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Record W2507993346 · doi:10.3389/fmicb.2016.01271

Is HELICS the Right Way? Lack of Chest Radiography Limits Ventilator-Associated Pneumonia Surveillance in Wales

2016· article· en· W2507993346 on OpenAlexaff
Richard Pugh, Dean Harris, Susan K. Harris, Hywel Roberts, Gareth Scholey, Tamás Szakmány

Bibliographic record

VenueFrontiers in Microbiology · 2016
Typearticle
Languageen
FieldMedicine
TopicNosocomial Infections in ICU
Canadian institutionsInstitute of Infection and Immunity
FundersIntensive Care Society
KeywordsMedicineVentilator-associated pneumoniaPneumoniaIncidence (geometry)Intensive careIntensive care medicineMechanical ventilationEmergency medicineInfection controlIntubationPediatricsInternal medicineSurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: The reported incidence of ventilator-associated pneumonia (VAP) in Wales is low compared with surveillance data from other European regions. It is unclear whether this reflects success of the Welsh healthcare-associated infection prevention measures or limitations in the application of European VAP surveillance methods. Our primary aim was to investigate episodes of ventilator-associated respiratory tract infection (VARTI), to identify episodes that met established criteria for VAP, and to explore reasons why others did not, according to the Hospitals in Europe Link for Infection Control through Surveillance (HELICS) definitions. MATERIALS AND METHODS: During two 14-day study periods 2012-2014, investigators reviewed all invasively ventilated patients in all 14 Welsh Intensive Care Units (ICUs). Episodes were identified in which the clinical team had commenced antibiotic therapy because of suspected VARTI. Probability of pneumonia was estimated using a modified Clinical Pulmonary Infection Score (mCPIS). Episodes meeting HELICS definitions of VAP were identified, and reasons for other episodes not meeting definitions examined. In the second period, each patient was also assessed with regards to the development of a ventilator-associated event (VAE), according to recent US definitions. RESULTS: The study included 306 invasively ventilated patients; 282 were admitted to ICU for 48 h or more. 32 (11.3%) patients were commenced on antibiotics for suspected VARTI. Ten of these episodes met HELICS definitions of VAP, an incidence of 4.2 per 1000 intubation days. In 48% VARTI episodes, concurrent chest radiography was not performed, precluding the diagnosis of VAP. Mechanical ventilation (16.0 vs. 8.0 days; p = 0.01) and ICU stay (25.0 vs. 11.0 days; p = 0.01) were significantly longer in patients treated for VARTI compared to those not treated. There was no overlap between episodes of VARTI and of VAE. DISCUSSION: HELICS VAP surveillance definitions identified less than one-third of cases in which antibiotics were commenced for suspected ventilator-associated RTI. Lack of chest radiography precluded nearly 50% cases from meeting the surveillance definition of VAP, and as a consequence we are almost certainly underestimating the incidence of VAP in Wales.

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)0.008
metaresearch head score (Gemma)0.024
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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.269
Teacher spread0.251 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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