Evidence map›Paper›PMID 39281731›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Predictors of white matter hyperintensities in the elderly Congolese population.

Emile Omba Yohe, Alvaro Alonso, Daniel L Drane, Saranya Sundaram Patel, Megan Schwinne, Emmanuel Epenge, Guy Gikelekele, Esambo Herve, Immaculee Kavugho, Nathan Tshengele and 7 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Emile Omba YoheEmory University, Department of Epidemiology, Rollins School of Public Health, Atlanta, GA, 30322, USA.
Alvaro AlonsoEmory University, Department of Epidemiology, Rollins School of Public Health, Atlanta, GA, 30322, USA.ORCID 0000-0002-2225-8323
Daniel L DraneEmory University School of Medicine, Departments of Neurology and Pediatrics, Atlanta, Georgia 30322, USA.
Saranya Sundaram PatelEmory University School of Medicine, Department of Rehabilitation Medicine, Atlanta, Georgia, 30322, USA.ORCID 0000-0003-1070-6421
Megan SchwinneEmory University, Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Atlanta, GA, USA.
Emmanuel EpengeUniversity of Kinshasa, Department of Neurology, Kinshasa, B.P. 7463 Kinshasa I, Democratic Republic of Congo.
Guy GikelekeleUniversity of Kinshasa and Catholic University of Congo, School of Medicine, Kinshasa, Department of Psychiatry, B.P. 7463 Kinshasa I, Democratic Republic of Congo.
Esambo HerveUniversity of Kinshasa, Department of Neurology, Kinshasa, B.P. 7463 Kinshasa I, Democratic Republic of Congo.
Immaculee KavughoMemory clinic of Kinshasa, Kinshasa, B.P. 7463 Kinshasa I, Democratic Republic of Congo.
Nathan TshengeleUniversity of Kinshasa and Catholic University of Congo, School of Medicine, Kinshasa, Department of Psychiatry, B.P. 7463 Kinshasa I, Democratic Republic of Congo.
Samuel MampunzaUniversity of Kinshasa and Catholic University of Congo, School of Medicine, Kinshasa, Department of Psychiatry, B.P. 7463 Kinshasa I, Democratic Republic of Congo.
Lelo ManangaUniversity of Kinshasa, Department of Neurology, Kinshasa, B.P. 7463 Kinshasa I, Democratic Republic of Congo.
Liping ZhaoEmory University, Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Atlanta, GA, USA.
Deqiang QiuEmory University, School of Medicine, Department of Radiology and Imaging Sciences & Department of Biomedical Engineering, Atlanta, GA, USA.
Anthony StringerEmory University School of Medicine, Department of Rehabilitation Medicine, Atlanta, Georgia, 30322, USA.
Amit M SaindaneEmory University School of Medicine, Departments of Radiology and Imaging Sciences and Neurosurgery, Atlanta, GA, USA.
Jean IkangaEmory University School of Medicine, Department of Rehabilitation Medicine, Atlanta, Georgia, 30322, USA.

Funding

Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1M
The Goizueta Alzheimer's Disease Research CenterP30AG066511 · NIA · EMORY UNIVERSITY · PI Deqiang Qiu · 2020 to 2026
$29.0M
Dissecting the Cognitive Roles of Hippocampus, Other Temporal Lobe StructuresR01NS088748 · NINDS · EMORY UNIVERSITY · PI DRANE, DANIEL L · 2014 to 2024
$6.4M
Mentoring in patient-oriented atrial fibrillation and cardiovascular researchK24HL148521 · NHLBI · EMORY UNIVERSITY · PI ALONSO, ALVARO · 2019 to 2023
$593k
NCATS NIH HHS UL1 TR002378NHLBI NIH HHS K24 HL148521NIA NIH HHS P30 AG066511NINDS NIH HHS R01 NS088748
6 · The paper itself

Abstract

Background: White matter hyperintensities (WMHs) are strongly linked to cardiovascular risk factors and other health conditions such as Alzheimer's disease. However, there is a dearth of research on this topic in low-income countries and underserved populations, especially in the Democratic Republic of Congo (DRC) where the population is aging rapidly with increasing cardiovascular risk factors and dementia-related diseases. This study evaluates health factors associated with WMH in the elderly Sub-Saharan Africa (SSA), specifically Congolese adults. Methods: In a cross-sectional study of 77 people from the DRC, participants underwent neuroimaging to analyze WMH volume and completed clinical evaluation, laboratory-based blood exams, self-reported questionnaires, and interviews. A simple linear regression model was conducted to test the association between WMH and potential predictors (neurological status, age, sex, hypertension, diabetes, tobacco abuse, stroke, high cholesterol, cardiovascular medication, and alcohol abuse). Stepwise selection and backward elimination analyses were performed to obtain the final model. Finally, a multiple linear regression model was conducted to assess the association between WMH and variables retained in the final model (neurological status, sex, and age). Results: Of the 77 individuals, 47 (61%) had dementia, 40 (52.6%) were males, and the mean age was 73 years (± 8.0 years standard deviation). In simple linear regression models, WMH was significantly associated with dementia (expβ1=1.75, 95% CI=1.14 - 2.71, p-value=0.01) though it had a weak association with age (expβ1=1.03, 95% CI=1.00 - 1.05, p-value=0.05) and sex (male) (expβ1=0.66, 95% CI=0.43 - 1.01, p-value=0.05). In multiple linear regression models, WMH was statistically significantly associated with dementia (expβ1=1.97, 95% CI=1.31 - 2.95, p-value =0.001), male sex (expβ2=0.54, 95% CI=0.36 - 0.80, p-value=0.003), and age (expβ3=1.03, 95% CI=1.00 - 1.06, p-value=0.03). However, WMH was not significantly associated with common cardiovascular risk factors, such as high blood pressure, diabetes, tobacco use, obesity, and high cholesterol levels. Conclusion: WMH is significantly associated with neurological status, sex, and age in the Congolese population. Understanding these predictors may improve our ability to diagnose, assess, and develop preventative treatments for white matter disease in SSA/DRC populations, where neuroimaging is difficult to obtain.

Indexed as

Cardiovascular risk factorsDementiaWhite Matter DiseaseWhite Matter Hyperintensities

Identifiers

PMID39281731
PMCPMC11398449

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.