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Record W2082858013 · doi:10.1371/journal.pone.0083298

Intensive Care Unit-Acquired Bacteremia in Mechanically Ventilated Patients: Clinical Features and Outcomes

2013· article· en· W2082858013 on OpenAlexaff
Hsin‐Kuo Ko, Wen-Kuang Yu, Te‐Cheng Lien, Jia-Horng Wang, Arthur S. Slutsky, Haibo Zhang, Yu Ru Kou

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersTaipei Veterans General HospitalNational Science Council
KeywordsMedicineIntensive care unitBacteremiaMechanical ventilationIntensive careHazard ratioRetrospective cohort studyInternal medicineIntensive care medicineProportional hazards modelMortality rateAPACHE IIAntibioticsConfidence intervalMicrobiology

Abstract

fetched live from OpenAlex

Intensive care unit (ICU)-acquired bacteremia (IAB) is associated with high medical expenditure and mortality. Mechanically ventilated patients represent one third of all patients admitted to ICU, but the clinical features and outcomes in mechanically ventilated patients who develop IAB remain unknown. We conducted a 3-year retrospective observational cohort study, and 1,453 patients who received mechanical ventilation on ICU admission were enrolled. Among patients enrolled, 126 patients who had developed IAB ≧48 hours after ICU admission were identified. The study patients were divided into IAB and no IAB groups, and clinical characteristics of IAB based on specific bacterial species were further analyzed. The multivariate Cox regression analysis showed that ventilator support for chronic obstructive pulmonary disease and congestive heart failure, and patients admitted from nursing home were the independent risk factors for developing IAB. Patients with IAB were significantly associated with longer length of ICU stay, prolonged ventilator use, lower rate of successful weaning, and higher rate of ventilator dependence and ICU mortality as compared to those without IAB. IAB was the independent risk factor for ICU mortality (HR, 1.510, 95% CI 1.054-1.123; p = 0.010). The clinical characteristics of IAB related to specific bacterial species included IAB due to Pseudomonas aeruginosa being likely polymicrobial, lung source and prior antibiotic use; Escherichia coli developing earlier and from urinary tract source; methicillin-resistant Staphylococcus aureus related to central venous catheter and multiple sets of positive hemoculture; and Elizabethkingia meningoseptica significantly associated with delayed/inappropriate antibiotic treatment. In summary, IAB was significantly associated with poor patient outcomes in mechanically ventilated ICU patients. The clinical features related to IAB and clinical characteristics of IAB based on specific bacterial species identified in our study may be utilized to refine the management of IAB.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.061
GPT teacher head0.323
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2013
Admission routes1
Has abstractyes

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