Incidence and Risk Factors of Dysphagia After Cardiac Surgery: A Scoping Review
Bibliographic record
Abstract
Dysphagia is a serious complication following cardiac surgery, associated with increased morbidity, prolonged hospitalization, and higher healthcare costs. Variability in the incidence and risk factors highlights the need for consolidated evidence. This scoping review aimed to analyze the incidence of dysphagia after cardiac surgery and identify the associated risk factors. A search was conducted in the PubMed, Embase, Web of Sciences, and PEDro databases for observational studies reporting dysphagia incidence and risk factors in adult cardiac surgery patients. The Newcastle-Ottawa Scale was used to assess the studies' quality and out of 2920 studies identified, 15 met the inclusion criteria for inclusion in this review. Dysphagia incidence ranged from 2.7% to 60%, with higher rates observed when objective assessments such as FEES or VFSS were employed. Key risk factors included advanced age, prolonged intubation, cerebrovascular events, and complex operative procedures. Post-operative dysphagia was linked to complications like aspiration pneumonia, prolonged ICU/hospital stays, and increased healthcare costs. In conclusion, dysphagia is a significant but under-recognized complication of cardiac surgery. Advanced age, prolonged intubation, and surgical complexity are major risk factors. Standardized assessment protocols and early interventions are crucial to mitigating its impact and improving patient clinical outcomes.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".