Anesthesia, Surgery, Surgery Complications
Conditions
Keywords
Perioperative medicine, Outcome, Mortality, Morbidity
Brief summary
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.
Detailed description
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.
Interventions
None listed
Sponsors
Karolinska Institutet
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* 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
Exclusion criteria
* 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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Mortality | [Time Frame: Mortality will be recorded at 30, 60, 90 and 365 days after index surgery] | Death within the time frames described below |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| DAH30 (Days At Home alive at 30 days) | 30 days after index surgery | DAH30: Patients who are hospitalized for 14 days postoperatively but are alive on day 30 will have DAH30=16. Patients who are hospitalized for five days, then discharged, but return after 10 days for an additional 11-day stay, will have DAH30=14. Anyone who dies within 30 days will have DAH30=0. This outcome measure is validated in several studies and has a significant advantage in that it correlates well with complications, even better than length of stay (LOS). |
| DAH365 (Days At Home alive at 365 days) | 365 days after index surgery | DAH365: See above |
Countries
Sweden
Contacts
CONTACTMax Bell, MD, PhD
CONTACTArman Valadkhani, MD, PhD
Outcome results
None listed