Evidence map›Paper›PMID 21152331›Full record

ArticleMcGill journal of medicine : MJM : an international forum for the advancement of medical sciences by students2009

TRAUMA IN TANZANIA: Researching Injury in a low-Resource Setting.

Baijayanta Mukhopadhyay, Respicious Boniface, Tarek Razek

Open access · diamondAbstract read
In one paragraph

Article in McGill journal of medicine : MJM : an international forum for the advancement of medical sciences by students, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 37% of its field
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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

3 authors.

Baijayanta Mukhopadhyay
Respicious Boniface
Tarek Razek

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prevalence of surgical trauma as a global public health hazard has been severely neglected. Trauma surgeons in Uganda and Canada have developed the Kampala Trauma Score (KTS), a trauma severity index specific to east African contexts. Hospitals in Tanzania have begun to use this tool to measure their own trauma management protocols in order to measure the validity of this index regionally. This study sought to enhance analysis of data collected through the KTS, by highlighting the efficacy and the lacunae of this registry through evaluation of the data quality of one ongoing round of data collection at an orthopaedic emergency room in Dar es Salaam, Tanzania. The data was screened for missing values that would have impact on prediction of clinical evolution and also analysed for contradictory evidence. Interviews were conducted with data collectors on the main challenges involved in data gathering and analysis for this project. Analysis of the initial round of data collection confirms road accidents cause the most trauma in Dar es Salaam, with pedestrians being particularly vulnerable. However, critical sources of information such as serious injury scores and two-week followup were inconsistently recorded, thereby limiting outcome measurement. The lack of research resources, both financial and human, had a major impact on the ability to sustain the data collection. While the results of this study demonstrate the public health value of having a mechanism to record trauma, research capacity must be supported in low-resource settings in order to enhance clinical care to accident and injury patients.

Indexed as

data qualityglobal healthresearch capacitySurgerytrauma

Identifiers

PMID21152331
PMCPMC2997249
OpenAlexW2272596143

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.