Poor cardiopulmonary fitness is an important risk factor for postoperative complications, yet a feasible, objective and prognostically accurate method to assess preoperative fitness has not been established. The 6 min walk test (6MWT) is a simple, inexpensive and widely applicable measure that shows promise for predicting postoperative risk. However, robust data are lacking on whether the 6MWT accurately predicts complications, provides incremental prognostic value beyond routinely collected clinical factors or outperforms simpler alternatives such as questionnaires, cardiac biomarkers or grip strength testing. The Functional Assessment for Surgery by a Timed Walk (FAST Walk) study is designed to address these knowledge gaps by evaluating whether the 6MWT improves prediction of key postoperative outcomes compared with clinical factors and simpler measures of fitness.

The FAST Walk study is an international multicentre prospective cohort study of 1672 adults (≥40 years) undergoing major elective non-cardiac surgery at centres in Canada, Hong Kong, Australia, Spain and the Netherlands. Participants complete a preoperative 6MWT and baseline assessments of comorbidities, self-reported cardiopulmonary fitness (MET: Re-evaluation for Perioperative Cardiac Risk questionnaire), biomarkers (N-terminal pro-B-type natriuretic peptide) and grip strength. The primary outcome is 30-day death or major postoperative complication, defined as Clavien-Dindo grade II or higher. Secondary outcomes are (1) death or new significant disability at 90 days after surgery and (2) days alive and out of hospital at 30 days after surgery. Disability is measured using the short-form WHO Disability Assessment Schedule 2.0 instrument. Multivariable regression models and complementary metrics of prediction performance will be used to determine whether 6MWT distance adds prognostic value beyond routinely collected clinical factors and simpler measures of fitness.

The FAST Walk study has received research ethics board approval at all participating sites. Recruitment commenced in June 2024, with completion of participant follow-up expected in 2026. Findings will be disseminated through peer-reviewed publications and conference presentations, with the primary results anticipated in 2027.

NCT06412367.

To develop prediction models for short-term outcomes following a first acute myocardial infarction (AMI) event (index) or for past AMI events (prevalent) in a national primary care cohort.

Retrospective cohort study using logistic regression models to estimate 1-year and 5-year risks of all-cause mortality and composite cardiovascular outcomes.

Primary care practices in England contributing data to the Clinical Practice Research Datalink (CPRD) Aurum and CPRD GOLD databases between 2006 and 2019.

Patients with an incident (index) or prevalent AMI event. Models were trained on a random 80% sample of CPRD Aurum (n=1018 practices), internally validated on the remaining 20% (n=255) and externally validated using CPRD GOLD (n=248).

Discrimination assessed using sensitivity, specificity and area under the receiver operating characteristic curve (AUC). Calibration assessed using calibration plots.

In the index (prevalent) cohorts, 94 241 (64 789) patients were included in the training and internal validation sets, and 16 832 (7479) in the external validation set. For the index cohort, AUCs for 1-year [5-year] all-cause mortality were 0.802 (95% CI 0.793 to 0.812) [0.847 (0.841 to 0.853)] internally and 0.800 (0.790 to 0.810) [0.841 (0.835 to 0.847)] externally. For the primary composite outcome (stroke, heart failure and all-cause death), AUCs were 0.763 (0.756 to 0.771) [0.824 (0.818 to 0.830)] internally and 0.748 (0.739 to 0.756) [0.808 (0.801 to 0.815)] externally. Discrimination was higher in the prevalent cohort, particularly for 1-year mortality (AUC: 0.896, 95% CI 0.887 to 0.904). Models excluding treatment variables showed slightly lower but comparable performance. Calibration was acceptable across models.

These models can support clinicians in identifying patients at increased risk of short-term adverse outcomes following AMI, whether newly diagnosed or with a prior history. This can inform monitoring strategies and secondary prevention and guide patient counselling on modifiable risk factors.