Defining microbial invasion of the bloodstream: a structured review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Microbial invasion of the bloodstream is associated with a major burden of illness. Despite its importance, there is inconsistency in utilization of terms used to define it.Objective: To characterize the contemporary use of terms to define microbial invasion of the bloodstream for surveillance and research purposes.Methods: Structured review of publications reported from 2000 to 2019.Results: The search strategy retrieved 10,095 citations of which bloodstream infection, bacteraemia and fungaemia were included in 2813, 6900 and 1054 articles, respectively. There was a tripling of the number of annual citations during the study and although bacteraemia was most frequent, there was a progressive increase in the use of the term bloodstream infection. Among the 100 reports randomly selected for detailed review, the terms bacteraemia, bloodstream infection and fungaemia were used in 57, 51 and 19 publications, respectively. Explicit definitions for bloodstream infection (26/51; 51%), bacteraemia (13/57; 23%) and fungaemia (7/19; 37%) were included in reports where these terms were used. Although nearly all (95%) of the studies indicated a positive blood culture as an inclusion criteria and/or definition, only a minority indicated means to exclude contaminants (33%) or specific attributes to support clinical significance (38%). Use of explicit definitions was more common among reports that exclusively used the term bloodstream infection as compared to bacteraemia.Conclusions: Terms have been inconsistently defined and imprecisely used to refer to microbial invasion of the bloodstream. Clinically relevant and objective definitions that are widely acceptable are needed for surveillance and research purposes.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it