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Record W3113104590 · doi:10.1016/j.eclinm.2020.100675

Longitudinal evaluation of risk factors and outcomes of blood stream infections due to Staphylococcus species in persons with HIV: An observational cohort study

2020· article· en· W3113104590 on OpenAlexaffabout
Raynell Lang, M. John Gill, Quang Vu, Jeannine Viczko, C. Naugler, Deirdre L. Church

Bibliographic record

VenueEClinicalMedicine · 2020
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsAlberta Health ServicesUniversity of Calgary
Fundersnot available
KeywordsMedicineHazard ratioMethicillin-resistant Staphylococcus aureusInternal medicineIncidence (geometry)ConfoundingObservational studyCoinfectionHuman immunodeficiency virus (HIV)Staphylococcus aureusPediatricsImmunologyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: (CoNS). METHODS: Using linked longitudinal clinical and microbiologic databases, all cases of SBSI in PWH accessing care at Southern Alberta Clinic were identified and demographic features and outcomes characterized. We compared participants with SBSI to those with no SBSI and determined the 1-year all-cause mortality following SBSI and longitudinally over the study period. FINDINGS: = <0.001) for SBSI compared to no SBSI, following adjusting for confounding. Seventy deaths occurred in persons with SBSI with 40% in the first year. Higher 1-year mortality rates occurred in hospital-acquired infections. INTERPRETATION: Incidence rates of SBSI are high in PWH, with identified characteristics that further increase this risk. PWH who experience SBSI have a significant mortality risk within the first year of follow-up, however they also have greater long-term all-cause mortality compared to those with no SBSI. Further investigation is needed in PWH evaluating host, environment and pathogen differences that lead to differing rates of SBSI and mortality seen here. FUNDING: No funding was received for this work.

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)0.001
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 score0.010
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.116
GPT teacher head0.377
Teacher spread0.261 · 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

Citations5
Published2020
Admission routes2
Has abstractyes

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