Risk factors for intracranial hemorrhage in adults with acute leukemia
Bibliographic record
Abstract
Abstract Background Intracranial hemorrhage (ICH) is a rare, but serious complication in patients with acute leukemia. Little is known about why some patients experience serious bleeding, including ICH, while others do not. Materials and Methods Adults between 18 and 80 years old with acute leukemia and ICH between January 1, 2009 and December 31, 2016 were included. Matched controls were identified using the propensity score matching method. Clinical and laboratory characteristics and outcome data were collected to identify variables associated with ICH. Results Of 2578 patients diagnosed with acute leukemia during the study period, 55 cases and 161 matched controls were included. Patients who experienced ICH were older (62 vs. 55 years, p = .004) and more likely to have diabetes mellitus (p = .04). Patients with ICH had a higher baseline white blood cell count (mean 84.5 ± 115.8 vs. 28.7 ± 58.5 × 10 9 /L, p = .001), peripheral blast count (61.3 ± 96.5 vs. 21.2 ± 50.8 × 10 9 /L, p = .004), and a longer PT (16.5 ± 2.06 vs. 15.3 ± 3.2 s, p = .002). Neither the platelet count at diagnosis, the platelet nadir, the number of days with a platelet count of less than 10 × 10 9 /L, or a diagnosis of platelet refractoriness were associated with ICH. Conclusions Older age and more proliferative disease appear to be associated with ICH, whereas thrombocytopenia alone does not. In patients with newly diagnosed acute leukemia, aggressive cytoreduction in those with leukocytosis may help mitigate the risk of ICH.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".