Fever in Adult ICUs
Bibliographic record
Abstract
OBJECTIVES: Fever is common and associated with increased mortality among patients admitted to adult ICUs, yet recent literature suggests that the incidence of fever may be decreasing. The objective of this study was to determine whether the incidence of fever in adult ICUs changed over time and the factors responsible for the observed change. DESIGNS: Interrupted time series analysis. The primary outcome was the cumulative incidence of fever (temperature ≥ 38.3 °C). Secondary outcomes included the cumulative rate of blood cultures ordered, and the cumulative incidence of bloodstream infections and ventilator-associated pneumonia. Data were analyzed with segmented linear regression and adjusted for important confounding variables. SETTING: Calgary zone of Alberta Health Services between January 1, 2004, and June 30, 2009. PATIENTS: Adults (age ≥ 18 yr) admitted to ICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 18,989 ICU admissions among 17,153 patients. The cumulative incidence of fever during ICU admission decreased from 50.1% of all patients to 25.5% over the 5.5-year study period. Implementation of a new noninvasive thermometer was associated with a 5.1% (95% CI, 1.4-8.9%, p = 0.01) absolute decrease in fever incidence; however, the decrease in fever incidence was predominantly a function of a constant baseline decrease of 1.1% per quarter (95% CI, 0.8-1.5%, p < 0.0001). Multivariate logistic time series regression found that time and thermometer change were the only independent predictors of the changing incidence of fever. The ordering of blood cultures, bloodstream infection incidence, and ICU mortality were unchanged throughout the study period. CONCLUSIONS: The incidence of fever in adult ICUs decreased considerably over time. The lack of change in the ordering of blood cultures and the incidence of bloodstream infections calls into question the importance of fever during the diagnostic evaluation of critically ill patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".