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Record W2564678983 · doi:10.1182/blood.v104.11.884.884

High Risk AML Outpatient Management: A Retrospective Analysis of Bacteremia Incidence Following Chemotherapy.

2004· article· en· W2564678983 on OpenAlexaff
Timotheus Y. Halim, Julye C. Lavoie, Michael J. Barnett, Stephen H. Nantel, Thomas J. Nevill, John D. Shepherd, Heather J. Sutherland, Donna E. Hogge, Kevin Song, Donna L. Forrest, Cynthia L. Toze, Clay Smith

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsMedicineBacteremiaFluconazoleChemotherapyIncidence (geometry)Internal medicineChemotherapy regimenIntensive care medicineAntibiotics

Abstract

fetched live from OpenAlex

Abstract Treatment of acute myeloid leukemia (AML) involves aggressive remission inducing (IND) chemotherapy, and consolidation (CON) chemotherapy aimed at preventing or delaying relapse. Since September 2001, our institution has implemented a selective discharge protocol, which allows the majority of CON cycles, and some selected IND cycles, to be administered entirely on outpatient (OP), or early discharge (ED: prior to ANC >0.5 x 109/L or before d+15) basis. One of the primary concerns associated with this novel practice is the prompt management of infections in these high-risk neutropenic patients, requiring immediate administration of empirical broad spectrum parenteral antibiotics. Our group previously reported the safety and feasibility of OP management (Savoie Blood 2002, 100:11 p766a). We now present a comparative review of the incidence of septicemia over a 5 year period, encompassing the change in management policy. We investigated the impact of selective discharge on infectious morbidity, and the spectrum of bacterial pathogens and their resistance profile. OP received all standard chemotherapy and supportive care in outpatient settings. Supportive care was modified for OP, adding Ciprofloxacin 500mg po BID as antimicrobial prophylaxis d+1 from the start of chemotherapy. Universal supportive care for all pts consisted of Acyclovir 600mg po qid or Valacyclovir 500mg po od (if HSV IgG positive) and Fluconazole 200–400mg po od or Itraconazole 200mg po bid (if previously aspergillus infection). The prophylaxis was stopped upon ANC recovery. Pts were not routinely treated with G-CSF. Between Feb 1999 and Feb 2004, 328 IND and 295 CON cycles of chemotherapy (total=623) were given to 295 patients. Following guidelines adopted in Sep 1, 2001 the majority of CON cycles [84% (133/159)] were administered to pts in our OP day-care clinic, also a smaller number of CON and some IND cycles were candidates for ED. Analysis of trends indicated a minor decrease in overall bacteremia incidence following the implementation of OP protocol. [21% (65/303) before 1-Sept-01, 19% (61/320) after 1-Sept-01),NS]. However, a significant decrease in bacteremia was observed in the CON cycle subgroup (which included the largest OP population), from 31% (42/136) before, to 19% (29/159) after 1-Sept-01 (p=0.01). In addition, a notable shift in incidence of gram-ve bacteremia occurred in IP (-cipro prophylaxis) compared to OP (+cipro prophylaxis) from 49% to 27% of total bacterial infections. Nevertheless, a larger fraction of gram-ve isolates from OP exhibited resistance to ciprofloxacin. No treatment related deaths occurred as a result of infection in the OP population. This report constitutes the first comparative study of bacteremial complications in high risk neutropenic AML patients treated in OP settings. OP management in conjunction with prophylactic antibiotherapy is safe, and results in a significant decrease in bacteremia. However, the use of gram-ve coverage prophylaxis introduced a shift in pathogenic microorganisms and emergence of resistance. Supported by our findings we propose that selective OP management of AML pts should be encouraged, keeping in mind the change in the spectrum of infections.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.245
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2004
Admission routes1
Has abstractyes

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