Evidence map›Paper›PMID 33674966›Full record

ArticleJournal of community genetics2021

Modelled epidemiological data for selected congenital disorders in South Africa.

Helen L Malherbe, Colleen Aldous, Arnold L Christianson, Matthew W Darlison, Bernadette Modell

Abstract read
In one paragraph

Article in Journal of community genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Observational
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

5 authors.

Helen L MalherbeKwaZulu Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu Natal, Durban, South Africa. helen@hmconsult.co.za.ORCID http://orcid.org/0000-0002-9566-6248
Colleen AldousCollege of Health Sciences, University of KwaZulu Natal, Durban, South Africa.
Arnold L ChristiansonWits Centre for Ethics (WiCE), University of the Witwatersrand, Johannesburg, South Africa.
Matthew W DarlisonWHO Collaborating Centre for Community Genetics, Institute of Health Informatics, University College London, London, UK.
Bernadette ModellWHO Collaborating Centre for Community Genetics, Institute of Health Informatics, University College London, London, UK.

Funding

College of Health Sciences, UKZN PhD & Post-doc bursaries 2013-2019UKZN APACHE Flagship Post-Doctoral Research Scholarship (2019 - to date)
6 · The paper itself

Abstract

Congenital disorders (CD) remain an unprioritized health care issue in South Africa with national surveillance underreporting by > 95%. This lack of empiric data contributes to an underestimation of the CD disease burden, resulting in a lack of services for those affected. Modelling offers estimated figures for policymakers to plan services until surveillance is improved. This study applied the Modell Global Database (MGDb) method to quantify the South African CD disease burden in 2012. The MGDb combines birth prevalence data from well-established registries with local demographic data to generate national baseline estimates (birth prevalence and outcomes) for specific early-onset, endogenous CDs. The MGBd was adapted with local South African demographic data to generate baseline (no care) and current care national and provincial estimates for a sub-set of early-onset endogenous CDs. Access to care/impact of interventions was quantified using the infant mortality rate as proxy. With available care in 2012, baseline birth prevalence (27.56 per 1000 live births, n = 32,190) decreased by 7% with 2130 less affected births, with 5400 (17%) less under-5 CD-related deaths and 3530 (11%) more survivors at 5 years, including 4720 (15%) effectively cured and 1190 (4%) less living with disability. Results indicate a higher proportion of CD-affected births than currently indicated by national surveillance. By offering evidence-based estimates, the MGDb may be considered a tool for policymakers until accurate empiric data becomes available. Further work is needed on key CD groups and costing of specific interventions.

Indexed as

Birth defectsCommunity geneticsCongenital anomaliesCongenital disordersInfant mortality rateModell Global DatabaseRare diseasesSouth Africa

Identifiers

PMID33674966
PMCPMC8241974

What OpenQuestion holds

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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.