Outcome of Lung Cancer Patients Admitted to the Intensive Care Unit
Bibliographic record
Abstract
In Brief We investigate the outcome of lung cancer patients admitted to the medical intensive care unit (MICU) and examine potential predictors of mortality. A retrospective quality assurance study of primary lung cancer patients admitted to the MICUs at 2 local tertiary care university hospitals from January 1, 1994 to May 12, 2004 was conducted (n = 69). Data on demographics and tumor-related data were collected using the hospital records of all patients admitted to MICU with a diagnosis of lung cancer. Statistical analysis was performed to determine the prognostic factors associated with MICU and hospital mortality as well as MICU and hospital lengths of stay. The MICU mortality rate was 50.7% and the mean MICU length of stay was 3.0 days. Multivariate analysis determined that Acute Physiology and Chronic Health Evaluation (APACHE II) scores, Therapeutic Intervention Scoring System scores, and non-small cell lung cancer were significantly associated with MICU mortality, whereas age and APACHE II scores were associated with hospital mortality. Respiratory failure upon admission and use of a Swan Ganz monitor were predictors of increased MICU length of stay, and chemotherapy administration and mechanical ventilation predicted increased hospital length of stay. The 50.7% mortality rate for patients with previously or newly diagnosed primary lung cancer admitted to the MICU is lower than the previously reported mortality rate of 66.7% for a period of 1986. Although the mortality remains high, an improvement over the previous decade has occurred and is comparable to that for patients requiring MICU admission for other indications. There is a high mortality rate associated with medical intensive care unit (MICU) admission for patients with previously or newly diagnosed primary lung cancer. However, it has improved over the previous decade and is comparable to that among patients requiring MICU admission for other illness such as pneumonia, adult respiratory distress syndrome, sepsis, and cardiopulmonary resuscitation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".