The impact of airway management guided by Protection Motivation Theory on the prevention and prognosis of post-stroke pneumonia
Bibliographic record
Abstract
Background Stroke remains a leading cause of morbidity and mortality worldwide, with post-stroke pneumonia significantly impacting patient outcomes. Despite progress in stroke management, there was a lack of emphasis on targeted preventive measures for pneumonia. This study evaluates the impact of airway management guided by Protection Motivation Theory (PMT) on preventing post-stroke pneumonia. Methods A retrospective study was conducted with 100 stroke patients admitted to the general neurology ward between January and December 2023. Patients were divided into two groups based on chronological admission order: 50 received standard airway management (January–June 2023), and 50 received PMT-guided intervention (July–December 2023). The PMT group engaged in structured educational sessions (30 min daily for 7 days) and actionable coping strategies to enhance adherence to airway management. Outcomes assessed included incidence of post-stroke pneumonia (diagnosed by chest CT within 7 days post-admission), respiratory function, length of hospital stay, and cognitive and psychological measures. Results The PMT group showed a lower incidence of pneumonia (16% vs. 34%, p = 0.038) and reduced hospital stay (13.47 ± 3.86 days vs. 15.72 ± 4.36 days, p = 0.007). The absolute risk reduction was 18% with a number needed to treat (NNT) of 5.6. Improvements were noted in respiratory function, with higher forced vital capacity (2.46 ± 0.68 L vs. 2.15 ± 0.56 L, p = 0.013). Cognitive function, as measured by the Montreal Cognitive Assessment, was enhanced (23.58 ± 4.06 vs. 21.35 ± 3.84, p = 0.006), with both groups remaining below the normal threshold of 26 points. Depression levels were reduced (PHQ-9: 12.05 ± 3.12 vs. 13.46 ± 3.56, p = 0.038). Conclusion PMT-guided airway management significantly enhances post-stroke outcomes through improved respiratory function, reduced pneumonia incidence, and better cognitive and psychological wellbeing. Future prospective studies with larger sample sizes are warranted to validate these findings.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".