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Device-Related Infections: A Review

2005· review· en· W1988912096 on OpenAlexaff
Donald C. Vinh, John M. Embil

Bibliographic record

VenueJournal of Long-Term Effects of Medical Implants · 2005
Typereview
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIntensive care medicineMedicineBiofilmQuality of life (healthcare)AntibioticsImplantDehiscenceWound dehiscenceAntimicrobialSurgeryBiologyBacteriaMicrobiology

Abstract

fetched live from OpenAlex

The use of surgically implanted devices has increased as a result of their beneficial effect on quality of life, and in some circumstances, on patient survival rates. They can, however, be associated with a variety of complications, the most dreaded being infection. Device-related infections are important to understand because of the morbidity and mortality associated with them. Frequently, patients are managed with hospitalization, prolonged courses of antibiotics, and surgical interventions, all of which can negatively impact on patients' quality of life. Such care is also associated with increased costs to health care systems. Furthermore, these infections often represent a diagnostic challenge because of the lack of consensus definition of what constitutes an infection and its severity, as well as the paucity of well-designed, large studies addressing optimal methods of investigation and management. An implant-associated infection is defined as a host immune response to one or more microbial pathogens on an indwelling implant. An understanding of the pathogenesis of these infections provides a rationale for management. Development of device-related infections begins with colonization of the foreign material, followed by a complex metamorphosis by the microorganisms with resultant biofilm formation. In this surface-associated form, bacteria have altered phenotypic properties. This change, in conjunction with the physical protective layer provided by the biofilm, renders antimicrobial therapy ineffective when used alone. Because the microorganisms are able to reside on the hardware, they proliferate and cause local damage, such as loosening of implanted devices, wound dehiscence, or disruption of prosthetic valves, as well as systemic manifestations, such as fever or embolic phenomenon. The onset and clinical manifestations of device-related infections vary with the pathogen involved, as well as which component of the device is affected. The time period after device implantation that signs and symptoms develop can assist in the selection of empiric antimicrobial therapy. Optimal diagnostic microbiologic specimens are paramount in tailoring the antimicrobial therapy, which almost always has to be given for a prolonged period of time. Surgical removal of the device is usually necessary. Some studies of limited types of device-related infections, however, have defined indications for which salvage therapy may be warranted. In addition, some patients are not candidates for, or may not want, further surgical interventions, in which case indefinite suppressive antimicrobial therapy may be considered. This review provides an overview of infections related to various neurosurgical, cardiac, and orthopedic devices, as well as those related to cochlear, breast, and penile prostheses, with discussion of definitions of such infections, along with microbiology, pathogenesis, and management guidelines, including the limited indications for salvage techniques.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.428
Teacher spread0.387 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations118
Published2005
Admission routes1
Has abstractyes

Explore more

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