score (Gemma)0.055
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 score0.019
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.055
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.260
Teacher spread0.218 · 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

Citations21
Published2022
Admission routes1
Has abstractyes

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