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Record W2981604275 · doi:10.1093/ofid/ofz360.1301

1437. Safety and Effectiveness of a Laboratory Intervention to Reduce Antibiotic Consumption in Patients with Asymptomatic Bacteriuria

2019· article· en· W2981604275 on OpenAlexaff
Mohammad Mozafarihashjin, Lorraine Maze Dit Mieusement, Allison McGeer, Liz McCreight, Liz Van Horne, Jannice So, Ananya Shrivastava, Nadeem Khan, Louis Wong, Jerome A. Leis

Bibliographic record

VenueOpen Forum Infectious Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsSinai Health SystemHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineAsymptomaticBacteriuriaUrinary systemAdverse effectAsymptomatic bacteriuriaEmergency medicineSepsisAntibioticsInternal medicinePediatrics

Abstract

fetched live from OpenAlex

Abstract Background Antibiotic (AB) therapy for asymptomatic bacteriuria (ASB) persists despite evidence of lack of benefit. In 2012, our hospital piloted an intervention to stop routinely reporting positive midstream urine (MSU) from inpatients since the majority of patients were asymptomatic. Following the pilot, we moved to rejecting all MSU unless a telephone request was received. We undertook the present study to establish the safety and assess the long-term impact of this change. Methods From November 2013 to April 2019, when MSU were received from surgical wards (two surgical wards added in May 2015) and medical wards (from August 2017) in our hospital, a message was posted noting that ASB should not be treated and a call to the lab was required to initiate specimen processing. Patients were interviewed, and charts were reviewed within 24h of specimen receipt and 4d later to identify urinary tract symptoms/infection (UTS/UTI) and systemic infection. Primary outcome was serious adverse events (AEs). Secondary outcomes were: rate of MSU submitted, impact on lab workload, AB use. Results 1,678 episodes with submitted MSU were included; 995/1,678 (60%) MSU cultures were not processed. Of 683 processed, 482 (71%) were negative. 1,111/1,678 (66%) patients were asymptomatic when MSU was ordered. 1,393/1,678 (83%) had negative culture (N = 482) or completed d4 follow-up (N = 911). No symptomatic UTI/sepsis/systemic infection occurred; the only AE identified were 4 patients with prolonged UTS which might have been prevented by MSU processing (4/911; 0.4% patients with AE). Rates of MSU submitted remained stable at 12 per 1,000 patient-days, P = 0.59 (Figure 1). Proportion of processed MSU decreased from 16/22, 73% in 2013 to 67/137, 49% in 2019 (Figure 2; P = 0.002). Overall, microbiology workload decreased by 5 person-days/year (fewer MSU processed, but staff needed to respond to telephone calls). 275/1,678 (16%) patients received AB for presumed UTI; 221 (80%) treated empirically, 54 (20%) in response to positive MSU. Of 69 patients with ASB whose MSU was processed and positive, 32 (46%) were prescribed antibiotics. Assuming that 21% of rejected MSU from asymptomatic patients would have been positive, AB therapy for ASB was avoided in 66 patients. Conclusion Rejecting MSU specimens does not result in harm, and reduces lab workload and AB therapy for ASB. Disclosures All authors: No reported disclosures.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.261
Teacher spread0.256 · 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 designNon-randomized trial
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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