Management of Febrile Critically Ill Adults: A Retrospective Assessment of Regional Practice
Bibliographic record
Abstract
The aim of this study was to report on fever epidemiology and management strategies within a general population of critically ill patients. This was a retrospective cohort study among febrile patients (temperature ≥38.3°C) without acute brain injury admitted to one of four regional adult intensive care units (ICUs). There were 7535 ICU admissions over the 30-month study period. One hundred patients with fever were randomly selected for detailed analysis and represent the study population. The study population had a median age (interquartile range) of 56 (43-69) years and a mean (±standard deviation) Acute Physiology and Chronic Health Evaluation II score of 22 (±9). Septic shock was the most common admission diagnosis (36%), followed by pneumonia (without a shock syndrome; 18%). Fifty-three percent of patients had fever at ICU admission. To investigate the etiology of fever, most patients (89%) had at least one culture sent to the laboratory for analysis and a blood culture (73%) was the most commonly ordered microbiologic investigation. A chest X-ray was ordered in 95% of patients within 48 hours of fever onset. The majority of patients had an infection as the cause of their fever (73%), with pneumonia as the most common diagnosis (70%, 51/73). Prior to the occurrence of fever, 74% of patients were on antibiotics and this increased to 85% within the first 24 hours after documentation of fever. Seventy-nine percent of patients were managed with antipyretic drugs (77%) and/or external cooling (29%); however, only five patients had an order written that specifically guided the use of these temperature-lowering agents. Fever was most commonly infectious in origin. Treatment of patients with fever was a common and nonstandardized practice in this cohort of critically ill patients. This is likely due to lack of evidence in support of a particular temperature management strategy.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".