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Record W2415206148 · doi:10.3201/eid2108.140978

Hospital Resource Utilization and Patient Outcomes Associated with Respiratory Viral Testing in Hospitalized Patients

2015· article· en· W2415206148 on OpenAlexafffundabout
Sunita Mulpuru, Shawn D. Aaron, Paul E. Ronksley, Nadine Lawrence, Alan J. Forster

Bibliographic record

VenueEmerging infectious diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsOttawa HospitalUniversity of CalgaryUniversity of Ottawa
FundersOttawa Hospital Research InstituteCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsMedicineIsolation (microbiology)Odds ratioIntensive care unitIntensive care medicineEmergency medicineOddsInfection controlHealth careViral loadInternal medicineImmunologyHuman immunodeficiency virus (HIV)Logistic regressionBioinformatics

Abstract

fetched live from OpenAlex

Testing patients for respiratory viruses should guide isolation precautions and provide a rationale for antimicrobial drug therapies, but few studies have evaluated these assumptions. To determine the association between viral testing, patient outcomes, and care processes, we identified adults hospitalized with respiratory symptoms from 2004 through 2012 at a large, academic, tertiary hospital in Canada. Viral testing was performed in 11% (2,722/24,567) of hospital admissions and was not associated with reduced odds for death (odds ratio 0.90, 95% CI 0.76-1.10) or longer length of stay (+1 day for those tested). Viral testing resulted in more resource utilization, including intensive care unit admission, but positive test results were not associated with less antibiotic use or shorter duration of isolation. Results suggest that health care providers do not use viral test results in making management decisions at this hospital. Further research is needed to evaluate the effectiveness of respiratory infection control policies.

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)0.005
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 score0.007
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.041
GPT teacher head0.320
Teacher spread0.279 · 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

Citations27
Published2015
Admission routes3
Has abstractyes

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