Evidence map›Paper›PMID 21595872›Full record

ArticleGlobalization and health2011

A review of health system infection control measures in developing countries: what can be learned to reduce maternal mortality.

Julia Hussein, Dileep V Mavalankar, Sheetal Sharma, Lucia D'Ambruoso

Open access · goldAbstract read
In one paragraph

Article in Globalization and health, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 7% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 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

4 authors at 3 institutions in 2 countries.

Julia HusseinUniversity of Aberdeen, Foresterhill, Aberdeen, UK. j.hussein@abdn.ac.uk.
Dileep V Mavalankar
Sheetal Sharma
Lucia D'Ambruoso
University of Aberdeen · GBBournemouth University · GBIndian Institute of Management Ahmedabad · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A functional health system is a necessary part of efforts to achieve maternal mortality reduction in developing countries. Puerperal sepsis is an infection contracted during childbirth and one of the commonest causes of maternal mortality in developing countries, despite the discovery of antibiotics over eighty years ago. Infections can be contracted during childbirth either in the community or in health facilities. Some developing countries have recently experienced increased use of health facilities for labour and delivery care and there is a possibility that this trend could lead to rising rates of puerperal sepsis. Drug and technological developments need to be combined with effective health system interventions to reduce infections, including puerperal sepsis. This article reviews health system infection control measures pertinent to labour and delivery units in developing country health facilities. Organisational improvements, training, surveillance and continuous quality improvement initiatives, used alone or in combination have been shown to decrease infection rates in some clinical settings. There is limited evidence available on effective infection control measures during labour and delivery and from low resource settings. A health systems approach is necessary to reduce maternal mortality and the occurrence of infections resulting from childbirth. Organisational and behavioural change underpins the success of infection control interventions. A global, targeted initiative could raise awareness of the need for improved infection control measures during childbirth.

Identifiers

PMID21595872
PMCPMC3113713
OpenAlexW2165327315

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.