Identification of Predictors of Adverse Health Outcomes in Acute Care Patients with Dysphagia
Bibliographic record
Abstract
Purpose: Dysphagia, common among adult patients in acute care settings, is associated with various complications. This study aimed to identify significant predictors of adverse health outcomes in hospitalized patients with dysphagia. Methods: A consulting committee meeting preceded a retrospective chart review involving 420 adult patients (mean age 72 years, 55% male) hospitalized at CHU de Québec—Université Laval, who underwent an interdisciplinary dysphagia assessment. Multivariate logistic and linear regression analyses were conducted to examine relationships between potential predictors and outcomes (in-hospital mortality and pneumonia), with age and sex as covariates. Results: The consulting committee agreed that most predictors of adverse health outcomes, identified through the research team’s clinical experience and existing literature, were both important and applicable to clinical practice. Stroke, head and neck cancer, all types of malnutrition, and unauthorized food intake were the most significant predictors of mortality (P < 0.04, for all). Intellectual disability, chronic obstructive pulmonary disease, gastroesophageal reflux, and severe malnutrition were the most significant predictors of pneumonia (P ≤ 0.02, for all). Conclusion: This study highlights the importance of addressing malnutrition as a significant modifiable risk factor for mortality and pneumonia among hospitalized patients with dysphagia. These findings underscore the need to manage high-risk patients with dysphagia effectively.
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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 | 0.002 | 0.001 |
| 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 | 0.000 | 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".