58 4-metre-gait speed as a predictor of 5-year survival after acute myocardial infarction: a prospective cohort study. (6th June 2022)

• Record Type: Journal Article
• Authors: Sharma, Pranev; Thomas, Katharine; Rogers, Paula; Prendergast, Claire; Banya, Winston; Lane, Rebecca; Nolan, Claire; Jones, Sarah; Canavan, Jane; Kon, Samantha; Man, William; Dalby, Miles
• Is Part Of: Heart. Volume 108(2022)Supplement 1
• Page Start: A43
• Page End: A44
• Publication Date: 2022-06-06
• Subjects: Gait-speed -- Percutaneous coronary intervention -- Myocardial infarction; Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/heartjnl-2022-BCS.58
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : Introduction: Patients undergoing primary percutaneous coronary intervention (PPCI) for myocardial infarction (MI) are increasingly frail and multi-morbid and modelling patient outcomes is important with limited healthcare resource. Recognised parameters and scores predicting survival after PPCI can be complex. The 4-Metre Gait Speed (4MGS) is simple, quick, low-cost and requires little training. A gait speed of <0.8 m/s is associated with increased mortality, independent of age in the general population, and with higher cardiovascular events and readmission post-MI. We evaluated the 4MGS as a predictor of mortality following PPCI.Methods560 patients, who had undergone PPCI from December 2013 – January 2016 and survived to discharge were recruited and divided into slow (<0.8 m/s) and fast (>= 0.8 m/s) walkers according to 4MGS. Recognised predictors of mortality following PPCI including age, renal disease, diabetes and left ventricular ejection function (LVEF) were recorded. The primary and principle secondary outcome measures were the ability of the 4MGS at discharge after PPCI to predict all-cause mortality at 1 and 5-years respectively. Mortality traces using the NHS Demographic Batch Service were run at 1 and 5-years. Cox proportional hazards regression analyses were conducted for mortality outcomes at 1 and 5-years. Univariate analyses for recognised predictors of mortality were conducted. Receiver operator characteristic (ROC) curves calculated the area under the curve (AUC) to determine the discriminate ability of each variable in predicting mortality. Results: At baseline, 457 patients (81.6%) were male with a mean age of 61.4 years. 94 (16.8%) were slow-walkers. At 1-year, 10 deaths were observed, with a trend towards higher mortality in slow vs fast walkers (4.3% vs 1.3%, HR=3.3, 95% CI 0.93, 11.7 p=0.06). At 5-years, 50 deaths were observed, with significantly higher mortality in slow vs fast walkers (19.1% vs 6.74%, HR=3.05, 95% CI 1.71, 5.45 p<0.0001) (Figure 1). Age >=65, LVEF <40% and renal disease but not diabetes were all associated with increased 5-year mortality. ROC analyses revealed the discriminate ability of each variable to predict mortality, from highest to lowest AUC; age >=65 (0.66), gait speed <0.8 m/s (0.61), LVEF <40% (0.57) and renal disease (0.52) (Figure 2). 4MGS provided no significant additive discriminate ability to age alone (p=0.11). Conclusions: The 4MGS is a simple point-of-care test which was able to predict 5-year mortality at discharge post PPCI. It demonstrated a higher predictive power than traditionally recognised cardiovascular risk factors, including diabetes, renal disease and LVEF. Age was the only risk factor with a stronger predictive power for mortality than 4MGS. 4MGS provided a 0.05 AUC improvement to age though this did not reach statistical significance. Conflict of Interest: None