The Use of Intravenous Antibiotics at the Onset of Neutropenia in Patients Receiving Outpatient-Based Hematopoietic Stem Cell Transplants
Bibliographic record
Abstract
Empirical antibiotics at the onset of febrile neutropenia are one of several strategies for management of bacterial infections in patients undergoing Hematopoietic Stem Cell Transplant (HSCT) (empiric strategy). Our HSCT program aims to perform HSCT in an outpatient setting, where an empiric antibiotic strategy was employed. HSCT recipients began receiving intravenous antibiotics at the onset of neutropenia in the absence of fever as part of our institutional policy from 01 Jan 2009; intravenous Prophylactic strategy. A prospective study was conducted to compare two consecutive cohorts [Year 2008 (Empiric strategy) vs. Year 2009 (Prophylactic strategy)] of patients receiving HSCT. There were 238 HSCTs performed between 01 Jan 2008 and 31 Dec 2009 with 127 and 111 in the earlier and later cohorts respectively. Infection-related mortality pre- engraftment was similar with a prophylactic compared to an empiric strategy (3.6% vs. 7.1%; p = 0.24), but reduced among recipients of autologous HSCT (0% vs. 6.8%; p = 0.03). Microbiologically documented, blood stream infections and clinically documented infections pre-engraftment were reduced in those receiving a prophylactic compared to an empiric strategy, (11.7% vs. 28.3%; p = 0.001), (9.9% vs. 24.4%; p = 0.003) and (18.2% vs. 33.9% p = 0.007) respectively. The prophylactic use of intravenous once-daily ceftriaxone in patients receiving outpatient based HSCT is safe and may be particularly effective in patients receiving autologous HSCT. Further studies are warranted to study the impact of this Prophylactic strategy in an outpatient based HSCT program.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".