Predictors of septic shock among BCR/ABL-positive chronic myeloid leukemia patients admitted for sepsis: A nationwide study and analysis.
Bibliographic record
Abstract
e18569 Background: Cancer patients, especially those with chronic myeloid leukemia (CML), are susceptible to infections and develop sepsis, which can lead to septic shock and increased mortality. This study aims to identify the predictors of septic shock in BCR-ABL-positive CML patients hospitalized for sepsis. Methods: We conducted a retrospective analysis using the National Inpatient Sample, an extensive database of admission records from the United States. We focused on BCR-ABL-positive CML patients not in remission who were admitted with sepsis from 2016 to 2022. Multivariable logistic regression models were used to identify these patients' factors associated with septic shock. Results: Among 13,540 admissions for septicemia, 3,250 (24%) developed septic shock. The median age of patients with septic shock was 72 years, compared to 71 years in the non-shock group (p<0.01). Both sexes had similar mortality odds (aOR 1.021, 95% CI 0.753-1.385, p=0.894). Factors significantly associated with septic shock included age ≥60 years (aOR 1.278, 95% CI 1.132-1.443, p<0.01), frailty (aOR 1.353, 95% CI 1.212-1.51, p<0.001), malnutrition (aOR 1.354, 95% CI 1.186-1.546, p<0.001), liver cirrhosis (aOR 2.942, 95% CI 2.587-3.345, p<0.001), chronic kidney disease (aOR 1.161, 95% CI 1.059-1.273, p=0.001), and congestive heart failure (aOR 1.574, 95% CI 1.437-1.724, p<0.001). There were no significant sex-based differences (aOR 0.968, 95% CI 0.888-1.054, p=0.452). While Black patients had comparable odds of septic shock to Whites (aOR 1.027, 95% CI 0.902-1.168, p=0.69), Hispanics were less likely to develop septic shock (aOR 0.816, 95% CI 0.697-0.955, p=0.011). No statistical significance was found for other variables, like COPD, obesity, diabetes, metastasis, weekend admissions, or Medicaid/Private insurance status. Septic shock was associated with a more extended hospital stay (7.0 days vs. 5.0 days, p<0.01) and higher hospital charges ($90,661 vs. $50,475, p<0.01). Conclusions: Several factors, including age, frailty, malnutrition, and comorbidities such as liver cirrhosis, chronic kidney disease, and congestive heart failure, were identified as key predictors of septic shock in BCR-ABL-positive CML patients hospitalized for sepsis. These findings have the potential to significantly improve patient outcomes by helping healthcare providers triage and prioritize high-risk patients who develop septic shock.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".