Evidence map›Paper›PMID 39070949›Full record

ArticleClinical pathology (Thousand Oaks, Ventura County, Calif.)

Safeguarding Accuracy: The Impact of Interventions on Reducing Blood Culture Contamination.

Fareeha Adnan, Nazia Khursheed, Moiz Ahmed Khan, Nazia Parveen

Abstract read
In one paragraph

Article in Clinical pathology (Thousand Oaks, Ventura County, Calif.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Fareeha AdnanConsultant, Microbiology Department, Indus Hospital & Health Network, Karachi, Pakistan.
Nazia KhursheedConsultant, Microbiology Department, Indus Hospital & Health Network, Karachi, Pakistan.
Moiz Ahmed KhanConsultant, Microbiology Department, Indus Hospital & Health Network, Karachi, Pakistan.ORCID https://orcid.org/0009-0004-2726-277X
Nazia ParveenSenior Technologist, Microbiology Department, Indus Hospital & Health Network, Karachi, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Blood culture is the gold standard for diagnosing bacteremia and direct the physicians to select appropriate antimicrobials. In hospitals, blood culture contamination (BCC) is a common problem that has a detrimental effect on patient outcomes. Hence, we implemented strategies in our tertiary care setup, for training phlebotomists and nurses in proper blood sampling techniques, and assessed their effectiveness in reducing BCC rates. Methods: This interventional study was conducted at the Indus Hospital, Karachi, Pakistan from 1 Results: A total of 86 774 Blood cultures were received from all departments of the hospital, out of which n = 30 672 were received in the pre-intervention period whereas, n = 56 102 were received in the intervention period. Mean BCC rate in the pre-intervention period was found to be 4.6%. However, after the implementation of different measures to reduce BCC, the contamination rate decreased to a mean of 3.1% by the end of the intervention period. Emergency department accounted for the highest proportion of BCC in the pre-intervention and intervention periods. Conclusion: We decreased BCC in our tertiary care setup by implementing a simple and inexpensive collaborative intervention, and came to the conclusion that the higher incidence of BCC was probably caused by factors unique to the emergency department and provided measures to successfully address them.

Indexed as

Blood culturecontaminationinterventionquality improvement

Identifiers

PMID39070949
PMCPMC11282538

What OpenQuestion holds

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LicenceCC BY-NC
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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.