Bibliographic record
Abstract
Introduction: Patients with hematologic malignancy are at increased risk of developing life-threatening complications that can lead to admission to an Intensive Care Unit (ICU). Acute respiratory failure is the most frequent reason for ICU admission in these patients. Existing knowledge gaps in the field include the lack of population-based estimates of the incidence and timing of ICU admission in these patients and the associated risk factors; uncertainty about the relative effectiveness of treatments for acute hypoxemic respiratory failure; and information about long-term outcomes and symptoms for patients with hematologic malignancies who survive an ICU admission. Objectives: This thesis 1) characterizes the epidemiology of critical illness after a new diagnosis of hematologic malignancy in a large population-based cohort in Ontario, Canada; 2) evaluates the effectiveness of different noninvasive oxygenation strategies for reducing the receipt of invasive mechanical ventilation and decreasing mortality in patients with acute hypoxemic respiratory failure; and 3) describes the association between ICU admission and subsequent patient-reported symptoms in patients with hematologic malignancies who received hematopoietic cell transplantation. Synthesis: Between April 1st 2006 and March 31st 2017, 87965 patients were diagnosed with hematologic malignancy in Ontario. The one-year incidence of ICU admission was 13.9% (median time to ICU 35 days), ranging from 7.3% for patients with indolent lymphoma to 22.5% for patients with acute myeloid leukemia. Among ICU patients, 36.7% required invasive mechanical ventilation and in-hospital mortality was 31.0%. We found that the use of noninvasive ventilation provided by either a helmet or a face mask interface or use of high flow nasal oxygen decreased the risk of receiving invasive mechanical ventilation or dying in patients with acute hypoxemic respiratory failure. Among 5844 patients with hematologic malignancy who received hematopoietic cell transplantation, ICU admission was associated with a higher risk of reporting moderate to severe symptoms during follow-up across multiple symptom domains. Conclusion: This thesis provides important findings about the epidemiology of ICU admission for patients with a new hematological malignancy and describes the impact that ICU admission and treatments can have on subsequent outcomes.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".