Use of daunorubicin and cytarabine in adults with acute myeloid leukemia and associated risk factors for inpatient mortality: National inpatient sample review.
Bibliographic record
Abstract
e19029 Background: According to American Cancer Society’s 2023 estimates, Acute Myeloid Leukemia (AML) is the most common leukemia in adults, involving up to 34% of new cases in the United States. The conventional cytotoxic therapy in AML involves induction therapy with cytarabine and an anthracycline daunorubicin or idarubicin. The purpose of this study was to assess patient traits and disease variables augmenting mortality risk in AML patients treated with cytarabine and daunorubicin. Methods: We used the 2016-2020 National inpatient sample (NIS), via SPSS 29. 0, to find adult patients with a diagnosis of AML and use of Daunorubicin/Cytarabine. Several patient characteristics and comorbidities such as sex, race, obesity, diabetes, and hypertension were identified. The mortality rate among these patients were estimated and logistic regression models were used to report risk factors of mortality and their associated adjusted odds ratio and 95% confidence interval (95% CI). Results: Our analysis found 6695 cases of AML using Daunorubicin/Cytarabine. Among them 47.1% were above the age of 60, 45.7% were covered under private insurance, 71.8% were of White race, 54.4% were males and 31.8% were smokers. 10.3% of patients were admitted on the weekend. Various comorbidities were seen including diabetes (14.7%), obesity (13.0%), hypertension (32.9%), history of old myocardial infarction (2.5%), and cirrhosis (3.0%). While admitted, patients experienced a range of side effects and complications including fever (2.2%), nausea and vomiting (9.4%), weakness or malaise or fatigue (4.4%), septicemia (18.6%), Acute Kidney Injury (AKI) (18.5%), cardiac dysrhythmias (16.0%), cardiogenic shock (0.5%) and secondary or unspecified thrombocytopenia (21.0%). Unfortunately, 415 patients died (6.2%) during hospitalization. A higher risk of mortality was seen in weekend admissions (aOR 1.687, 95% CI 1.227-2.318, p < 0.01), those who developed septicemia (aOR 7.859, 95% CI 6.076-10.164, p < 0.01), and AKI (aOR 3.095, 95% CI 2.396-3.998, p < 0.01). Mortality risk was also higher in those with cirrhosis (aOR 6.367, 95% CI 4.139-9.794, p < 0.01) and age more than 60 (aOR 3.174, 95% CI 2.275-4.428, p < 0.01). However, a lower mortality risk was seen in patients with hypertension (aOR 0.689, 95% CI 0.518-0.918, p = 0.011). Conclusions: Various factors such as weekend admissions, septicemia, AKI, cirrhosis, and age > 60 were associated with poorer outcomes while hypertensive patients had a lower mortality rate. The drawbacks of this study were that complications and side effects couldn't be quantified in proportion to doses or number of cycles received post induction with or without consolidation therapy with cytarabine and daunorubicin. Further studies in clinical settings should investigate the various disparities observed in our study.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".