Developing machine learning predictive models for personalized PEFR risk assessment in upper abdominal surgery patients: An observational study
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 62
- 试验地点
- 1
- 主要终点
- To assess various preoperative, intraoperative and postoperative factors that can cause reduction in postoperative PEFR.
研究概览
简要总结
62 patients scheduled for upper abdominal surgeries will be screened for inclusion and exclusion criteria and informed consent will be taken. The study involves collection of data on preoperative patient characteristics, surgical factors, anesthesia protocols and relevant parameters. Preoperative baseline data including demographic information, comorbidities and preoperative PFT will be recorded. Intraoperative data such as surgical details, anesthetic agents used, and duration of surgery will be documented. After surgery, postoperative PEFR will be done 6th hours, 24th hours & 48th hours. If the patients received truncal blocks in addition to general anesthesia will be noted.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 18.00 Year(s) 至 65.00 Year(s)（—）
- 性别
- All
入选标准
- •Patients scheduled for elective upper abdominal surgeries e.g. cholecystectomy, gastrectomy, hernia repair either open or laparoscopic.
- •Adults aged 18years and above.
排除标准
- •Emergency surgeries.
- •Patients unable to provide informed consent.
- •Patients who are unable to comprehend and perform PEFR.
结局指标
主要结局
To assess various preoperative, intraoperative and postoperative factors that can cause reduction in postoperative PEFR.
时间窗: Baseline | 6th hour postoperative | 24th hour postoperative | 48th hour postoperative
次要结局
- To develop predictive models using machine learning algorithms for assessment of risk factors of patients undergoing upper abdominal surgeries based on preoperative characteristics, surgical factors. and Anesthesia protocols to identify individuals at high risk reduction of PEFR.(To validate the predictive models and assess their accuracy in identifying patients at risk of reduced PEFR postoperative.)
研究者
Dr Lairenjam Deepa Devi
Rajarajeswari Medical college and hospital