Perioperative Predictive Value of Physical Activity on Short- and Long-term Morbidity and Mortality
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 50,000
- 试验地点
- 1
- 主要终点
- Mortality
研究概览
简要总结
Over 300 million surgeries are performed globally every year. Complications after surgery - infections, cardiovascular conditions, postoperative pulmonary complications and renal impairment - affect survival and quality of life.
Age and co-morbidity are unmodifiable factors, contributing to increased risk of these perioperative complications. However, a modifiable risk factor is physical activity. This study aims to test if self reported physical activity has added predicted value, beyond established risk factors, for predicting perioperative morbidity and mortality.
详细描述
Research question: This cohort study investigates if higher levels of self reported physical activity at preoperative assessment has added predicted value, beyond established risk factors, for predicting perioperative morbidity and mortality.
Background: Previous studies of perioperative outcomes in high-income countries indicate that close to 20% had complications within 30 days after surgery, and that around 3% died within 1 yr after surgery. In multiple studies, postoperative complications massively increase risk of 1yr mortality. Whilst perioperative complications are under-reported, they affect length of stay and days at home up to 30 days after surgery (DAH30). DAH30 is a validated, patient-centered outcome measure with prognostic importance due to high sensitivity to changes in surgical risks and the impact of surgical complications. DAH365, the days at home up to one year after surgery, is also an important patient-centered outcome measure.
Data collection: Age, sex, body mass index, co-morbid conditions (using ICD-codes and reported medication) as well as American Society of Anesthesiologists (ASA) physical status classification will be recorded. The predictor of interest: the Metabolic Equivalent of Task Score (MET-score), reported in the electronic health record by the attending anesthesiologist based on patient history in conjunction with the preoperative assessment.
Analysis: The MET-score is the predictor of interest. The potential added predictive value of the MET-score, will be assed using a machine learning approach, by comparing it to other established predictive factors.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Elective non-cardiac surgery patients (equal to or over 18 years) at the two study sites, Karolinska University Hospital Solna and Karolinska University Hospital Huddinge
排除标准
- •Patients under the age of 18, transplant, day surgery, acute surgery, anesthesia monitoring, brachy therapy and gamma knife interventions. In case of multiple surgeries, only the first will be included.
结局指标
主要结局
Mortality
时间窗: [Time Frame: Mortality will be recorded at 30, 60, 90 and 365 days after index surgery]
Death within the time frames described below
次要结局
- DAH30 (Days At Home alive at 30 days)(30 days after index surgery)
- DAH365 (Days At Home alive at 365 days)(365 days after index surgery)
研究者
Max Bell
Associate Professor, Senior Lecturer
Karolinska Institutet
