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Record W2130221554

Reduction of the door-to-needle time for administration of antibiotics in patients with a severe infection: a tailored intervention project.

2010· article· en· W2130221554 on OpenAlexaff
Charlotte F.J. Van Tuijn, Jan S. K. Luitse, Marc van der Valk, Sanne van Wissen, Maria Prins, R.W. Rosmulder, Suzanne E. Geerlings

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicinePsychological interventionEmergency departmentAntibioticsEmergency medicineAttendanceDipstickUrinePediatricsSurgeryInternal medicineNursing
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Door-to-needle time (DNT), defined as the time between arrival at the emergency department (ED) and intravenous (iv) antibiotic administration is of crucial importance in the treatment of patients suffering from serious infections. The aim of this project was to reduce the DNT for patients with a serious infection as primary outcome parameter. METHODS: All adult patients arriving at the ED with a suspected infection for whom admission and iv antibiotics were indicated were included. RESULTS: Firstly, baseline DNT was measured and potential delaying factors were identified. Subsequently, five tailored interventions were implemented at regular intervals and their effects on the DNT were analysed. The interventions were: 1) additional resident attendance during peak hours, 2) immediate examination by residents prior to laboratory results, 3) chest X-ray at the ED instead of the external radiology department, 4) iv antibiotic administration at the ED instead of the ward and finally, 5) primary dipstick urine analysis at the ED. A total of 295 patients were included (53.9% men), median age was 59 years (IQR 46 to 73). Median baseline DNT was 183 min (IQR 122 to 296). Implementation of the first three interventions did not reduce the DNT ; however, after implementation of the fourth (administer all antibiotics at the ED) and finally all five interventions the DNT was reduced by 15.3% (p=0.040) to a final median DNT of 155 min (IQR 95 to 221). CONCLUSION: Identification of delaying factors and implementation of tailored interventions reduces the DNT .

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)0.000
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 score0.071
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

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