Evidence map›Paper›PMID 31555457›Full record

ArticleGlobal health, epidemiology and genomics2019

A model for point of care testing for non-communicable disease diagnosis in resource-limited countries.

Stuart Malcolm, Joane Cadet, Lindsay Crompton, Vincent DeGennaro

Abstract read
In one paragraph

Article in Global health, epidemiology and genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  5. Diagnostic accuracy of CardiochekLipids in health and disease · 2024
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4 · The record

Corrections and comments

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

4 authors.

Stuart MalcolmDepartment of Internal Medicine, Emory University School of Medicine, 80 Jessie Hill Jr. Dr. SE, Atlanta, GA 30303, USA.ORCID 0000-0002-3789-973X
Joane CadetDepartment of Medicine, University of Florida College of Medicine, Gainesville, USA.
Lindsay CromptonLondon School of Hygiene and Tropical Medicine, London, United Kingdom of Great Britain and Northern Ireland.
Vincent DeGennaroInnovating Health International, Port-au-Prince, Haiti.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-communicable disease diagnosis frequently relies on biochemical measurements but laboratory infrastructure in low-income settings is often insufficient and distances to clinics may be vast. We present a model for point of care (POC) epidemiology as used in our study of chronic disease in the Haiti Health Study, in rural and urban Haiti. Point of care testing (POCT) of creatinine, cholesterol, and hemoglobin A1c as well as physical measurements of weight, height, and waist circumference allowed for diagnosis of diabetes, chronic kidney disease, dyslipidemias, and obesity. Methods and troubleshooting techniques for the data collection of this study are presented. We discuss our method of community-health worker (CHW) training, community engagement, study design, and field data collection. We also discuss the machines used and our quality control across CHWs and across geographical regions. Pitfalls tended to include equipment malfunction, transportation issues, and cultural differences. May this paper provide information for those attempting to perform similar diagnostic and screening studies using POCT in resource poor settings.

Indexed as

AdultChronic DiseaseCommunity Health WorkersCost of IllnessDiabetes MellitusDyslipidemiasFemaleHaitiHumansMaleMiddle AgedNoncommunicable DiseasesObesityPoint-of-Care TestingQuality ControlRenal Insufficiency, ChronicChronic diseaseglobal healthHaitinon-communicable diseasepoint of care

Identifiers

PMID31555457
PMCPMC6749552

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.