Clinical and Economic Outcomes Associated with Dysphagia in Hospitalized Patients with Parkinson’s Disease
Bibliographic record
Abstract
BACKGROUND: Dysphagia is a frequent complication that may increase morbidity and mortality in Parkinson's disease (PD). Nevertheless, there is limited data on its objective impact on healthcare outcomes. OBJECTIVE: To investigate the outcomes associated with dysphagia in hospitalized patients with PD and associated healthcare costs and utilization. METHODS: We performed a retrospective cohort study using the National Inpatient Sample (NIS) data from 2004 to 2014. A multivariable regression analysis was adjusted for demographic, and comorbidity variables to examine the association between dysphagia and associated outcomes. Logistic and negative binomial regressions were used to estimate odds or incidence rate ratios for binary and continuous outcomes, respectively. RESULTS: We identified 334,395 non-elective hospitalizations of individuals with PD, being 21,288 (6.36%) associated with dysphagia. Patients with dysphagia had significantly higher odds of negative outcomes, including aspiration pneumonia (AOR 7.55, 95%CI 7.29-7.82), sepsis (AOR 1.91, 95%CI 1.82-2.01), and mechanical ventilation (AOR 2.00, 95%CI 1.86-2.15). For hospitalizations with a dysphagia code, the length of stay was 44%(95%CI 1.43-1.45) longer and inpatient costs 46%higher (95%CI 1.44-1.47) compared to those without dysphagia. Mortality was also substantially increased in individuals with PD and dysphagia (AOR 1.37, 95%CI 1.29-1.46). CONCLUSION: In hospitalized patients with PD, dysphagia was a strong predictor of adverse clinical outcomes, and associated with substantially prolonged length of stay, higher mortality, and care costs. These results highlight the need for interventions focused on early recognition and prevention of dysphagia to avoid complications and lower costs in PD patients.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".