Evidence map›Paper›PMID 38824610›Full record

ArticleBMC research notes2024

Joint clinical determinants for bivariate hematological parameter among TB/HIV co-infected adults under TB/HIV treatment in university of Gondar comprehensive specialized hospital: Retrospective panel data study.

Nurye Seid Muhie

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Article in BMC research notes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Nurye Seid MuhieDepartment of Statistics, Mekdela Amba University, Tulu Awulia, Ethiopia. nuryedessie275@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWorldwide ranking above HIV/AIDS, tuberculosis is continues to have a significant effect on public health and the leading cause of death due to high progression of HIV. The objective of current study was identify joint clinical determinants that affecting bivariate hematological parameter among TB/HIV co-infected adults under TB/HIV treatment in university of Gondar comprehensive specialized hospital.

methodThe result of these study was conducted at university of Gondar comprehensive specialized hospital, Gondar, Ethiopia by using a retrospective cohort follow up study from September 2015-march 2022 G.C. The source of data in this study was secondary data obtained from patients chart. Bayesian approach of longitudinal linear mixed effect sub model was used in panel data set to get wide range of information about TB/HIV co-infected patients.

resultOut of 148 co-infected participants more than half of the patients (56.1%) and (52.7%) accounted for CPT and INH non users, of which 10.8% and 10.3% had the outcome of mortality respectively. The random intercept and slope model were selected for repeated measure hemoglobin level and hematocrit based on deviance information criteria (DIC), and probability of direction (Pd) under the full model.

conclusionCurrent study revealed that clinical predictors red blood cell count, platelet cell count, fair and good treatment adherence, other ART regiment, IPT drug users, and viral load count < 10,000 copies/mL, were associated with high hemoglobin level concentration while, lymphocyte count, WHO clinical stage-IV,1e ART regiment, and patients with OIs results for low hemoglobin level concentration. Likewise, red blood cell count, platelet cell count, fair and good treatment adherence, IPT drug users, and viral load count < 10,000 copies/mL co-infected patients had high hematocrit, while lymphocyte count, WHO clinical stage-III,1c ART regiment, and patients with OIs significantly leads to low hematocrit. Health professionals give more attention to these important predictors to reduce progression of disease when the co-infected patients come back again in the hospital. In addition, health staff should conduct health related education for individuals to examine continuous check-up of co-infected patients.

Indexed as

CoinfectionHIV InfectionsAdultAntitubercular AgentsBayes TheoremEthiopiaFemaleHematocritHemoglobinsHospitals, SpecialHumansMaleMiddle AgedRetrospective StudiesTuberculosisYoung AdultAntitubercular AgentsHemoglobinsCommon predictorsHematocritHematological parameterHemoglobinLongitudinal sub modelTB/HIV co-infected

Identifiers

PMID38824610
PMCPMC11143627

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.