MétaCan
Menu
Back to cohort
Record W4405046519 · doi:10.1182/blood-2024-202081

Outcomes in AML Patients Admitted to the ICU Following Allogeneic Stem Cell Transplantation

2024· article· en· W4405046519 on OpenAlexaff
Ali Mushtaq, Aastha Dhakal, John Hanna, Michael Sheu, Faiz Anwer, Zachary A. Yetmar, Thomas Crilley, Aneela Majeed

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineSepsisIntensive care unitTransplantationInternal medicineHematopoietic stem cell transplantationRetrospective cohort studyMechanical ventilationGraft-versus-host diseaseSurgery

Abstract

fetched live from OpenAlex

Background: Patients with acute myeloid leukemia (AML) who undergo an allogeneic stem cell transplant (allo-SCT) frequently require admission to the intensive care unit (ICU) within the first 100 days post-transplant, which is often associated with a poor prognosis. This retrospective study aims to evaluate the clinical outcomes and infection epidemiology among patients who require ICU admission during this critical period. Methods: We screened 438 AML patients who underwent allo-SCT between 2012 and 2023, including adult patients ≥ 18 years old, within 100 days of their index transplantation who required ICU admission for more than 72 hours. 65 patients met these criteria. Patients were divided into sepsis (N=46) and non-sepsis (N=19) groups, and baseline characteristics, treatment regimens, and outcomes were compared. Univariable Cox regression was used to assess factors associated with 90-day mortality after ICU admission. Results: The median age was 56.8 years in the sepsis group and 63.9 years in the non-sepsis group, with males comprising 43.5% and 57.9%, respectively. The median time from transplant to ICU admission was 20 days. Graft-versus-host disease (GVHD) was more prevalent in the sepsis group (34.8% vs. 26.3%, p=0.5072), with 64.3% of GVHD patients receiving methylprednisolone. Both groups received comparable GVHD and antimicrobial prophylaxis. Patients with sepsis had a significantly higher rates of mechanical ventilation (67.4% vs. 15.8%, p<0.001), longer ventilator duration (7.0 days vs. 2.0 days, p=0.03), vasopressor requirement (69.6% vs. 15.8%, p=<0.001), and extended ICU stays (median 9.5 days vs. 3.0 days, p<0.001). Among septic patients, survivors (N=8) had fewer comorbidities and higher rates of GVHD (50% vs. 31.6%, p=0.421) compared to those who died (N=38). We found no significant differences in comorbidities, neutropenia, lymphocyte count, GVHD prophylaxis, or antimicrobial prophylaxis between survivors and non-survivors. Sepsis before engraftment was more common in survivors (71.4% vs. 61.8%), with no significant differences in lactate levels (3.3 vs. 2.7). Overall, 52 patients (80%) died within 90 days of ICU admission. Univariable analyses revealed that sepsis (hazard ratio [HR] 3.34, 95% confidence interval [CI] 1.47-7.57; p=0.004), renal replacement therapy (HR 2.35, 95% CI 1.23-4.48; p=0.010), and mechanical ventilation (HR 3.14, 95% CI 1.61-6.12; p<0.001) were associated with increased 90-day mortality, while GVHD was not significantly associated (HR 1.25, 95% CI 0.65-2.39; p=0.506). Lastly, there were no significant differences in infection types or antimicrobial usage between the sepsis and non-sepsis groups. The most identified organisms were Klebsiella, Enterococcus, and Pseudomonas, with no significant differences between survivors and non-survivors. Conclusion: Sepsis significantly worsens clinical outcomes in AML patients undergoing allo-SCT, leading to higher rates of mechanical ventilation, prolonged ICU stays, and increased 90-day mortality. Early identification and aggressive management of sepsis are essential for improving mortality outcomes in this high-risk population.

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 score0.014
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBloodSame topicNeutropenia and Cancer InfectionsFrench-language works237,207