MétaCan
Menu
Back to cohort
Record W4403323298 · doi:10.1017/ash.2024.336

Case validation of bloodstream infections with an antibiotic-resistant organism

2024· article· en· W4403323298 on OpenAlexaffabout
Jennifer Ellison, Blanda Chow, Andrea Howatt, Logan Armstrong, Ted Pfister, Zhe Lü, Kathryn Bush

Bibliographic record

VenueAntimicrobial Stewardship & Healthcare Epidemiology · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsOrganismBloodstream infectionAntibioticsMicrobiologyAntibiotic resistanceMedicineIntensive care medicineBiologyGenetics

Abstract

fetched live from OpenAlex

Background: Bloodstream infections (BSIs) are an important cause of morbidity and mortality in severely ill patients, contributing to increased length of hospital stay and higher cost of care. Alberta Health Services Infection Prevention and Control (IPC) conducts inpatient surveillance of new episodes of BSIs with methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE) or carbapenemase-producing organisms (CPO) in 112 acute care facilities. A case-finding process was undertaken to verify the accuracy of BSI data entry. Methods: All positive MRSA, VRE or CPO blood cultures in 2021 were linked to the Inpatient Discharge Abstract Database (DAD) and the National Ambulatory Care Reporting System (NACRS) to identify new cases during acute care admissions. The results were then compared to surveillance records captured by infection control professionals (ICPs). Cases with unmatched culture date and/or encounter date and cases not identified by ICPs were screened by the study team with final decision made by ICPs. Results were analyzed by ARO and by % increase in number of surveillance records. Results: The laboratory linkage identified 286 new cases. Comparing to surveillance records (n = 248) captured by ICPs, 137 (57.3%) had matching collection dates and encounter dates, 85 (35.6%) had close matches on collection dates and encounter dates, 17 (7.1%) records had either matching collection dates or encounter dates, and 1 (0.4%) record did not have any matches on dates. There were 46 records identified in the laboratory data that were not in the surveillance system and 8 records that were in the surveillance system but not matched to the laboratory data. After review, 22 Surveillance records had data entry errors (1 CPO BSI, 20 MRSA BSI, and 1 VRE BSI), and there were 14 BSI records found to be missing (13 MRSA BSI, 1 VRE BSI). This represents a 6% increase in MRSA BSI and a 3% increase in VRE BSI identified in 2021 and no increase in CPO BSI. Conclusions: A laboratory validation to determine if BSIs with an ARO were missed during routine IPC surveillance identified a small proportion of missed bloodstream infections. The most common reason for the miss was admission through the emergency department with multiple blood cultures collected during a single admission. These results will be shared with the Infection Control program to facilitate correct BSI capture.

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)0.006
metaresearch head score (Gemma)0.030
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.315
Teacher spread0.278 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueAntimicrobial Stewardship & Healthcare EpidemiologySame topicAntibiotic Use and ResistanceFrench-language works237,207