Does This Adult Patient With Suspected Bacteremia Require Blood Cultures?
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
CONTEXT: Clinicians order blood cultures liberally among patients in whom bacteremia is suspected, though a small proportion of blood cultures yield true-positive results. Ordering blood cultures inappropriately may be both wasteful and harmful. OBJECTIVE: To review the accuracy of easily obtained clinical and laboratory findings to inform the decision to obtain blood cultures in suspected bacteremia. DATA SOURCES AND STUDY SELECTION: A MEDLINE and EMBASE search (inception to April 2012) yielded 35 studies that met inclusion criteria for evaluating the accuracy of clinical variables for bacteremia in adult immunocompetent patients, representing 4566 bacteremia and 25,946 negative blood culture episodes. DATA EXTRACTION: Data were extracted to determine the prevalence and likelihood ratios (LRs) of findings for bacteremia. DATA SYNTHESIS: The pretest probability of bacteremia varies depending on the clinical context, from low (eg, cellulitis: 2%) to high (eg, septic shock: 69%). Elevated temperatures alone do not accurately predict bacteremia (for ≥38°C [>100.3°F], LR, 1.9 [95% CI, 1.4-2.4]; for ≥38.5°C [>101.2°F], LR, 1.4 [95% CI, 1.1-2.0]), nor does isolated leukocytosis (LR, <1.7). The severity of chills graded on an ordinal scale (shaking chills, LR, 4.7; 95% CI, 3.0-7.2) may be more useful. Both the systemic inflammatory response syndrome (SIRS) and a multivariable decision rule with major and minor criteria are sensitive (but not specific) predictors of bacteremia (SIRS, negative LR, 0.09 [95% CI, 0.03-0.26]; decision rule, negative LR, 0.08 [95% CI, 0.04-0.17]). CONCLUSIONS: Blood cultures should not be ordered for adult patients with isolated fever or leukocytosis without considering the pretest probability. SIRS and the decision rule may be helpful in identifying patients who do not need blood cultures. These conclusions do not apply to immunocompromised patients or when endocarditis is suspected.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 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