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Unusual Marine Pathogens Causing Cellulitis and Bacteremia in Hemodialysis Patients: Report of Two Cases and Review of the Literature

2003· article· en· W2091869949 on OpenAlexvenueno aff
Claudia Celic Guzmán Ruiz, Mahendra Agraharkar

Bibliographic record

VenueHemodialysis International · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsnot available
Fundersnot available
KeywordsBacteremiaCellulitisMedicineHemodialysisSeptic shockIntensive care medicineVibrio vulnificusAntibioticsSepsisMicrobiologySurgeryBiologyBacteria

Abstract

fetched live from OpenAlex

Cellulitis in immunocompetent hosts is usually caused by skin organisms and responds to oral antibiotics. In immunocompromised hosts, such as end-stage renal disease (ESRD) patients, unusual organisms with unpredictable pathogenicity can cause infections. We present two cases with isolates that are usually encountered in coastal waters. The first case describes a 71-year-old African-American ESRD patient who presented with bacteremia secondary to a wound infection after exposure to flood waters in a tropical storm. The second case describes a 70-year-old Caucasian male ESRD patient who developed septic shock after a trivial wound inflicted while on a shrimp boat. Both patients were successfully treated with appropriate antibiotics and supportive measures. The infective agents in both cases belong to the halophilic Vibrio species. The causative agent of cellulitis and bacteremia in the first hemodialysis patient was identified as Vibrio alginolyticus, a non-lactose-fermenting gram-negative bacillus that is rarely isolated from blood. The second patient presented with septic shock owing to Vibrio vulnificus, which is a lactose-fermenting bacillus known to produce severe localized or systemic illness. In both cases, the common features were ESRD-related immunocompromised state and exposure to marine environments. These two cases of life-threatening cellulitis and bacteremia are presented as examples of environmental pathogens common to a marine environment in coastal areas and the imperative need of rapid identification and prompt initiation of treatment in immunocompromised hosts.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2003
Admission routes1
Has abstractyes

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