Evidence map›Paper›PMID 32171011›Full record

SynthesisNeurosurgery2020

Neurosurgical Randomized Trials in Low- and Middle-Income Countries.

Dylan P Griswold, Ahsan A Khan, Tiffany E Chao, David J Clark, Karol Budohoski, B Indira Devi, Tej D Azad, Gerald A Grant, Rikin A Trivedi, Andres M Rubiano and 6 more

Abstract readSystematic Review
In one paragraph

Synthesis in Neurosurgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  8. The Work is Never Done.Acta medica Philippina · 2025
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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

16 authors.

Dylan P GriswoldStanford University School of Medicine, Stanford, California.
Ahsan A KhanNIHR Global Health Research Group on Neurotrauma, University of Cambridge, Cambridge, United Kingdom.
Tiffany E ChaoStanford University School of Medicine, Stanford, California.
David J ClarkNIHR Global Health Research Group on Neurotrauma, University of Cambridge, Cambridge, United Kingdom.
Karol BudohoskiNIHR Global Health Research Group on Neurotrauma, University of Cambridge, Cambridge, United Kingdom.
B Indira DeviNIHR Global Health Research Group on Neurotrauma, University of Cambridge, Cambridge, United Kingdom.
Tej D AzadStanford University School of Medicine, Stanford, California.
Gerald A GrantStanford University School of Medicine, Stanford, California.
Rikin A TrivediNIHR Global Health Research Group on Neurotrauma, University of Cambridge, Cambridge, United Kingdom.
Andres M RubianoNIHR Global Health Research Group on Neurotrauma, University of Cambridge, Cambridge, United Kingdom.
Walter D JohnsonEmergency and Essential Surgical Care Programme, World Health Organization, Geneva, Switzerland.
Kee B ParkGlobal Neurosurgery Initiative, Program in Global Surgery and Social Change, Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts.
Marike BroekmanDepartment of Neurosurgery, Leiden University Medical Center, Leiden and Haaglanden Medical Center, the Hague, the Netherlands.
Franco ServadeiDepartment of Neurosurgery, Humanitas Research Hospital, Humanitas University, Milan, Italy.
Peter J HutchinsonNIHR Global Health Research Group on Neurotrauma, University of Cambridge, Cambridge, United Kingdom.
Angelos G KoliasNIHR Global Health Research Group on Neurotrauma, University of Cambridge, Cambridge, United Kingdom.

Funding

Department of Health 16/137/105World Health Organization 001
6 · The paper itself

Abstract

backgroundThe setting of a randomized trial can determine whether its findings are generalizable and can therefore apply to different settings. The contribution of low- and middle-income countries (LMICs) to neurosurgical randomized trials has not been systematically described before.

objectiveTo perform a systematic analysis of design characteristics and methodology, funding source, and interventions studied between trials led by and/or conducted in high-income countries (HICs) vs LMICs.

methodsFrom January 2003 to July 2016, English-language trials with >5 patients assessing any one neurosurgical procedure against another procedure, nonsurgical treatment, or no treatment were retrieved from MEDLINE, Scopus, and Cochrane Library. Income classification for each country was assessed using the World Bank Atlas method.

resultsA total of 73.3% of the 397 studies that met inclusion criteria were led by HICs, whereas 26.7% were led by LMICs. Of the 106 LMIC-led studies, 71 were led by China. If China is excluded, only 8.8% were led by LMICs. HIC-led trials enrolled a median of 92 patients vs a median of 65 patients in LMIC-led trials. HIC-led trials enrolled from 7.6 sites vs 1.8 sites in LMIC-led studies. Over half of LMIC-led trials were institutionally funded (54.7%). The majority of both HIC- and LMIC-led trials evaluated spinal neurosurgery, 68% and 71.7%, respectively.

conclusionWe have established that there is a substantial disparity between HICs and LMICs in the number of published neurosurgical trials. A concerted effort to invest in research capacity building in LMICs is an essential step towards ensuring context- and resource-specific high-quality evidence is generated.

Indexed as

Neurosurgical ProceduresBibliometricsDeveloping CountriesFemaleHumansMaleRandomized Controlled Trials as TopicAccess to careGlobal healthGlobal neurosurgeryGlobal surgeryHealth disparitiesLow- and middle-income countriesNeurosurgeryNeurotraumaResearchResearch capacity strengtheningSpinal surgery

Identifiers

PMID32171011
PMCPMC7426187

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.