Evidence map›Paper›PMID 38605748›Full record

ArticleJournal of family medicine and primary care2024

Predictors for multidrug-resistant organisms (MDROs) carriage in haemodialysis patients.

Pavuluri Sai Swetha, Kavita Gupta, Swarnatrisha Saha, Sandip K Panda, Bijayini Behera

Open access · goldAbstract read
In one paragraph

Article in Journal of family medicine and primary care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 1 institution in 1 country.

Pavuluri Sai SwethaDepartment of Microbiology and Nephrology, Bhubaneswar, Odisha, India.
Kavita GuptaDepartment of Microbiology, AIIMS, Bhubaneswar, Odisha, India.
Swarnatrisha SahaDepartment of Microbiology, AIIMS, Bhubaneswar, Odisha, India.
Sandip K PandaDepartment of Nephrology, AIIMS, Bhubaneswar, Odisha, India.
Bijayini BeheraDepartment of Microbiology, AIIMS, Bhubaneswar, Odisha, India.
All India Institute of Medical Sciences Bhubaneswar · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Infections in haemodialysis (HD) patients are an important cause of morbidity, hospitalization, and mortality. Patients undergoing HD are more prone to develop bacterial infections by multidrug-resistant organisms (MDROs). Objectives: This study is aimed to detect MDROs colonization in HD patients and its associated risk factors and outcome. Methodology: A total of 62 nasal swabs and 124 rectal swabs were collected from 62 patients coming to the haemodialysis unit from of March to May 2021 and were further screened for MRSA, VRE and CRE. Results: Out of 62 patients, 22.59% showed the presence of methicillin-resistant staphylococcus aureus (MRSA) while VRE was present in four patients (4/62). CRE was found as 24.2% (15/62). Duration of dialysis was found as a significant risk factor-associated MRSA carriage, Whereas Charlson index and drug and medication were found as significant risk factor for VRE carriage. Discussion & Conclusion: HD patients are particularly vulnerable to life threatening infections. Therefore, continuous epidemiological surveillance for these MDROs, including genotypic analysis and implementation of adequate decolonization strategies, is crucial and will reduce the possibility of autoinfection as well as disrupt transmission of multi-resistant isolates to others.

Indexed as

HaemodialysisMDROrisk factor

Identifiers

PMID38605748
PMCPMC11006063
OpenAlexW4392475350

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.