Overview
This randomized controlled study aims to evaluate the effect of artificial intelligence (AI)-assisted respiratory training on fatigue, pain, and respiratory parameters in patients after open heart surgery.
Description
Open heart surgery and related procedures (such as sternotomy, cardiopulmonary bypass, and chest tubes) can negatively affect pulmonary functions and cause postoperative pain, fatigue, and limited respiratory muscle function. While standard care involves respiratory exercises, there is insufficient data regarding the combination of upper extremity Range of Motion (ROM) exercises with deep breathing. This study will utilize AI-generated educational videos, created using tools like ChatGPT, Gemini, and Adobe Firefly, to guide patients in performing these exercises safely and correctly. Participants will be randomized into three groups: a Rhythmic Breathing group, a Range of Motion-Deep Breathing (ROM-DB) group, and a Control group. The interventions will be applied for three consecutive days. The study will evaluate outcomes including respiratory rate, oxygen saturation, heart rate, pain levels, fatigue, dyspnea, and chest tube drainage volume.
Eligibility
Inclusion Criteria:
- Patients undergoing elective open heart surgery.
- Conscious.
- Speaks and understands Turkish.
- Has a chest tube inserted (on the right and/or left side).
- No visual, auditory, or mental problems.
- Willing to participate in the study.
Exclusion Criteria:
- Undergoing concurrent other chest surgery or having a history of re-surgery.
- Development of early postoperative complications (e.g., atelectasis) within 0-3 days.
- Any loss of an extremity.
- Long-term immobilization and intubation.
- Development of severe post-surgery infections (such as mediastinitis or sepsis) or respiratory complications (such as pneumonia or atelectasis).
