Investigation of parameters associated with mortality in a palliative care unit
Bibliographic record
Abstract
Introduction: Effective palliative care reduces unnecessary hospital admissions and intensive care length of stay.The present study aimed to investigate the parameters associated with mortality in patients receiving palliative care support. Material and methods:This prospective observational study was conducted among inpatients in a palliative care unit.Results: A total of 177 patients hospitalized in the palliative care unit were included in the study.Of the patients, 84 (47.5%) were female and the mean age was 72.49 ±15.12 years.At the end of the follow-up period in the palliative care unit, 67 patients (37.9%) had died.A one-unit increase in albumin was associated with 66.6% lower odds of mortality [odds ratio (OR): 0.334, 95% confidence interval (CI): 0.141-0.791;p = 0.013] and a one-unit increase in Karnofsky performance scales (KPS) score was associated with 4.8% lower odds of mortality (OR: 0.952, 95% CI: 0.925-0.980;p = 0.001).In contrast, the odds of mortality were 4.851 times higher in patients with congestive heart failure (95% CI: 1.716-13.717;p = 0.003), 4.442 times higher in patients with solid organ malignancy (95% CI: 1.420-13.894;p = 0.01), 3.727 times in the presence of hypoxia at admission (95% CI: 1.504-9.239;p = 0.005), and 3.626 times higher in patients who developed an infection during follow-up (95% CI: 1.523-8.635;p = 0.004). Conclusions:The results of this study suggest that congestive heart failure, solid organ malignancy, hypoxia at admission, infection during follow-up, and low albumin level and KPS score may be indicators of poor outcome.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".