Evidence map›Paper›PMID 40046152›Full record

ArticleThe Brown journal of hospital medicine2023

Automatic Implantable Cardioverter Defibrillator Lead-related Endocarditis due to Staphylococcus lugdunensis.

Geethika Thota, Betsy Joseph, Monarch Shah, Henry Redel, Karthik R Yeruva, Keval Patel

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Article in The Brown journal of hospital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing 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

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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.

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

6 authors.

Geethika ThotaDepartment of Internal Medicine Saint Peter's University Hospital, New Brunswick, NJ, USA.ORCID https://orcid.org/0000-0003-0438-8498
Betsy JosephDepartment of Internal Medicine Saint Peter's University Hospital, New Brunswick, NJ, USA.
Monarch ShahDepartment of Internal Medicine Saint Peter's University Hospital, New Brunswick, NJ, USA.
Henry RedelDepartment of Internal Medicine, Division of Infectious Disease Saint Peter's University Hospital, New Brunswick, NJ, USA.
Karthik R YeruvaDepartment of Internal Medicine Merit Health River Region Hospital, Vicksburg, MS, USA.
Keval PatelDepartment of Internal Medicine, Division of Cardiology Saint Peter's University Hospital, New Brunswick, NJ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Staphylococcus lugdunensis is a coagulase-negative staphylococcus (CoNS) that constitutes normal skin flora and is often read as a contaminant when isolated in blood cultures. In recent years S. lugdunensis has been increasingly recognized as a true pathogen causing a spectrum of infections from benign skin and soft tissue infections to bacteremia, bone and joint infections, and endocarditis. A significant role in the pathogenesis of infections is played by the ability of the organism to form biofilms that allow it to attach itself to foreign objects such as pacemakers, prosthetic valves, and orthopedic implants. The mortality rate in infective endocarditis caused by S. lugdunensis has been as high as 38.8 % making it as virulent as Staphylococcus aureus reported in the literature. It requires aggressive antibiotics and optimal source control, including surgical debridement and valve replacement if indicated. We present a case of S.lugdunensis infective endocarditis in a patient with an automatic implantable cardioverter defibrillator (AICD). The patient presented with lower back pain for three weeks and was found to have a right psoas abscess and S.lugdunensis bacteremia, with a vegetation on the right ventricular defibrillator wire requiring device explantation and prolonged antibiotic treatment.

Indexed as

AICDautomatic implanted cardioverter defibrillatorbacteremiabiofilmcoagulase negative Staphylococciimplantinfective endocarditispacemakerprosthetic valveStaphylococcus lugdunensis

Identifiers

PMID40046152
PMCPMC11878827

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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.