Efficacy of measuring procalcitonin levels in determination of prognosis and early diagnosis of bacterial resistance in sepsis
Bibliographic record
Abstract
BACKGROUND: Rapid and proper diagnosis of sepsis is one of the daily challenges of emergency department (ED) and intensive care units. The general aim of the present study was to determine the efficacy of measuring procalcitonin levels in the early diagnosis of bacterial resistance to antibiotics administered empirically in patients with sepsis. MATERIALS AND METHODS: The present cross-sectional study consisted of patients with clinical evidence of sepsis or systemic inflammatory response syndrome (SIRS), referring to the ED of a third-level hospital in Tehran, Iran in 2012. After collection of basic and clinical data of patients, venous blood samples were taken for routine laboratory tests and determination of procalcitonin serum levels at baseline and 6 and 24 hours after administration of the first dose of an empirical antibiotic. The subjects were divided into two groups of discharged and expired and then comparisons were made using t-test, Chi-squared test and Fisher's test. Specificity and sensitivity of procalcitonin were evaluated along with ROC curve. RESULTS: In the present study, 170 patients with sepsis were included. Evaluation of serum levels of procalcitonin 24 hours after administration of antibiotics exhibited the best sensitivity and specificity for each patient's response to antibiotics. Use of the cutoff point of 6.5 mg/mL for procalcitonin can predict the disease outcome with sensitivity and specificity of 67% and 80%, respectively. CONCLUSION: It is suggested that procalcitonin be used for the diagnosis of sepsis or SIRS resulting from an infectious disease, for follow-up of treatment and for evaluation of response to treatment.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 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".