High-Sensitivity Troponin T and Incident Heart Failure in Older Men: British Regional Heart Study

Paul Welsh,Olia Papacosta,Sheena Ramsay,Peter Whincup,John Mcmurray,Goya Wannamethee,Naveed Sattar

doi:10.1016/j.cardfail.2018.08.002

Abstract

The aim of this work was to study the association of high-sensitivity troponin T (hsTnT) with incident heart failure (HF), and implications for its use in prediction models. In the British Regional Heart Study, 3852 men aged 60-79years without baseline HF (3165 without baseline chronic heart disease) were followed for a median of 12.6years, during which 295 incident cases of HF occurred (7.7%). A 1-SD increase in log-transformed hsTnT was associated with a higher risk of incident HF after adjusting for classic risk factors (hazard ratio [HR] 1.58, 95% confidence interval [CI] 1.42-1.77) and after additional adjustment for N-terminal pro-B-type natriuretic peptide (NT-proBNP; HR 1.34, 95% CI 1.19-1.52). The strength of the association between hsTnT and incident HF did not differ by strata of other risk factors. An hsTnT concentration of <5ng/L had a sensitivity of 99.7% (95% CI 98.1%-99.9%) and a specificity of 3.4% (95% CI 2.8%-4.0%). A risk-prediction model including classic risk factors and NT-proBNP yielded a C-index of 0.791, but addition of hsTnT did not further improve prediction (P = .28). Elevated hsTnT is consistently associated with risk of HF in older men. HF occurred rarely over 12years when baseline hsTnT was below the limit of detection. hsTnT measurement, however, does not improve HF prediction in a model already containing NT-proBNP.

Highlights

We examined whether the measurement of high-sensitivity troponin T (hsTnT) usefully predicts risk of incident heart failure (HF) beyond the measurement of NT-proBNP
During a median follow-up period of 12.6 years, there were 295 incident cases of HF in the whole cohort (n = 3852; incidence 7.7%), including 201 incident cases (6.4%) in those without baseline coronary heart disease (CHD) (n = 3165) and 94 incident cases (13.7%) in those with baseline CHD (n = 687; P < .001). Those who experienced HF during follow-up were generally older, had higher body mass index (BMI) and waist circumference, were more likely to have diabetes, had lower forced expiratory volume in 1 second (FEV1) and examination. Predicted glomerular filtration rate (eGFR), had higher heart rate, were more likely to be on blood pressureÀlowering medication and to have atrial fibrillation and higher C-reactive protein (CRP)
In this cohort of older British men, hsTnT was consistently strongly associated with incident HF, suggesting that subclinical myocardial damage may be an important risk factor for HF, even in individuals without diagnosed CHD

Summary

Methods

The British Regional Heart Study was a socioeconomically representative prospective study of 7735 men aged 40À59 years and of predominantly white European ethnicity (>99%), drawn from 1 general practice in each of 24 British towns, who were screened from 1978 to 1980.14 In 1998À2000, surviving men aged 60À79 years were invited for a 20th-year follow-up examination, on which the present analyses were based.[15,16] Ethical approval was obtained from all relevant local Research Ethics Committees, and informed consent had been obtained from the subjects. Multiple imputation with the use of chained equations was used to generate 10 datasets with complete data.[18] The imputation model included hsTnT, age, cardiovascular disease (CVD), diabetes, incident HF (none missing), smoking (4 missing), index of deprivation (6 missing), atrial fibrillation (9 missing), heart rate (10 missing), systolic blood pressure (17 missing), body mass index (BMI; 17 missing), C-reactive protein (CRP; 31 missing), eGFR (35 missing), total cholesterol (38 missing), glucose (39 missing), forced expiratory volume in 1 second (FEV1; 40 missing), blood pressure medications (49 missing), alcohol use (57 missing), high-density lipoprotein (HDL) cholesterol (61 missing), physical activity (138 missing), and NT-proBNP (272 missing). All analyses were performed in Stata (version 14.2) and R (version 3.3.1, with the use of the survIDINRI package and 5000 bootstrap samples to generate confidence intervals for the NRI and IDI)

Results

Discussion

Conclusions

Disclosures