Prevalence of Bacteremia in Febrile Patients With Sickle Cell Disease: Meta-Analysis of Observational Studies.
Bibliographic record
Abstract
OBJECTIVE: Pneumococcal vaccination has decreased the bacteremia rate in both the general pediatric and sickle cell disease (SCD) populations. Despite this decrease, and an increasing concern for antibiotic resistance, it remains standard practice to obtain blood cultures and administer antibiotics in all febrile (>38.5°C) patients with SCD. We conducted a systematic review and meta-analysis of the available studies of the prevalence of bacteremia in febrile patients with SCD. METHODS: We searched the medical literature up to November 2018 in PUBMED, EMBASE, and Web of Science with terms epidemiology, prevalence, bacteremia, and sickle cell anemia. We only included studies with patients after 2000, when the pneumococcal 7-valent conjugate (PCV7) vaccine became widely available. The prevalence of bacteremia [95% confidence interval (CI)] was calculated by dividing the number of positive blood cultures by the number of febrile episodes. The I2 statistic measured heterogeneity between prevalence estimates. Bias in our studies was quantified by the Newcastle-Ottawa Quality Assessment Scale. RESULTS: Our search identified 228 citations with 10 studies meeting our inclusion/exclusion criteria. The weighted prevalence of bacteremia across all studies was 1.9% (95% CI, 1.22%-2.73%), and for Streptococcus pneumoniae bacteremia, it was 0.31% (95% CI, 0.16%-0.50%). Risks for bacteremia except central lines could not be determined because of the low prevalence of the outcome. CONCLUSIONS: There appears to be a need to develop a risk stratification strategy to guide physicians to manage febrile patients with SCD based on factors including, but not limited to, history and clinical examination, vaccination status, use of prophylactic antibiotics, laboratory values, likely source of infection, and accessibility to health care.
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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 | 0.022 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.052 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".