Evidence map›Paper›PMID 32823641›Full record

ReviewPathogens (Basel, Switzerland)2020

Microbial Contamination of Dental Unit Waterlines and Potential Risk of Infection: A Narrative Review.

Anna Maria Spagnolo, Marina Sartini, Maria Luisa Cristina

Abstract readReview
In one paragraph

Review in Pathogens (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

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

  1. Pooled it
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  12. Pathogens (Basel, Switzerland) · 2025
    Review
  13. Article
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  16. Article
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  19. Article
  20. Dental Unit Waterlines: Disinfection and Management.International dental journal · 2024
    Review
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.

Anna Maria SpagnoloDepartment of Health Sciences, University of Genova, 16132 Genova, Italy.
Marina SartiniDepartment of Health Sciences, University of Genova, 16132 Genova, Italy.ORCID 0000-0002-7127-2893
Maria Luisa CristinaDepartment of Health Sciences, University of Genova, 16132 Genova, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several studies have revealed that dental unit waterlines (DUWLs) are often contaminated by large numbers of various micro-organisms (bacteria, fungi, protozoa, viruses). Microbial contamination in DUWLs may originate from the mains water piped into the dental unit, the suck-back of patients' saliva into the line due to the lack of adequate valves, and contamination from bottled water systems. Some of the main determinants of microbial contamination in DUWLs are: a very small lumen size (0.5-2 mm) of the tubing used, high surface-to-volume ratio (6:1), low throughput and the materials of which the tubing is made, water stagnation outside of working hours. The environmental conditions present inside the conduits of the dental unit may facilitate the proliferation of micro-organisms and the consequent formation of biofilm on the interior surface of the pipes of DUWLs. During the use of handpieces, particularly high-speed rotating instruments, a spray is thrown up in the form of aerosols or spatters containing biological material (saliva, blood and dental plaque) and micro-organisms. This means that the health of both dental staff and patients could be at risk of infection. The risk of cross-infections in dental settings can be tackled by implementing combined interventions to prevent the contamination of DUWLs.

Indexed as

biofilmsdental infection controlwater microbiology

Identifiers

PMID32823641
PMCPMC7460066

What OpenQuestion holds

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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.